module Tensorflow::RawOps

Public Class Methods

_arg(typeT: nil, index: nil, name: "_Arg") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5011
def self._arg(typeT: nil, index: nil, name: "_Arg")
  self.execute("_Arg", [], T: typeT, index: index, name: name)
end
_array_to_list(input, typeT: nil, n: nil, out_types: nil, name: "_ArrayToList") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5015
def self._array_to_list(input, typeT: nil, n: nil, out_types: nil, name: "_ArrayToList")
  self.execute("_ArrayToList", [input], T: typeT, N: n, out_types: out_types, name: name)
end
_configure_distributed_tpu(inputs, n: nil, enable_whole_mesh_compilations: false, name: "_ConfigureDistributedTPU") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5019
def self._configure_distributed_tpu(inputs, n: nil, enable_whole_mesh_compilations: false, name: "_ConfigureDistributedTPU")
  self.execute("_ConfigureDistributedTPU", [inputs], N: n, enable_whole_mesh_compilations: enable_whole_mesh_compilations, name: name)
end
_device_arg(typeT: nil, index: nil, name: "_DeviceArg") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5023
def self._device_arg(typeT: nil, index: nil, name: "_DeviceArg")
  self.execute("_DeviceArg", [], T: typeT, index: index, name: name)
end
_device_retval(input, typeT: nil, index: nil, name: "_DeviceRetval") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5027
def self._device_retval(input, typeT: nil, index: nil, name: "_DeviceRetval")
  self.execute("_DeviceRetval", [input], T: typeT, index: index, name: name)
end
_disconnect_host_from_distributed_tpu_system(name: "_DisconnectHostFromDistributedTPUSystem") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5031
def self._disconnect_host_from_distributed_tpu_system(name: "_DisconnectHostFromDistributedTPUSystem")
  self.execute("_DisconnectHostFromDistributedTPUSystem", [], name: name)
end
_fused_batch_norm_ex(x, scale, offset, mean, variance, side_input, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, num_side_inputs: 0, activation_mode: "Identity", data_format: "NHWC", is_training: true, name: "_FusedBatchNormEx") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5035
def self._fused_batch_norm_ex(x, scale, offset, mean, variance, side_input, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, num_side_inputs: 0, activation_mode: "Identity", data_format: "NHWC", is_training: true, name: "_FusedBatchNormEx")
  self.execute("_FusedBatchNormEx", [x, scale, offset, mean, variance, side_input], T: typeT, U: u, epsilon: epsilon, num_side_inputs: num_side_inputs, activation_mode: activation_mode, data_format: data_format, is_training: is_training, name: name)
end
_fused_conv2_d(input, filter, args, typeT: nil, num_args: nil, strides: nil, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], use_cudnn_on_gpu: true, fused_ops: [], epsilon: 9.999999747378752e-05, name: "_FusedConv2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5039
def self._fused_conv2_d(input, filter, args, typeT: nil, num_args: nil, strides: nil, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], use_cudnn_on_gpu: true, fused_ops: [], epsilon: 9.999999747378752e-05, name: "_FusedConv2D")
  self.execute("_FusedConv2D", [input, filter, args], T: typeT, num_args: num_args, strides: strides, padding: padding, explicit_paddings: explicit_paddings, data_format: data_format, dilations: dilations, use_cudnn_on_gpu: use_cudnn_on_gpu, fused_ops: fused_ops, epsilon: epsilon, name: name)
end
_fused_mat_mul(a, b, args, transpose_a: false, transpose_b: false, typeT: nil, num_args: nil, fused_ops: [], epsilon: 9.999999747378752e-05, name: "_FusedMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5043
def self._fused_mat_mul(a, b, args, transpose_a: false, transpose_b: false, typeT: nil, num_args: nil, fused_ops: [], epsilon: 9.999999747378752e-05, name: "_FusedMatMul")
  self.execute("_FusedMatMul", [a, b, args], transpose_a: transpose_a, transpose_b: transpose_b, T: typeT, num_args: num_args, fused_ops: fused_ops, epsilon: epsilon, name: name)
end
_host_cast(x, srct: nil, dstt: nil, truncate: false, name: "_HostCast") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5047
def self._host_cast(x, srct: nil, dstt: nil, truncate: false, name: "_HostCast")
  self.execute("_HostCast", [x], SrcT: srct, DstT: dstt, Truncate: truncate, name: name)
end
_host_recv(tensor_type: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_HostRecv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5051
def self._host_recv(tensor_type: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_HostRecv")
  self.execute("_HostRecv", [], tensor_type: tensor_type, tensor_name: tensor_name, send_device: send_device, send_device_incarnation: send_device_incarnation, recv_device: recv_device, client_terminated: client_terminated, name: name)
end
_host_send(tensor, typeT: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_HostSend") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5055
def self._host_send(tensor, typeT: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_HostSend")
  self.execute("_HostSend", [tensor], T: typeT, tensor_name: tensor_name, send_device: send_device, send_device_incarnation: send_device_incarnation, recv_device: recv_device, client_terminated: client_terminated, name: name)
end
_if(cond, input, tcond: nil, tin: nil, tout: nil, then_branch: nil, else_branch: nil, name: "_If") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5059
def self._if(cond, input, tcond: nil, tin: nil, tout: nil, then_branch: nil, else_branch: nil, name: "_If")
  self.execute("_If", [cond, input], Tcond: tcond, Tin: tin, Tout: tout, then_branch: then_branch, else_branch: else_branch, name: name)
end
_initialize_host_for_distributed_tpu(input, enable_whole_mesh_compilations: false, name: "_InitializeHostForDistributedTPU") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5063
def self._initialize_host_for_distributed_tpu(input, enable_whole_mesh_compilations: false, name: "_InitializeHostForDistributedTPU")
  self.execute("_InitializeHostForDistributedTPU", [input], enable_whole_mesh_compilations: enable_whole_mesh_compilations, name: name)
end
_list_to_array(input, tin: nil, typeT: nil, n: nil, name: "_ListToArray") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5067
def self._list_to_array(input, tin: nil, typeT: nil, n: nil, name: "_ListToArray")
  self.execute("_ListToArray", [input], Tin: tin, T: typeT, N: n, name: name)
end
_mkl_maximum(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklMaximum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5071
def self._mkl_maximum(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklMaximum")
  self.execute("_MklMaximum", [x, y, mkl_x, mkl_y], T: typeT, name: name)
end
_mkl_mul(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5075
def self._mkl_mul(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklMul")
  self.execute("_MklMul", [x, y, mkl_x, mkl_y], T: typeT, name: name)
end
_mkl_squared_difference(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklSquaredDifference") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5079
def self._mkl_squared_difference(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklSquaredDifference")
  self.execute("_MklSquaredDifference", [x, y, mkl_x, mkl_y], T: typeT, name: name)
end
_mkl_sub(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5083
def self._mkl_sub(x, y, mkl_x, mkl_y, typeT: nil, name: "_MklSub")
  self.execute("_MklSub", [x, y, mkl_x, mkl_y], T: typeT, name: name)
end
_nccl_broadcast_recv(shape, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclBroadcastRecv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5087
def self._nccl_broadcast_recv(shape, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclBroadcastRecv")
  self.execute("_NcclBroadcastRecv", [shape], T: typeT, num_devices: num_devices, shared_name: shared_name, name: name)
end
_nccl_broadcast_send(input, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclBroadcastSend") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5091
def self._nccl_broadcast_send(input, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclBroadcastSend")
  self.execute("_NcclBroadcastSend", [input], T: typeT, num_devices: num_devices, shared_name: shared_name, name: name)
end
_nccl_reduce_recv(input, reduction: nil, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclReduceRecv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5095
def self._nccl_reduce_recv(input, reduction: nil, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclReduceRecv")
  self.execute("_NcclReduceRecv", [input], reduction: reduction, T: typeT, num_devices: num_devices, shared_name: shared_name, name: name)
end
_nccl_reduce_send(input, reduction: nil, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclReduceSend") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5099
def self._nccl_reduce_send(input, reduction: nil, typeT: nil, num_devices: nil, shared_name: "", name: "_NcclReduceSend")
  self.execute("_NcclReduceSend", [input], reduction: reduction, T: typeT, num_devices: num_devices, shared_name: shared_name, name: name)
end
_parallel_concat_start(shape: nil, dtype: nil, name: "_ParallelConcatStart") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5103
def self._parallel_concat_start(shape: nil, dtype: nil, name: "_ParallelConcatStart")
  self.execute("_ParallelConcatStart", [], shape: shape, dtype: dtype, name: name)
end
_parallel_concat_update(value, update, typeT: nil, loc: nil, name: "_ParallelConcatUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5107
def self._parallel_concat_update(value, update, typeT: nil, loc: nil, name: "_ParallelConcatUpdate")
  self.execute("_ParallelConcatUpdate", [value, update], T: typeT, loc: loc, name: name)
end
_read_variables_op(resources, n: nil, dtypes: nil, name: "_ReadVariablesOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5111
def self._read_variables_op(resources, n: nil, dtypes: nil, name: "_ReadVariablesOp")
  self.execute("_ReadVariablesOp", [resources], N: n, dtypes: dtypes, name: name)
end
_recv(tensor_type: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_Recv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5115
def self._recv(tensor_type: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_Recv")
  self.execute("_Recv", [], tensor_type: tensor_type, tensor_name: tensor_name, send_device: send_device, send_device_incarnation: send_device_incarnation, recv_device: recv_device, client_terminated: client_terminated, name: name)
end
_retval(input, typeT: nil, index: nil, name: "_Retval") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5119
def self._retval(input, typeT: nil, index: nil, name: "_Retval")
  self.execute("_Retval", [input], T: typeT, index: index, name: name)
end
_scoped_allocator(shapes: nil, shape: nil, typeT: nil, sa_name: "", id: nil, expected_call_count: nil, name: "_ScopedAllocator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5123
def self._scoped_allocator(shapes: nil, shape: nil, typeT: nil, sa_name: "", id: nil, expected_call_count: nil, name: "_ScopedAllocator")
  self.execute("_ScopedAllocator", [], shapes: shapes, shape: shape, T: typeT, sa_name: sa_name, id: id, expected_call_count: expected_call_count, name: name)
end
_scoped_allocator_concat(backing, inputs, shape: nil, typeT: nil, reshape: false, sa_name: "", id: nil, n: nil, name: "_ScopedAllocatorConcat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5127
def self._scoped_allocator_concat(backing, inputs, shape: nil, typeT: nil, reshape: false, sa_name: "", id: nil, n: nil, name: "_ScopedAllocatorConcat")
  self.execute("_ScopedAllocatorConcat", [backing, inputs], shape: shape, T: typeT, reshape: reshape, sa_name: sa_name, id: id, N: n, name: name)
end
_scoped_allocator_split(concat, split, typeT: nil, sa_name: "", id: nil, n: nil, shapes: nil, name: "_ScopedAllocatorSplit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5131
def self._scoped_allocator_split(concat, split, typeT: nil, sa_name: "", id: nil, n: nil, shapes: nil, name: "_ScopedAllocatorSplit")
  self.execute("_ScopedAllocatorSplit", [concat, split], T: typeT, sa_name: sa_name, id: id, N: n, shapes: shapes, name: name)
end
_send(tensor, typeT: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_Send") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5135
def self._send(tensor, typeT: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "_Send")
  self.execute("_Send", [tensor], T: typeT, tensor_name: tensor_name, send_device: send_device, send_device_incarnation: send_device_incarnation, recv_device: recv_device, client_terminated: client_terminated, name: name)
end
_set_global_tpu_array(topology, name: "_SetGlobalTPUArray") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5139
def self._set_global_tpu_array(topology, name: "_SetGlobalTPUArray")
  self.execute("_SetGlobalTPUArray", [topology], name: name)
end
_shutdown_distributed_tpu(name: "_ShutdownDistributedTPU") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5143
def self._shutdown_distributed_tpu(name: "_ShutdownDistributedTPU")
  self.execute("_ShutdownDistributedTPU", [], name: name)
end
_switch_n(data, output_index, num_outs: nil, typeT: nil, name: "_SwitchN") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5147
def self._switch_n(data, output_index, num_outs: nil, typeT: nil, name: "_SwitchN")
  self.execute("_SwitchN", [data, output_index], num_outs: num_outs, T: typeT, name: name)
end
_tpu_replicate(inputs, broadcast_inputs, variables, guaranteed_constants, computation: nil, num_replicas: nil, num_cores_per_replica: 1, topology: "", use_tpu: true, device_assignment: [], host_compute_core: [], tinputs: nil, tbroadcast_inputs: nil, numvariables: nil, tguaranteed_constants: nil, output_types: nil, padding_map: [], step_marker_location: "STEP_MARK_AT_ENTRY", allow_soft_placement: false, name: "_TPUReplicate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5151
def self._tpu_replicate(inputs, broadcast_inputs, variables, guaranteed_constants, computation: nil, num_replicas: nil, num_cores_per_replica: 1, topology: "", use_tpu: true, device_assignment: [], host_compute_core: [], tinputs: nil, tbroadcast_inputs: nil, numvariables: nil, tguaranteed_constants: nil, output_types: nil, padding_map: [], step_marker_location: "STEP_MARK_AT_ENTRY", allow_soft_placement: false, name: "_TPUReplicate")
  self.execute("_TPUReplicate", [inputs, broadcast_inputs, variables, guaranteed_constants], computation: computation, num_replicas: num_replicas, num_cores_per_replica: num_cores_per_replica, topology: topology, use_tpu: use_tpu, device_assignment: device_assignment, host_compute_core: host_compute_core, Tinputs: tinputs, Tbroadcast_inputs: tbroadcast_inputs, NumVariables: numvariables, Tguaranteed_constants: tguaranteed_constants, output_types: output_types, padding_map: padding_map, step_marker_location: step_marker_location, allow_soft_placement: allow_soft_placement, name: name)
end
_unary_ops_composition(x, typeT: nil, op_names: nil, name: "_UnaryOpsComposition") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5155
def self._unary_ops_composition(x, typeT: nil, op_names: nil, name: "_UnaryOpsComposition")
  self.execute("_UnaryOpsComposition", [x], T: typeT, op_names: op_names, name: name)
end
_var_handles_op(containers: nil, shared_names: nil, n: nil, dtypes: nil, shapes: nil, name: "_VarHandlesOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5159
def self._var_handles_op(containers: nil, shared_names: nil, n: nil, dtypes: nil, shapes: nil, name: "_VarHandlesOp")
  self.execute("_VarHandlesOp", [], containers: containers, shared_names: shared_names, N: n, dtypes: dtypes, shapes: shapes, name: name)
end
_wait_for_distributed_tpu(inputs, startup_timeout_sec: 20, n: nil, name: "_WaitForDistributedTPU") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5163
def self._wait_for_distributed_tpu(inputs, startup_timeout_sec: 20, n: nil, name: "_WaitForDistributedTPU")
  self.execute("_WaitForDistributedTPU", [inputs], startup_timeout_sec: startup_timeout_sec, N: n, name: name)
end
_while(input, typeT: nil, cond: nil, body: nil, name: "_While") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5167
def self._while(input, typeT: nil, cond: nil, body: nil, name: "_While")
  self.execute("_While", [input], T: typeT, cond: cond, body: body, name: name)
end
_xla_recv_at_host(dynamic_key, toutputs: nil, key: "", device_ordinal: nil, name: "_XlaRecvAtHost") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5171
def self._xla_recv_at_host(dynamic_key, toutputs: nil, key: "", device_ordinal: nil, name: "_XlaRecvAtHost")
  self.execute("_XlaRecvAtHost", [dynamic_key], Toutputs: toutputs, key: key, device_ordinal: device_ordinal, name: name)
end
_xla_send_from_host(inputs, dynamic_key, tinputs: nil, key: "", device_ordinal: nil, name: "_XlaSendFromHost") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5175
def self._xla_send_from_host(inputs, dynamic_key, tinputs: nil, key: "", device_ordinal: nil, name: "_XlaSendFromHost")
  self.execute("_XlaSendFromHost", [inputs, dynamic_key], Tinputs: tinputs, key: key, device_ordinal: device_ordinal, name: name)
end
abort(error_msg: "", exit_without_error: false, name: "Abort") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 18
def self.abort(error_msg: "", exit_without_error: false, name: "Abort")
  self.execute("Abort", [], error_msg: error_msg, exit_without_error: exit_without_error, name: name)
end
abs(x, typeT: nil, name: "Abs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 22
def self.abs(x, typeT: nil, name: "Abs")
  self.execute("Abs", [x], T: typeT, name: name)
end
accumulate_nv2(inputs, n: nil, typeT: nil, shape: nil, name: "AccumulateNV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 26
def self.accumulate_nv2(inputs, n: nil, typeT: nil, shape: nil, name: "AccumulateNV2")
  self.execute("AccumulateNV2", [inputs], N: n, T: typeT, shape: shape, name: name)
end
accumulator_apply_gradient(handle, local_step, gradient, dtype: nil, name: "AccumulatorApplyGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 30
def self.accumulator_apply_gradient(handle, local_step, gradient, dtype: nil, name: "AccumulatorApplyGradient")
  self.execute("AccumulatorApplyGradient", [handle, local_step, gradient], dtype: dtype, name: name)
end
accumulator_num_accumulated(handle, name: "AccumulatorNumAccumulated") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 34
def self.accumulator_num_accumulated(handle, name: "AccumulatorNumAccumulated")
  self.execute("AccumulatorNumAccumulated", [handle], name: name)
end
accumulator_set_global_step(handle, new_global_step, name: "AccumulatorSetGlobalStep") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 38
def self.accumulator_set_global_step(handle, new_global_step, name: "AccumulatorSetGlobalStep")
  self.execute("AccumulatorSetGlobalStep", [handle, new_global_step], name: name)
end
accumulator_take_gradient(handle, num_required, dtype: nil, name: "AccumulatorTakeGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 42
def self.accumulator_take_gradient(handle, num_required, dtype: nil, name: "AccumulatorTakeGradient")
  self.execute("AccumulatorTakeGradient", [handle, num_required], dtype: dtype, name: name)
end
acos(x, typeT: nil, name: "Acos") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 46
def self.acos(x, typeT: nil, name: "Acos")
  self.execute("Acos", [x], T: typeT, name: name)
end
acosh(x, typeT: nil, name: "Acosh") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 50
def self.acosh(x, typeT: nil, name: "Acosh")
  self.execute("Acosh", [x], T: typeT, name: name)
end
add(x, y, typeT: nil, name: "Add") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 54
def self.add(x, y, typeT: nil, name: "Add")
  self.execute("Add", [x, y], T: typeT, name: name)
end
add_many_sparse_to_tensors_map(sparse_indices, sparse_values, sparse_shape, typeT: nil, container: "", shared_name: "", name: "AddManySparseToTensorsMap") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 58
def self.add_many_sparse_to_tensors_map(sparse_indices, sparse_values, sparse_shape, typeT: nil, container: "", shared_name: "", name: "AddManySparseToTensorsMap")
  self.execute("AddManySparseToTensorsMap", [sparse_indices, sparse_values, sparse_shape], T: typeT, container: container, shared_name: shared_name, name: name)
end
add_n(inputs, n: nil, typeT: nil, name: "AddN") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 62
def self.add_n(inputs, n: nil, typeT: nil, name: "AddN")
  self.execute("AddN", [inputs], N: n, T: typeT, name: name)
end
add_sparse_to_tensors_map(sparse_indices, sparse_values, sparse_shape, typeT: nil, container: "", shared_name: "", name: "AddSparseToTensorsMap") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 66
def self.add_sparse_to_tensors_map(sparse_indices, sparse_values, sparse_shape, typeT: nil, container: "", shared_name: "", name: "AddSparseToTensorsMap")
  self.execute("AddSparseToTensorsMap", [sparse_indices, sparse_values, sparse_shape], T: typeT, container: container, shared_name: shared_name, name: name)
end
add_v2(x, y, typeT: nil, name: "AddV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 70
def self.add_v2(x, y, typeT: nil, name: "AddV2")
  self.execute("AddV2", [x, y], T: typeT, name: name)
end
adjust_contrast(images, contrast_factor, min_value, max_value, typeT: nil, name: "AdjustContrast") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 74
def self.adjust_contrast(images, contrast_factor, min_value, max_value, typeT: nil, name: "AdjustContrast")
  self.execute("AdjustContrast", [images, contrast_factor, min_value, max_value], T: typeT, name: name)
end
adjust_contrastv2(images, contrast_factor, typeT: :float, name: "AdjustContrastv2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 78
def self.adjust_contrastv2(images, contrast_factor, typeT: :float, name: "AdjustContrastv2")
  self.execute("AdjustContrastv2", [images, contrast_factor], T: typeT, name: name)
end
adjust_hue(images, delta, typeT: :float, name: "AdjustHue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 82
def self.adjust_hue(images, delta, typeT: :float, name: "AdjustHue")
  self.execute("AdjustHue", [images, delta], T: typeT, name: name)
end
adjust_saturation(images, scale, typeT: :float, name: "AdjustSaturation") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 86
def self.adjust_saturation(images, scale, typeT: :float, name: "AdjustSaturation")
  self.execute("AdjustSaturation", [images, scale], T: typeT, name: name)
end
all(input, reduction_indices, keep_dims: false, tidx: :int32, name: "All") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 90
def self.all(input, reduction_indices, keep_dims: false, tidx: :int32, name: "All")
  self.execute("All", [input, reduction_indices], keep_dims: keep_dims, Tidx: tidx, name: name)
end
all_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, seed: 0, seed2: 0, name: "AllCandidateSampler") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 94
def self.all_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, seed: 0, seed2: 0, name: "AllCandidateSampler")
  self.execute("AllCandidateSampler", [true_classes], num_true: num_true, num_sampled: num_sampled, unique: unique, seed: seed, seed2: seed2, name: name)
end
all_to_all(input, group_assignment, typeT: nil, concat_dimension: nil, split_dimension: nil, split_count: nil, name: "AllToAll") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 98
def self.all_to_all(input, group_assignment, typeT: nil, concat_dimension: nil, split_dimension: nil, split_count: nil, name: "AllToAll")
  self.execute("AllToAll", [input, group_assignment], T: typeT, concat_dimension: concat_dimension, split_dimension: split_dimension, split_count: split_count, name: name)
end
angle(input, typeT: :complex64, tout: :float, name: "Angle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 102
def self.angle(input, typeT: :complex64, tout: :float, name: "Angle")
  self.execute("Angle", [input], T: typeT, Tout: tout, name: name)
end
anonymous_iterator(output_types: nil, output_shapes: nil, name: "AnonymousIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 106
def self.anonymous_iterator(output_types: nil, output_shapes: nil, name: "AnonymousIterator")
  self.execute("AnonymousIterator", [], output_types: output_types, output_shapes: output_shapes, name: name)
end
anonymous_iterator_v2(output_types: nil, output_shapes: nil, name: "AnonymousIteratorV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 110
def self.anonymous_iterator_v2(output_types: nil, output_shapes: nil, name: "AnonymousIteratorV2")
  self.execute("AnonymousIteratorV2", [], output_types: output_types, output_shapes: output_shapes, name: name)
end
anonymous_memory_cache(name: "AnonymousMemoryCache") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 114
def self.anonymous_memory_cache(name: "AnonymousMemoryCache")
  self.execute("AnonymousMemoryCache", [], name: name)
end
anonymous_multi_device_iterator(devices: nil, output_types: nil, output_shapes: nil, name: "AnonymousMultiDeviceIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 118
def self.anonymous_multi_device_iterator(devices: nil, output_types: nil, output_shapes: nil, name: "AnonymousMultiDeviceIterator")
  self.execute("AnonymousMultiDeviceIterator", [], devices: devices, output_types: output_types, output_shapes: output_shapes, name: name)
end
anonymous_random_seed_generator(seed, seed2, name: "AnonymousRandomSeedGenerator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 122
def self.anonymous_random_seed_generator(seed, seed2, name: "AnonymousRandomSeedGenerator")
  self.execute("AnonymousRandomSeedGenerator", [seed, seed2], name: name)
end
any(input, reduction_indices, keep_dims: false, tidx: :int32, name: "Any") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 126
def self.any(input, reduction_indices, keep_dims: false, tidx: :int32, name: "Any")
  self.execute("Any", [input, reduction_indices], keep_dims: keep_dims, Tidx: tidx, name: name)
end
apply_ada_max(var, m, v, beta1_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyAdaMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 130
def self.apply_ada_max(var, m, v, beta1_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyAdaMax")
  self.execute("ApplyAdaMax", [var, m, v, beta1_power, lr, beta1, beta2, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyAdadelta") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 134
def self.apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyAdadelta")
  self.execute("ApplyAdadelta", [var, accum, accum_update, lr, rho, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
apply_adagrad(var, accum, lr, grad, typeT: nil, use_locking: false, update_slots: true, name: "ApplyAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 138
def self.apply_adagrad(var, accum, lr, grad, typeT: nil, use_locking: false, update_slots: true, name: "ApplyAdagrad")
  self.execute("ApplyAdagrad", [var, accum, lr, grad], T: typeT, use_locking: use_locking, update_slots: update_slots, name: name)
end
apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, lr, l1, l2, global_step, typeT: nil, use_locking: false, name: "ApplyAdagradDA") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 142
def self.apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, lr, l1, l2, global_step, typeT: nil, use_locking: false, name: "ApplyAdagradDA")
  self.execute("ApplyAdagradDA", [var, gradient_accumulator, gradient_squared_accumulator, grad, lr, l1, l2, global_step], T: typeT, use_locking: use_locking, name: name)
end
apply_adagrad_v2(var, accum, lr, epsilon, grad, typeT: nil, use_locking: false, update_slots: true, name: "ApplyAdagradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 146
def self.apply_adagrad_v2(var, accum, lr, epsilon, grad, typeT: nil, use_locking: false, update_slots: true, name: "ApplyAdagradV2")
  self.execute("ApplyAdagradV2", [var, accum, lr, epsilon, grad], T: typeT, use_locking: use_locking, update_slots: update_slots, name: name)
end
apply_adam(var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, use_nesterov: false, name: "ApplyAdam") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 150
def self.apply_adam(var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, use_nesterov: false, name: "ApplyAdam")
  self.execute("ApplyAdam", [var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad], T: typeT, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
apply_add_sign(var, m, lr, alpha, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ApplyAddSign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 154
def self.apply_add_sign(var, m, lr, alpha, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ApplyAddSign")
  self.execute("ApplyAddSign", [var, m, lr, alpha, sign_decay, beta, grad], T: typeT, use_locking: use_locking, name: name)
end
apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyCenteredRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 158
def self.apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyCenteredRMSProp")
  self.execute("ApplyCenteredRMSProp", [var, mg, ms, mom, lr, rho, momentum, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
apply_ftrl(var, accum, linear, grad, lr, l1, l2, lr_power, typeT: nil, use_locking: false, name: "ApplyFtrl") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 162
def self.apply_ftrl(var, accum, linear, grad, lr, l1, l2, lr_power, typeT: nil, use_locking: false, name: "ApplyFtrl")
  self.execute("ApplyFtrl", [var, accum, linear, grad, lr, l1, l2, lr_power], T: typeT, use_locking: use_locking, name: name)
end
apply_ftrl_v2(var, accum, linear, grad, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, use_locking: false, name: "ApplyFtrlV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 166
def self.apply_ftrl_v2(var, accum, linear, grad, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, use_locking: false, name: "ApplyFtrlV2")
  self.execute("ApplyFtrlV2", [var, accum, linear, grad, lr, l1, l2, l2_shrinkage, lr_power], T: typeT, use_locking: use_locking, name: name)
end
apply_gradient_descent(var, alpha, delta, typeT: nil, use_locking: false, name: "ApplyGradientDescent") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 170
def self.apply_gradient_descent(var, alpha, delta, typeT: nil, use_locking: false, name: "ApplyGradientDescent")
  self.execute("ApplyGradientDescent", [var, alpha, delta], T: typeT, use_locking: use_locking, name: name)
end
apply_momentum(var, accum, lr, grad, momentum, typeT: nil, use_locking: false, use_nesterov: false, name: "ApplyMomentum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 174
def self.apply_momentum(var, accum, lr, grad, momentum, typeT: nil, use_locking: false, use_nesterov: false, name: "ApplyMomentum")
  self.execute("ApplyMomentum", [var, accum, lr, grad, momentum], T: typeT, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
apply_power_sign(var, m, lr, logbase, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ApplyPowerSign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 178
def self.apply_power_sign(var, m, lr, logbase, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ApplyPowerSign")
  self.execute("ApplyPowerSign", [var, m, lr, logbase, sign_decay, beta, grad], T: typeT, use_locking: use_locking, name: name)
end
apply_proximal_adagrad(var, accum, lr, l1, l2, grad, typeT: nil, use_locking: false, name: "ApplyProximalAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 182
def self.apply_proximal_adagrad(var, accum, lr, l1, l2, grad, typeT: nil, use_locking: false, name: "ApplyProximalAdagrad")
  self.execute("ApplyProximalAdagrad", [var, accum, lr, l1, l2, grad], T: typeT, use_locking: use_locking, name: name)
end
apply_proximal_gradient_descent(var, alpha, l1, l2, delta, typeT: nil, use_locking: false, name: "ApplyProximalGradientDescent") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 186
def self.apply_proximal_gradient_descent(var, alpha, l1, l2, delta, typeT: nil, use_locking: false, name: "ApplyProximalGradientDescent")
  self.execute("ApplyProximalGradientDescent", [var, alpha, l1, l2, delta], T: typeT, use_locking: use_locking, name: name)
end
apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 190
def self.apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ApplyRMSProp")
  self.execute("ApplyRMSProp", [var, ms, mom, lr, rho, momentum, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
approximate_equal(x, y, typeT: nil, tolerance: 9.999999747378752e-06, name: "ApproximateEqual") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 194
def self.approximate_equal(x, y, typeT: nil, tolerance: 9.999999747378752e-06, name: "ApproximateEqual")
  self.execute("ApproximateEqual", [x, y], T: typeT, tolerance: tolerance, name: name)
end
arg_max(input, dimension, typeT: nil, tidx: :int32, output_type: :int64, name: "ArgMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 198
def self.arg_max(input, dimension, typeT: nil, tidx: :int32, output_type: :int64, name: "ArgMax")
  self.execute("ArgMax", [input, dimension], T: typeT, Tidx: tidx, output_type: output_type, name: name)
end
arg_min(input, dimension, typeT: nil, tidx: :int32, output_type: :int64, name: "ArgMin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 202
def self.arg_min(input, dimension, typeT: nil, tidx: :int32, output_type: :int64, name: "ArgMin")
  self.execute("ArgMin", [input, dimension], T: typeT, Tidx: tidx, output_type: output_type, name: name)
end
as_string(input, typeT: nil, precision: -1, scientific: false, shortest: false, width: -1, fill: "", name: "AsString") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 206
def self.as_string(input, typeT: nil, precision: -1, scientific: false, shortest: false, width: -1, fill: "", name: "AsString")
  self.execute("AsString", [input], T: typeT, precision: precision, scientific: scientific, shortest: shortest, width: width, fill: fill, name: name)
end
asin(x, typeT: nil, name: "Asin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 210
def self.asin(x, typeT: nil, name: "Asin")
  self.execute("Asin", [x], T: typeT, name: name)
end
asinh(x, typeT: nil, name: "Asinh") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 214
def self.asinh(x, typeT: nil, name: "Asinh")
  self.execute("Asinh", [x], T: typeT, name: name)
end
assert(condition, data, typeT: nil, summarize: 3, name: "Assert") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 218
def self.assert(condition, data, typeT: nil, summarize: 3, name: "Assert")
  self.execute("Assert", [condition, data], T: typeT, summarize: summarize, name: name)
end
assert_next_dataset(input_dataset, transformations, output_types: nil, output_shapes: nil, name: "AssertNextDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 222
def self.assert_next_dataset(input_dataset, transformations, output_types: nil, output_shapes: nil, name: "AssertNextDataset")
  self.execute("AssertNextDataset", [input_dataset, transformations], output_types: output_types, output_shapes: output_shapes, name: name)
end
assign(ref, value, typeT: nil, validate_shape: true, use_locking: true, name: "Assign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 226
def self.assign(ref, value, typeT: nil, validate_shape: true, use_locking: true, name: "Assign")
  self.execute("Assign", [ref, value], T: typeT, validate_shape: validate_shape, use_locking: use_locking, name: name)
end
assign_add(ref, value, typeT: nil, use_locking: false, name: "AssignAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 230
def self.assign_add(ref, value, typeT: nil, use_locking: false, name: "AssignAdd")
  self.execute("AssignAdd", [ref, value], T: typeT, use_locking: use_locking, name: name)
end
assign_add_variable_op(resource, value, dtype: nil, name: "AssignAddVariableOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 234
def self.assign_add_variable_op(resource, value, dtype: nil, name: "AssignAddVariableOp")
  self.execute("AssignAddVariableOp", [resource, value], dtype: dtype, name: name)
end
assign_sub(ref, value, typeT: nil, use_locking: false, name: "AssignSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 238
def self.assign_sub(ref, value, typeT: nil, use_locking: false, name: "AssignSub")
  self.execute("AssignSub", [ref, value], T: typeT, use_locking: use_locking, name: name)
end
assign_sub_variable_op(resource, value, dtype: nil, name: "AssignSubVariableOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 242
def self.assign_sub_variable_op(resource, value, dtype: nil, name: "AssignSubVariableOp")
  self.execute("AssignSubVariableOp", [resource, value], dtype: dtype, name: name)
end
assign_variable_op(resource, value, dtype: nil, name: "AssignVariableOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 246
def self.assign_variable_op(resource, value, dtype: nil, name: "AssignVariableOp")
  self.execute("AssignVariableOp", [resource, value], dtype: dtype, name: name)
end
atan(x, typeT: nil, name: "Atan") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 250
def self.atan(x, typeT: nil, name: "Atan")
  self.execute("Atan", [x], T: typeT, name: name)
end
atan2(y, x, typeT: nil, name: "Atan2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 254
def self.atan2(y, x, typeT: nil, name: "Atan2")
  self.execute("Atan2", [y, x], T: typeT, name: name)
end
atanh(x, typeT: nil, name: "Atanh") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 258
def self.atanh(x, typeT: nil, name: "Atanh")
  self.execute("Atanh", [x], T: typeT, name: name)
end
audio_spectrogram(input, window_size: nil, stride: nil, magnitude_squared: false, name: "AudioSpectrogram") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 262
def self.audio_spectrogram(input, window_size: nil, stride: nil, magnitude_squared: false, name: "AudioSpectrogram")
  self.execute("AudioSpectrogram", [input], window_size: window_size, stride: stride, magnitude_squared: magnitude_squared, name: name)
end
audio_summary(tag, tensor, sample_rate: nil, max_outputs: 3, name: "AudioSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 266
def self.audio_summary(tag, tensor, sample_rate: nil, max_outputs: 3, name: "AudioSummary")
  self.execute("AudioSummary", [tag, tensor], sample_rate: sample_rate, max_outputs: max_outputs, name: name)
end
audio_summary_v2(tag, tensor, sample_rate, max_outputs: 3, name: "AudioSummaryV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 270
def self.audio_summary_v2(tag, tensor, sample_rate, max_outputs: 3, name: "AudioSummaryV2")
  self.execute("AudioSummaryV2", [tag, tensor, sample_rate], max_outputs: max_outputs, name: name)
end
auto_shard_dataset(input_dataset, num_workers, index, auto_shard_policy: 0, output_types: nil, output_shapes: nil, name: "AutoShardDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 274
def self.auto_shard_dataset(input_dataset, num_workers, index, auto_shard_policy: 0, output_types: nil, output_shapes: nil, name: "AutoShardDataset")
  self.execute("AutoShardDataset", [input_dataset, num_workers, index], auto_shard_policy: auto_shard_policy, output_types: output_types, output_shapes: output_shapes, name: name)
end
avg_pool(value, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: nil, name: "AvgPool") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 278
def self.avg_pool(value, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: nil, name: "AvgPool")
  self.execute("AvgPool", [value], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
avg_pool3_d(input, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "AvgPool3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 282
def self.avg_pool3_d(input, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "AvgPool3D")
  self.execute("AvgPool3D", [input], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
avg_pool3_d_grad(orig_input_shape, grad, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "AvgPool3DGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 286
def self.avg_pool3_d_grad(orig_input_shape, grad, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "AvgPool3DGrad")
  self.execute("AvgPool3DGrad", [orig_input_shape, grad], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
avg_pool_grad(orig_input_shape, grad, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: nil, name: "AvgPoolGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 290
def self.avg_pool_grad(orig_input_shape, grad, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: nil, name: "AvgPoolGrad")
  self.execute("AvgPoolGrad", [orig_input_shape, grad], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
barrier(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "Barrier") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 294
def self.barrier(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "Barrier")
  self.execute("Barrier", [], component_types: component_types, shapes: shapes, capacity: capacity, container: container, shared_name: shared_name, name: name)
end
barrier_close(handle, cancel_pending_enqueues: false, name: "BarrierClose") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 298
def self.barrier_close(handle, cancel_pending_enqueues: false, name: "BarrierClose")
  self.execute("BarrierClose", [handle], cancel_pending_enqueues: cancel_pending_enqueues, name: name)
end
barrier_incomplete_size(handle, name: "BarrierIncompleteSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 302
def self.barrier_incomplete_size(handle, name: "BarrierIncompleteSize")
  self.execute("BarrierIncompleteSize", [handle], name: name)
end
barrier_insert_many(handle, keys, values, typeT: nil, component_index: nil, name: "BarrierInsertMany") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 306
def self.barrier_insert_many(handle, keys, values, typeT: nil, component_index: nil, name: "BarrierInsertMany")
  self.execute("BarrierInsertMany", [handle, keys, values], T: typeT, component_index: component_index, name: name)
end
barrier_ready_size(handle, name: "BarrierReadySize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 310
def self.barrier_ready_size(handle, name: "BarrierReadySize")
  self.execute("BarrierReadySize", [handle], name: name)
end
barrier_take_many(handle, num_elements, component_types: nil, allow_small_batch: false, wait_for_incomplete: false, timeout_ms: -1, name: "BarrierTakeMany") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 314
def self.barrier_take_many(handle, num_elements, component_types: nil, allow_small_batch: false, wait_for_incomplete: false, timeout_ms: -1, name: "BarrierTakeMany")
  self.execute("BarrierTakeMany", [handle, num_elements], component_types: component_types, allow_small_batch: allow_small_batch, wait_for_incomplete: wait_for_incomplete, timeout_ms: timeout_ms, name: name)
end
batch(in_tensors, num_batch_threads: nil, max_batch_size: nil, max_enqueued_batches: 10, batch_timeout_micros: nil, allowed_batch_sizes: [], grad_timeout_micros: nil, container: "", shared_name: "", batching_queue: "", typeT: nil, name: "Batch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 318
def self.batch(in_tensors, num_batch_threads: nil, max_batch_size: nil, max_enqueued_batches: 10, batch_timeout_micros: nil, allowed_batch_sizes: [], grad_timeout_micros: nil, container: "", shared_name: "", batching_queue: "", typeT: nil, name: "Batch")
  self.execute("Batch", [in_tensors], num_batch_threads: num_batch_threads, max_batch_size: max_batch_size, max_enqueued_batches: max_enqueued_batches, batch_timeout_micros: batch_timeout_micros, allowed_batch_sizes: allowed_batch_sizes, grad_timeout_micros: grad_timeout_micros, container: container, shared_name: shared_name, batching_queue: batching_queue, T: typeT, name: name)
end
batch_cholesky(input, typeT: nil, name: "BatchCholesky") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 322
def self.batch_cholesky(input, typeT: nil, name: "BatchCholesky")
  self.execute("BatchCholesky", [input], T: typeT, name: name)
end
batch_cholesky_grad(l, grad, typeT: nil, name: "BatchCholeskyGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 326
def self.batch_cholesky_grad(l, grad, typeT: nil, name: "BatchCholeskyGrad")
  self.execute("BatchCholeskyGrad", [l, grad], T: typeT, name: name)
end
batch_dataset(input_dataset, batch_size, output_types: nil, output_shapes: nil, name: "BatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 330
def self.batch_dataset(input_dataset, batch_size, output_types: nil, output_shapes: nil, name: "BatchDataset")
  self.execute("BatchDataset", [input_dataset, batch_size], output_types: output_types, output_shapes: output_shapes, name: name)
end
batch_dataset_v2(input_dataset, batch_size, drop_remainder, parallel_copy: false, output_types: nil, output_shapes: nil, name: "BatchDatasetV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 334
def self.batch_dataset_v2(input_dataset, batch_size, drop_remainder, parallel_copy: false, output_types: nil, output_shapes: nil, name: "BatchDatasetV2")
  self.execute("BatchDatasetV2", [input_dataset, batch_size, drop_remainder], parallel_copy: parallel_copy, output_types: output_types, output_shapes: output_shapes, name: name)
end
batch_fft(input, name: "BatchFFT") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 338
def self.batch_fft(input, name: "BatchFFT")
  self.execute("BatchFFT", [input], name: name)
end
batch_fft2_d(input, name: "BatchFFT2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 342
def self.batch_fft2_d(input, name: "BatchFFT2D")
  self.execute("BatchFFT2D", [input], name: name)
end
batch_fft3_d(input, name: "BatchFFT3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 346
def self.batch_fft3_d(input, name: "BatchFFT3D")
  self.execute("BatchFFT3D", [input], name: name)
end
batch_function(in_tensors, captured_tensors, f: nil, num_batch_threads: nil, max_batch_size: nil, batch_timeout_micros: nil, max_enqueued_batches: 10, allowed_batch_sizes: [], container: "", shared_name: "", batching_queue: "", tin: nil, tcaptured: nil, tout: nil, name: "BatchFunction") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 350
def self.batch_function(in_tensors, captured_tensors, f: nil, num_batch_threads: nil, max_batch_size: nil, batch_timeout_micros: nil, max_enqueued_batches: 10, allowed_batch_sizes: [], container: "", shared_name: "", batching_queue: "", tin: nil, tcaptured: nil, tout: nil, name: "BatchFunction")
  self.execute("BatchFunction", [in_tensors, captured_tensors], f: f, num_batch_threads: num_batch_threads, max_batch_size: max_batch_size, batch_timeout_micros: batch_timeout_micros, max_enqueued_batches: max_enqueued_batches, allowed_batch_sizes: allowed_batch_sizes, container: container, shared_name: shared_name, batching_queue: batching_queue, Tin: tin, Tcaptured: tcaptured, Tout: tout, name: name)
end
batch_ifft(input, name: "BatchIFFT") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 354
def self.batch_ifft(input, name: "BatchIFFT")
  self.execute("BatchIFFT", [input], name: name)
end
batch_ifft2_d(input, name: "BatchIFFT2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 358
def self.batch_ifft2_d(input, name: "BatchIFFT2D")
  self.execute("BatchIFFT2D", [input], name: name)
end
batch_ifft3_d(input, name: "BatchIFFT3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 362
def self.batch_ifft3_d(input, name: "BatchIFFT3D")
  self.execute("BatchIFFT3D", [input], name: name)
end
batch_mat_mul(x, y, typeT: nil, adj_x: false, adj_y: false, name: "BatchMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 366
def self.batch_mat_mul(x, y, typeT: nil, adj_x: false, adj_y: false, name: "BatchMatMul")
  self.execute("BatchMatMul", [x, y], T: typeT, adj_x: adj_x, adj_y: adj_y, name: name)
end
batch_mat_mul_v2(x, y, typeT: nil, adj_x: false, adj_y: false, name: "BatchMatMulV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 370
def self.batch_mat_mul_v2(x, y, typeT: nil, adj_x: false, adj_y: false, name: "BatchMatMulV2")
  self.execute("BatchMatMulV2", [x, y], T: typeT, adj_x: adj_x, adj_y: adj_y, name: name)
end
batch_matrix_band_part(input, num_lower, num_upper, typeT: nil, name: "BatchMatrixBandPart") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 374
def self.batch_matrix_band_part(input, num_lower, num_upper, typeT: nil, name: "BatchMatrixBandPart")
  self.execute("BatchMatrixBandPart", [input, num_lower, num_upper], T: typeT, name: name)
end
batch_matrix_determinant(input, typeT: nil, name: "BatchMatrixDeterminant") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 378
def self.batch_matrix_determinant(input, typeT: nil, name: "BatchMatrixDeterminant")
  self.execute("BatchMatrixDeterminant", [input], T: typeT, name: name)
end
batch_matrix_diag(diagonal, typeT: nil, name: "BatchMatrixDiag") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 382
def self.batch_matrix_diag(diagonal, typeT: nil, name: "BatchMatrixDiag")
  self.execute("BatchMatrixDiag", [diagonal], T: typeT, name: name)
end
batch_matrix_diag_part(input, typeT: nil, name: "BatchMatrixDiagPart") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 386
def self.batch_matrix_diag_part(input, typeT: nil, name: "BatchMatrixDiagPart")
  self.execute("BatchMatrixDiagPart", [input], T: typeT, name: name)
end
batch_matrix_inverse(input, adjoint: false, typeT: nil, name: "BatchMatrixInverse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 390
def self.batch_matrix_inverse(input, adjoint: false, typeT: nil, name: "BatchMatrixInverse")
  self.execute("BatchMatrixInverse", [input], adjoint: adjoint, T: typeT, name: name)
end
batch_matrix_set_diag(input, diagonal, typeT: nil, name: "BatchMatrixSetDiag") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 394
def self.batch_matrix_set_diag(input, diagonal, typeT: nil, name: "BatchMatrixSetDiag")
  self.execute("BatchMatrixSetDiag", [input, diagonal], T: typeT, name: name)
end
batch_matrix_solve(matrix, rhs, adjoint: false, typeT: nil, name: "BatchMatrixSolve") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 398
def self.batch_matrix_solve(matrix, rhs, adjoint: false, typeT: nil, name: "BatchMatrixSolve")
  self.execute("BatchMatrixSolve", [matrix, rhs], adjoint: adjoint, T: typeT, name: name)
end
batch_matrix_solve_ls(matrix, rhs, l2_regularizer, typeT: nil, fast: true, name: "BatchMatrixSolveLs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 402
def self.batch_matrix_solve_ls(matrix, rhs, l2_regularizer, typeT: nil, fast: true, name: "BatchMatrixSolveLs")
  self.execute("BatchMatrixSolveLs", [matrix, rhs, l2_regularizer], T: typeT, fast: fast, name: name)
end
batch_matrix_triangular_solve(matrix, rhs, lower: true, adjoint: false, typeT: nil, name: "BatchMatrixTriangularSolve") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 406
def self.batch_matrix_triangular_solve(matrix, rhs, lower: true, adjoint: false, typeT: nil, name: "BatchMatrixTriangularSolve")
  self.execute("BatchMatrixTriangularSolve", [matrix, rhs], lower: lower, adjoint: adjoint, T: typeT, name: name)
end
batch_norm_with_global_normalization(t, m, v, beta, gamma, typeT: nil, variance_epsilon: nil, scale_after_normalization: nil, name: "BatchNormWithGlobalNormalization") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 410
def self.batch_norm_with_global_normalization(t, m, v, beta, gamma, typeT: nil, variance_epsilon: nil, scale_after_normalization: nil, name: "BatchNormWithGlobalNormalization")
  self.execute("BatchNormWithGlobalNormalization", [t, m, v, beta, gamma], T: typeT, variance_epsilon: variance_epsilon, scale_after_normalization: scale_after_normalization, name: name)
end
batch_norm_with_global_normalization_grad(t, m, v, gamma, backprop, typeT: nil, variance_epsilon: nil, scale_after_normalization: nil, name: "BatchNormWithGlobalNormalizationGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 414
def self.batch_norm_with_global_normalization_grad(t, m, v, gamma, backprop, typeT: nil, variance_epsilon: nil, scale_after_normalization: nil, name: "BatchNormWithGlobalNormalizationGrad")
  self.execute("BatchNormWithGlobalNormalizationGrad", [t, m, v, gamma, backprop], T: typeT, variance_epsilon: variance_epsilon, scale_after_normalization: scale_after_normalization, name: name)
end
batch_self_adjoint_eig(input, typeT: nil, name: "BatchSelfAdjointEig") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 418
def self.batch_self_adjoint_eig(input, typeT: nil, name: "BatchSelfAdjointEig")
  self.execute("BatchSelfAdjointEig", [input], T: typeT, name: name)
end
batch_self_adjoint_eig_v2(input, compute_v: true, typeT: nil, name: "BatchSelfAdjointEigV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 422
def self.batch_self_adjoint_eig_v2(input, compute_v: true, typeT: nil, name: "BatchSelfAdjointEigV2")
  self.execute("BatchSelfAdjointEigV2", [input], compute_v: compute_v, T: typeT, name: name)
end
batch_svd(input, compute_uv: true, full_matrices: false, typeT: nil, name: "BatchSvd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 426
def self.batch_svd(input, compute_uv: true, full_matrices: false, typeT: nil, name: "BatchSvd")
  self.execute("BatchSvd", [input], compute_uv: compute_uv, full_matrices: full_matrices, T: typeT, name: name)
end
batch_to_space(input, crops, typeT: nil, block_size: nil, tidx: :int32, name: "BatchToSpace") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 430
def self.batch_to_space(input, crops, typeT: nil, block_size: nil, tidx: :int32, name: "BatchToSpace")
  self.execute("BatchToSpace", [input, crops], T: typeT, block_size: block_size, Tidx: tidx, name: name)
end
batch_to_space_nd(input, block_shape, crops, typeT: nil, tblock_shape: :int32, tcrops: :int32, name: "BatchToSpaceND") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 434
def self.batch_to_space_nd(input, block_shape, crops, typeT: nil, tblock_shape: :int32, tcrops: :int32, name: "BatchToSpaceND")
  self.execute("BatchToSpaceND", [input, block_shape, crops], T: typeT, Tblock_shape: tblock_shape, Tcrops: tcrops, name: name)
end
bessel_i0e(x, typeT: nil, name: "BesselI0e") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 438
def self.bessel_i0e(x, typeT: nil, name: "BesselI0e")
  self.execute("BesselI0e", [x], T: typeT, name: name)
end
bessel_i1e(x, typeT: nil, name: "BesselI1e") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 442
def self.bessel_i1e(x, typeT: nil, name: "BesselI1e")
  self.execute("BesselI1e", [x], T: typeT, name: name)
end
betainc(a, b, x, typeT: nil, name: "Betainc") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 446
def self.betainc(a, b, x, typeT: nil, name: "Betainc")
  self.execute("Betainc", [a, b, x], T: typeT, name: name)
end
bias_add(value, bias, typeT: nil, data_format: "NHWC", name: "BiasAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 450
def self.bias_add(value, bias, typeT: nil, data_format: "NHWC", name: "BiasAdd")
  self.execute("BiasAdd", [value, bias], T: typeT, data_format: data_format, name: name)
end
bias_add_grad(out_backprop, typeT: nil, data_format: "NHWC", name: "BiasAddGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 454
def self.bias_add_grad(out_backprop, typeT: nil, data_format: "NHWC", name: "BiasAddGrad")
  self.execute("BiasAddGrad", [out_backprop], T: typeT, data_format: data_format, name: name)
end
bias_add_v1(value, bias, typeT: nil, name: "BiasAddV1") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 458
def self.bias_add_v1(value, bias, typeT: nil, name: "BiasAddV1")
  self.execute("BiasAddV1", [value, bias], T: typeT, name: name)
end
bincount(arr, size, weights, typeT: nil, name: "Bincount") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 462
def self.bincount(arr, size, weights, typeT: nil, name: "Bincount")
  self.execute("Bincount", [arr, size, weights], T: typeT, name: name)
end
bitcast(input, typeT: nil, type: nil, name: "Bitcast") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 466
def self.bitcast(input, typeT: nil, type: nil, name: "Bitcast")
  self.execute("Bitcast", [input], T: typeT, type: type, name: name)
end
bitwise_and(x, y, typeT: nil, name: "BitwiseAnd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 470
def self.bitwise_and(x, y, typeT: nil, name: "BitwiseAnd")
  self.execute("BitwiseAnd", [x, y], T: typeT, name: name)
end
bitwise_or(x, y, typeT: nil, name: "BitwiseOr") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 474
def self.bitwise_or(x, y, typeT: nil, name: "BitwiseOr")
  self.execute("BitwiseOr", [x, y], T: typeT, name: name)
end
bitwise_xor(x, y, typeT: nil, name: "BitwiseXor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 478
def self.bitwise_xor(x, y, typeT: nil, name: "BitwiseXor")
  self.execute("BitwiseXor", [x, y], T: typeT, name: name)
end
block_lstm(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, forget_bias: 1.0, cell_clip: 3.0, use_peephole: false, typeT: nil, name: "BlockLSTM") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 482
def self.block_lstm(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, forget_bias: 1.0, cell_clip: 3.0, use_peephole: false, typeT: nil, name: "BlockLSTM")
  self.execute("BlockLSTM", [seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b], forget_bias: forget_bias, cell_clip: cell_clip, use_peephole: use_peephole, T: typeT, name: name)
end
block_lstm_grad(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, h, cs_grad, h_grad, use_peephole: nil, typeT: nil, name: "BlockLSTMGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 486
def self.block_lstm_grad(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, h, cs_grad, h_grad, use_peephole: nil, typeT: nil, name: "BlockLSTMGrad")
  self.execute("BlockLSTMGrad", [seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, h, cs_grad, h_grad], use_peephole: use_peephole, T: typeT, name: name)
end
block_lstm_grad_v2(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, h, cs_grad, h_grad, use_peephole: nil, typeT: nil, name: "BlockLSTMGradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 490
def self.block_lstm_grad_v2(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, h, cs_grad, h_grad, use_peephole: nil, typeT: nil, name: "BlockLSTMGradV2")
  self.execute("BlockLSTMGradV2", [seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, h, cs_grad, h_grad], use_peephole: use_peephole, T: typeT, name: name)
end
block_lstmv2(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, cell_clip: 0.0, use_peephole: false, typeT: nil, name: "BlockLSTMV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 494
def self.block_lstmv2(seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b, cell_clip: 0.0, use_peephole: false, typeT: nil, name: "BlockLSTMV2")
  self.execute("BlockLSTMV2", [seq_len_max, x, cs_prev, h_prev, w, wci, wcf, wco, b], cell_clip: cell_clip, use_peephole: use_peephole, T: typeT, name: name)
end
boosted_trees_aggregate_stats(node_ids, gradients, hessians, feature, max_splits: nil, num_buckets: nil, name: "BoostedTreesAggregateStats") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 498
def self.boosted_trees_aggregate_stats(node_ids, gradients, hessians, feature, max_splits: nil, num_buckets: nil, name: "BoostedTreesAggregateStats")
  self.execute("BoostedTreesAggregateStats", [node_ids, gradients, hessians, feature], max_splits: max_splits, num_buckets: num_buckets, name: name)
end
boosted_trees_bucketize(float_values, bucket_boundaries, num_features: nil, name: "BoostedTreesBucketize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 502
def self.boosted_trees_bucketize(float_values, bucket_boundaries, num_features: nil, name: "BoostedTreesBucketize")
  self.execute("BoostedTreesBucketize", [float_values, bucket_boundaries], num_features: num_features, name: name)
end
boosted_trees_calculate_best_feature_split(node_id_range, stats_summary, l1, l2, tree_complexity, min_node_weight, logits_dimension: nil, split_type: "inequality", name: "BoostedTreesCalculateBestFeatureSplit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 506
def self.boosted_trees_calculate_best_feature_split(node_id_range, stats_summary, l1, l2, tree_complexity, min_node_weight, logits_dimension: nil, split_type: "inequality", name: "BoostedTreesCalculateBestFeatureSplit")
  self.execute("BoostedTreesCalculateBestFeatureSplit", [node_id_range, stats_summary, l1, l2, tree_complexity, min_node_weight], logits_dimension: logits_dimension, split_type: split_type, name: name)
end
boosted_trees_calculate_best_gains_per_feature(node_id_range, stats_summary_list, l1, l2, tree_complexity, min_node_weight, max_splits: nil, num_features: nil, name: "BoostedTreesCalculateBestGainsPerFeature") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 510
def self.boosted_trees_calculate_best_gains_per_feature(node_id_range, stats_summary_list, l1, l2, tree_complexity, min_node_weight, max_splits: nil, num_features: nil, name: "BoostedTreesCalculateBestGainsPerFeature")
  self.execute("BoostedTreesCalculateBestGainsPerFeature", [node_id_range, stats_summary_list, l1, l2, tree_complexity, min_node_weight], max_splits: max_splits, num_features: num_features, name: name)
end
boosted_trees_center_bias(tree_ensemble_handle, mean_gradients, mean_hessians, l1, l2, name: "BoostedTreesCenterBias") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 514
def self.boosted_trees_center_bias(tree_ensemble_handle, mean_gradients, mean_hessians, l1, l2, name: "BoostedTreesCenterBias")
  self.execute("BoostedTreesCenterBias", [tree_ensemble_handle, mean_gradients, mean_hessians, l1, l2], name: name)
end
boosted_trees_create_ensemble(tree_ensemble_handle, stamp_token, tree_ensemble_serialized, name: "BoostedTreesCreateEnsemble") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 518
def self.boosted_trees_create_ensemble(tree_ensemble_handle, stamp_token, tree_ensemble_serialized, name: "BoostedTreesCreateEnsemble")
  self.execute("BoostedTreesCreateEnsemble", [tree_ensemble_handle, stamp_token, tree_ensemble_serialized], name: name)
end
boosted_trees_create_quantile_stream_resource(quantile_stream_resource_handle, epsilon, num_streams, max_elements: 1099511627776, name: "BoostedTreesCreateQuantileStreamResource") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 522
def self.boosted_trees_create_quantile_stream_resource(quantile_stream_resource_handle, epsilon, num_streams, max_elements: 1099511627776, name: "BoostedTreesCreateQuantileStreamResource")
  self.execute("BoostedTreesCreateQuantileStreamResource", [quantile_stream_resource_handle, epsilon, num_streams], max_elements: max_elements, name: name)
end
boosted_trees_deserialize_ensemble(tree_ensemble_handle, stamp_token, tree_ensemble_serialized, name: "BoostedTreesDeserializeEnsemble") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 526
def self.boosted_trees_deserialize_ensemble(tree_ensemble_handle, stamp_token, tree_ensemble_serialized, name: "BoostedTreesDeserializeEnsemble")
  self.execute("BoostedTreesDeserializeEnsemble", [tree_ensemble_handle, stamp_token, tree_ensemble_serialized], name: name)
end
boosted_trees_ensemble_resource_handle_op(container: "", shared_name: "", name: "BoostedTreesEnsembleResourceHandleOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 530
def self.boosted_trees_ensemble_resource_handle_op(container: "", shared_name: "", name: "BoostedTreesEnsembleResourceHandleOp")
  self.execute("BoostedTreesEnsembleResourceHandleOp", [], container: container, shared_name: shared_name, name: name)
end
boosted_trees_example_debug_outputs(tree_ensemble_handle, bucketized_features, num_bucketized_features: nil, logits_dimension: nil, name: "BoostedTreesExampleDebugOutputs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 534
def self.boosted_trees_example_debug_outputs(tree_ensemble_handle, bucketized_features, num_bucketized_features: nil, logits_dimension: nil, name: "BoostedTreesExampleDebugOutputs")
  self.execute("BoostedTreesExampleDebugOutputs", [tree_ensemble_handle, bucketized_features], num_bucketized_features: num_bucketized_features, logits_dimension: logits_dimension, name: name)
end
boosted_trees_flush_quantile_summaries(quantile_stream_resource_handle, num_features: nil, name: "BoostedTreesFlushQuantileSummaries") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 538
def self.boosted_trees_flush_quantile_summaries(quantile_stream_resource_handle, num_features: nil, name: "BoostedTreesFlushQuantileSummaries")
  self.execute("BoostedTreesFlushQuantileSummaries", [quantile_stream_resource_handle], num_features: num_features, name: name)
end
boosted_trees_get_ensemble_states(tree_ensemble_handle, name: "BoostedTreesGetEnsembleStates") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 542
def self.boosted_trees_get_ensemble_states(tree_ensemble_handle, name: "BoostedTreesGetEnsembleStates")
  self.execute("BoostedTreesGetEnsembleStates", [tree_ensemble_handle], name: name)
end
boosted_trees_make_quantile_summaries(float_values, example_weights, epsilon, num_features: nil, name: "BoostedTreesMakeQuantileSummaries") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 546
def self.boosted_trees_make_quantile_summaries(float_values, example_weights, epsilon, num_features: nil, name: "BoostedTreesMakeQuantileSummaries")
  self.execute("BoostedTreesMakeQuantileSummaries", [float_values, example_weights, epsilon], num_features: num_features, name: name)
end
boosted_trees_make_stats_summary(node_ids, gradients, hessians, bucketized_features_list, max_splits: nil, num_buckets: nil, num_features: nil, name: "BoostedTreesMakeStatsSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 550
def self.boosted_trees_make_stats_summary(node_ids, gradients, hessians, bucketized_features_list, max_splits: nil, num_buckets: nil, num_features: nil, name: "BoostedTreesMakeStatsSummary")
  self.execute("BoostedTreesMakeStatsSummary", [node_ids, gradients, hessians, bucketized_features_list], max_splits: max_splits, num_buckets: num_buckets, num_features: num_features, name: name)
end
boosted_trees_predict(tree_ensemble_handle, bucketized_features, num_bucketized_features: nil, logits_dimension: nil, name: "BoostedTreesPredict") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 554
def self.boosted_trees_predict(tree_ensemble_handle, bucketized_features, num_bucketized_features: nil, logits_dimension: nil, name: "BoostedTreesPredict")
  self.execute("BoostedTreesPredict", [tree_ensemble_handle, bucketized_features], num_bucketized_features: num_bucketized_features, logits_dimension: logits_dimension, name: name)
end
boosted_trees_quantile_stream_resource_add_summaries(quantile_stream_resource_handle, summaries, num_features: nil, name: "BoostedTreesQuantileStreamResourceAddSummaries") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 558
def self.boosted_trees_quantile_stream_resource_add_summaries(quantile_stream_resource_handle, summaries, num_features: nil, name: "BoostedTreesQuantileStreamResourceAddSummaries")
  self.execute("BoostedTreesQuantileStreamResourceAddSummaries", [quantile_stream_resource_handle, summaries], num_features: num_features, name: name)
end
boosted_trees_quantile_stream_resource_deserialize(quantile_stream_resource_handle, bucket_boundaries, num_streams: nil, name: "BoostedTreesQuantileStreamResourceDeserialize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 562
def self.boosted_trees_quantile_stream_resource_deserialize(quantile_stream_resource_handle, bucket_boundaries, num_streams: nil, name: "BoostedTreesQuantileStreamResourceDeserialize")
  self.execute("BoostedTreesQuantileStreamResourceDeserialize", [quantile_stream_resource_handle, bucket_boundaries], num_streams: num_streams, name: name)
end
boosted_trees_quantile_stream_resource_flush(quantile_stream_resource_handle, num_buckets, generate_quantiles: false, name: "BoostedTreesQuantileStreamResourceFlush") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 566
def self.boosted_trees_quantile_stream_resource_flush(quantile_stream_resource_handle, num_buckets, generate_quantiles: false, name: "BoostedTreesQuantileStreamResourceFlush")
  self.execute("BoostedTreesQuantileStreamResourceFlush", [quantile_stream_resource_handle, num_buckets], generate_quantiles: generate_quantiles, name: name)
end
boosted_trees_quantile_stream_resource_get_bucket_boundaries(quantile_stream_resource_handle, num_features: nil, name: "BoostedTreesQuantileStreamResourceGetBucketBoundaries") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 570
def self.boosted_trees_quantile_stream_resource_get_bucket_boundaries(quantile_stream_resource_handle, num_features: nil, name: "BoostedTreesQuantileStreamResourceGetBucketBoundaries")
  self.execute("BoostedTreesQuantileStreamResourceGetBucketBoundaries", [quantile_stream_resource_handle], num_features: num_features, name: name)
end
boosted_trees_quantile_stream_resource_handle_op(container: "", shared_name: "", name: "BoostedTreesQuantileStreamResourceHandleOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 574
def self.boosted_trees_quantile_stream_resource_handle_op(container: "", shared_name: "", name: "BoostedTreesQuantileStreamResourceHandleOp")
  self.execute("BoostedTreesQuantileStreamResourceHandleOp", [], container: container, shared_name: shared_name, name: name)
end
boosted_trees_serialize_ensemble(tree_ensemble_handle, name: "BoostedTreesSerializeEnsemble") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 578
def self.boosted_trees_serialize_ensemble(tree_ensemble_handle, name: "BoostedTreesSerializeEnsemble")
  self.execute("BoostedTreesSerializeEnsemble", [tree_ensemble_handle], name: name)
end
boosted_trees_sparse_aggregate_stats(node_ids, gradients, hessians, feature_indices, feature_values, feature_shape, max_splits: nil, num_buckets: nil, name: "BoostedTreesSparseAggregateStats") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 582
def self.boosted_trees_sparse_aggregate_stats(node_ids, gradients, hessians, feature_indices, feature_values, feature_shape, max_splits: nil, num_buckets: nil, name: "BoostedTreesSparseAggregateStats")
  self.execute("BoostedTreesSparseAggregateStats", [node_ids, gradients, hessians, feature_indices, feature_values, feature_shape], max_splits: max_splits, num_buckets: num_buckets, name: name)
end
boosted_trees_sparse_calculate_best_feature_split(node_id_range, stats_summary_indices, stats_summary_values, stats_summary_shape, l1, l2, tree_complexity, min_node_weight, logits_dimension: nil, split_type: "inequality", name: "BoostedTreesSparseCalculateBestFeatureSplit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 586
def self.boosted_trees_sparse_calculate_best_feature_split(node_id_range, stats_summary_indices, stats_summary_values, stats_summary_shape, l1, l2, tree_complexity, min_node_weight, logits_dimension: nil, split_type: "inequality", name: "BoostedTreesSparseCalculateBestFeatureSplit")
  self.execute("BoostedTreesSparseCalculateBestFeatureSplit", [node_id_range, stats_summary_indices, stats_summary_values, stats_summary_shape, l1, l2, tree_complexity, min_node_weight], logits_dimension: logits_dimension, split_type: split_type, name: name)
end
boosted_trees_training_predict(tree_ensemble_handle, cached_tree_ids, cached_node_ids, bucketized_features, num_bucketized_features: nil, logits_dimension: nil, name: "BoostedTreesTrainingPredict") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 590
def self.boosted_trees_training_predict(tree_ensemble_handle, cached_tree_ids, cached_node_ids, bucketized_features, num_bucketized_features: nil, logits_dimension: nil, name: "BoostedTreesTrainingPredict")
  self.execute("BoostedTreesTrainingPredict", [tree_ensemble_handle, cached_tree_ids, cached_node_ids, bucketized_features], num_bucketized_features: num_bucketized_features, logits_dimension: logits_dimension, name: name)
end
boosted_trees_update_ensemble(tree_ensemble_handle, feature_ids, node_ids, gains, thresholds, left_node_contribs, right_node_contribs, max_depth, learning_rate, pruning_mode: nil, num_features: nil, name: "BoostedTreesUpdateEnsemble") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 594
def self.boosted_trees_update_ensemble(tree_ensemble_handle, feature_ids, node_ids, gains, thresholds, left_node_contribs, right_node_contribs, max_depth, learning_rate, pruning_mode: nil, num_features: nil, name: "BoostedTreesUpdateEnsemble")
  self.execute("BoostedTreesUpdateEnsemble", [tree_ensemble_handle, feature_ids, node_ids, gains, thresholds, left_node_contribs, right_node_contribs, max_depth, learning_rate], pruning_mode: pruning_mode, num_features: num_features, name: name)
end
boosted_trees_update_ensemble_v2(tree_ensemble_handle, feature_ids, dimension_ids, node_ids, gains, thresholds, left_node_contribs, right_node_contribs, split_types, max_depth, learning_rate, pruning_mode, num_features: nil, logits_dimension: 1, name: "BoostedTreesUpdateEnsembleV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 598
def self.boosted_trees_update_ensemble_v2(tree_ensemble_handle, feature_ids, dimension_ids, node_ids, gains, thresholds, left_node_contribs, right_node_contribs, split_types, max_depth, learning_rate, pruning_mode, num_features: nil, logits_dimension: 1, name: "BoostedTreesUpdateEnsembleV2")
  self.execute("BoostedTreesUpdateEnsembleV2", [tree_ensemble_handle, feature_ids, dimension_ids, node_ids, gains, thresholds, left_node_contribs, right_node_contribs, split_types, max_depth, learning_rate, pruning_mode], num_features: num_features, logits_dimension: logits_dimension, name: name)
end
broadcast_args(s0, s1, typeT: :int32, name: "BroadcastArgs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 602
def self.broadcast_args(s0, s1, typeT: :int32, name: "BroadcastArgs")
  self.execute("BroadcastArgs", [s0, s1], T: typeT, name: name)
end
broadcast_gradient_args(s0, s1, typeT: :int32, name: "BroadcastGradientArgs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 606
def self.broadcast_gradient_args(s0, s1, typeT: :int32, name: "BroadcastGradientArgs")
  self.execute("BroadcastGradientArgs", [s0, s1], T: typeT, name: name)
end
broadcast_to(input, shape, typeT: nil, tidx: :int32, name: "BroadcastTo") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 610
def self.broadcast_to(input, shape, typeT: nil, tidx: :int32, name: "BroadcastTo")
  self.execute("BroadcastTo", [input, shape], T: typeT, Tidx: tidx, name: name)
end
bucketize(input, typeT: nil, boundaries: nil, name: "Bucketize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 614
def self.bucketize(input, typeT: nil, boundaries: nil, name: "Bucketize")
  self.execute("Bucketize", [input], T: typeT, boundaries: boundaries, name: name)
end
bytes_produced_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "BytesProducedStatsDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 618
def self.bytes_produced_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "BytesProducedStatsDataset")
  self.execute("BytesProducedStatsDataset", [input_dataset, tag], output_types: output_types, output_shapes: output_shapes, name: name)
end
cache_dataset(input_dataset, filename, output_types: nil, output_shapes: nil, name: "CacheDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 650
def self.cache_dataset(input_dataset, filename, output_types: nil, output_shapes: nil, name: "CacheDataset")
  self.execute("CacheDataset", [input_dataset, filename], output_types: output_types, output_shapes: output_shapes, name: name)
end
cache_dataset_v2(input_dataset, filename, cache, output_types: nil, output_shapes: nil, name: "CacheDatasetV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 654
def self.cache_dataset_v2(input_dataset, filename, cache, output_types: nil, output_shapes: nil, name: "CacheDatasetV2")
  self.execute("CacheDatasetV2", [input_dataset, filename, cache], output_types: output_types, output_shapes: output_shapes, name: name)
end
case(branch_index, input, tin: nil, tout: nil, branches: nil, output_shapes: [], name: "Case") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 658
def self.case(branch_index, input, tin: nil, tout: nil, branches: nil, output_shapes: [], name: "Case")
  self.execute("Case", [branch_index, input], Tin: tin, Tout: tout, branches: branches, output_shapes: output_shapes, name: name)
end
cast(x, srct: nil, dstt: nil, truncate: false, name: "Cast") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 662
def self.cast(x, srct: nil, dstt: nil, truncate: false, name: "Cast")
  self.execute("Cast", [x], SrcT: srct, DstT: dstt, Truncate: truncate, name: name)
end
ceil(x, typeT: nil, name: "Ceil") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 666
def self.ceil(x, typeT: nil, name: "Ceil")
  self.execute("Ceil", [x], T: typeT, name: name)
end
check_numerics(tensor, typeT: nil, message: "", name: "CheckNumerics") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 670
def self.check_numerics(tensor, typeT: nil, message: "", name: "CheckNumerics")
  self.execute("CheckNumerics", [tensor], T: typeT, message: message, name: name)
end
cholesky(input, typeT: nil, name: "Cholesky") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 674
def self.cholesky(input, typeT: nil, name: "Cholesky")
  self.execute("Cholesky", [input], T: typeT, name: name)
end
cholesky_grad(l, grad, typeT: nil, name: "CholeskyGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 678
def self.cholesky_grad(l, grad, typeT: nil, name: "CholeskyGrad")
  self.execute("CholeskyGrad", [l, grad], T: typeT, name: name)
end
choose_fastest_branch_dataset(input_dataset, ratio_numerator, ratio_denominator, other_arguments, targuments: nil, num_elements_per_branch: nil, branches: nil, other_arguments_lengths: nil, output_types: nil, output_shapes: nil, name: "ChooseFastestBranchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 682
def self.choose_fastest_branch_dataset(input_dataset, ratio_numerator, ratio_denominator, other_arguments, targuments: nil, num_elements_per_branch: nil, branches: nil, other_arguments_lengths: nil, output_types: nil, output_shapes: nil, name: "ChooseFastestBranchDataset")
  self.execute("ChooseFastestBranchDataset", [input_dataset, ratio_numerator, ratio_denominator, other_arguments], Targuments: targuments, num_elements_per_branch: num_elements_per_branch, branches: branches, other_arguments_lengths: other_arguments_lengths, output_types: output_types, output_shapes: output_shapes, name: name)
end
choose_fastest_dataset(input_datasets, n: nil, num_experiments: nil, output_types: nil, output_shapes: nil, name: "ChooseFastestDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 686
def self.choose_fastest_dataset(input_datasets, n: nil, num_experiments: nil, output_types: nil, output_shapes: nil, name: "ChooseFastestDataset")
  self.execute("ChooseFastestDataset", [input_datasets], N: n, num_experiments: num_experiments, output_types: output_types, output_shapes: output_shapes, name: name)
end
clip_by_value(t, clip_value_min, clip_value_max, typeT: nil, name: "ClipByValue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 690
def self.clip_by_value(t, clip_value_min, clip_value_max, typeT: nil, name: "ClipByValue")
  self.execute("ClipByValue", [t, clip_value_min, clip_value_max], T: typeT, name: name)
end
close_summary_writer(writer, name: "CloseSummaryWriter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 694
def self.close_summary_writer(writer, name: "CloseSummaryWriter")
  self.execute("CloseSummaryWriter", [writer], name: name)
end
collective_bcast_recv(typeT: nil, group_size: nil, group_key: nil, instance_key: nil, shape: nil, communication_hint: "auto", name: "CollectiveBcastRecv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 698
def self.collective_bcast_recv(typeT: nil, group_size: nil, group_key: nil, instance_key: nil, shape: nil, communication_hint: "auto", name: "CollectiveBcastRecv")
  self.execute("CollectiveBcastRecv", [], T: typeT, group_size: group_size, group_key: group_key, instance_key: instance_key, shape: shape, communication_hint: communication_hint, name: name)
end
collective_bcast_send(input, typeT: nil, group_size: nil, group_key: nil, instance_key: nil, shape: nil, communication_hint: "auto", name: "CollectiveBcastSend") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 702
def self.collective_bcast_send(input, typeT: nil, group_size: nil, group_key: nil, instance_key: nil, shape: nil, communication_hint: "auto", name: "CollectiveBcastSend")
  self.execute("CollectiveBcastSend", [input], T: typeT, group_size: group_size, group_key: group_key, instance_key: instance_key, shape: shape, communication_hint: communication_hint, name: name)
end
collective_gather(input, typeT: nil, group_size: nil, group_key: nil, instance_key: nil, shape: nil, communication_hint: "auto", name: "CollectiveGather") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 706
def self.collective_gather(input, typeT: nil, group_size: nil, group_key: nil, instance_key: nil, shape: nil, communication_hint: "auto", name: "CollectiveGather")
  self.execute("CollectiveGather", [input], T: typeT, group_size: group_size, group_key: group_key, instance_key: instance_key, shape: shape, communication_hint: communication_hint, name: name)
end
collective_permute(input, source_target_pairs, typeT: nil, name: "CollectivePermute") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 710
def self.collective_permute(input, source_target_pairs, typeT: nil, name: "CollectivePermute")
  self.execute("CollectivePermute", [input, source_target_pairs], T: typeT, name: name)
end
collective_reduce(input, typeT: nil, group_size: nil, group_key: nil, instance_key: nil, merge_op: nil, final_op: nil, subdiv_offsets: nil, wait_for: [], communication_hint: "auto", name: "CollectiveReduce") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 714
def self.collective_reduce(input, typeT: nil, group_size: nil, group_key: nil, instance_key: nil, merge_op: nil, final_op: nil, subdiv_offsets: nil, wait_for: [], communication_hint: "auto", name: "CollectiveReduce")
  self.execute("CollectiveReduce", [input], T: typeT, group_size: group_size, group_key: group_key, instance_key: instance_key, merge_op: merge_op, final_op: final_op, subdiv_offsets: subdiv_offsets, wait_for: wait_for, communication_hint: communication_hint, name: name)
end
combined_non_max_suppression(boxes, scores, max_output_size_per_class, max_total_size, iou_threshold, score_threshold, pad_per_class: false, clip_boxes: true, name: "CombinedNonMaxSuppression") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 718
def self.combined_non_max_suppression(boxes, scores, max_output_size_per_class, max_total_size, iou_threshold, score_threshold, pad_per_class: false, clip_boxes: true, name: "CombinedNonMaxSuppression")
  self.execute("CombinedNonMaxSuppression", [boxes, scores, max_output_size_per_class, max_total_size, iou_threshold, score_threshold], pad_per_class: pad_per_class, clip_boxes: clip_boxes, name: name)
end
compare_and_bitpack(input, threshold, typeT: nil, name: "CompareAndBitpack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 722
def self.compare_and_bitpack(input, threshold, typeT: nil, name: "CompareAndBitpack")
  self.execute("CompareAndBitpack", [input, threshold], T: typeT, name: name)
end
complex(real, imag, typeT: :float, tout: :complex64, name: "Complex") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 726
def self.complex(real, imag, typeT: :float, tout: :complex64, name: "Complex")
  self.execute("Complex", [real, imag], T: typeT, Tout: tout, name: name)
end
complex_abs(x, typeT: :complex64, tout: :float, name: "ComplexAbs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 730
def self.complex_abs(x, typeT: :complex64, tout: :float, name: "ComplexAbs")
  self.execute("ComplexAbs", [x], T: typeT, Tout: tout, name: name)
end
compute_accidental_hits(true_classes, sampled_candidates, num_true: nil, seed: 0, seed2: 0, name: "ComputeAccidentalHits") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 734
def self.compute_accidental_hits(true_classes, sampled_candidates, num_true: nil, seed: 0, seed2: 0, name: "ComputeAccidentalHits")
  self.execute("ComputeAccidentalHits", [true_classes, sampled_candidates], num_true: num_true, seed: seed, seed2: seed2, name: name)
end
concat(concat_dim, values, n: nil, typeT: nil, name: "Concat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 738
def self.concat(concat_dim, values, n: nil, typeT: nil, name: "Concat")
  self.execute("Concat", [concat_dim, values], N: n, T: typeT, name: name)
end
concat_offset(concat_dim, shape, n: nil, name: "ConcatOffset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 742
def self.concat_offset(concat_dim, shape, n: nil, name: "ConcatOffset")
  self.execute("ConcatOffset", [concat_dim, shape], N: n, name: name)
end
concat_v2(values, axis, n: nil, typeT: nil, tidx: :int32, name: "ConcatV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 746
def self.concat_v2(values, axis, n: nil, typeT: nil, tidx: :int32, name: "ConcatV2")
  self.execute("ConcatV2", [values, axis], N: n, T: typeT, Tidx: tidx, name: name)
end
concatenate_dataset(input_dataset, another_dataset, output_types: nil, output_shapes: nil, name: "ConcatenateDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 750
def self.concatenate_dataset(input_dataset, another_dataset, output_types: nil, output_shapes: nil, name: "ConcatenateDataset")
  self.execute("ConcatenateDataset", [input_dataset, another_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
conditional_accumulator(dtype: nil, shape: nil, container: "", shared_name: "", reduction_type: "MEAN", name: "ConditionalAccumulator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 754
def self.conditional_accumulator(dtype: nil, shape: nil, container: "", shared_name: "", reduction_type: "MEAN", name: "ConditionalAccumulator")
  self.execute("ConditionalAccumulator", [], dtype: dtype, shape: shape, container: container, shared_name: shared_name, reduction_type: reduction_type, name: name)
end
configure_distributed_tpu(embedding_config: "", tpu_embedding_config: "", is_global_init: false, enable_whole_mesh_compilations: false, name: "ConfigureDistributedTPU") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 758
def self.configure_distributed_tpu(embedding_config: "", tpu_embedding_config: "", is_global_init: false, enable_whole_mesh_compilations: false, name: "ConfigureDistributedTPU")
  self.execute("ConfigureDistributedTPU", [], embedding_config: embedding_config, tpu_embedding_config: tpu_embedding_config, is_global_init: is_global_init, enable_whole_mesh_compilations: enable_whole_mesh_compilations, name: name)
end
configure_tpu_embedding(config: "", name: "ConfigureTPUEmbedding") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 762
def self.configure_tpu_embedding(config: "", name: "ConfigureTPUEmbedding")
  self.execute("ConfigureTPUEmbedding", [], config: config, name: name)
end
conj(input, typeT: :complex64, name: "Conj") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 766
def self.conj(input, typeT: :complex64, name: "Conj")
  self.execute("Conj", [input], T: typeT, name: name)
end
conjugate_transpose(x, perm, typeT: nil, tperm: :int32, name: "ConjugateTranspose") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 770
def self.conjugate_transpose(x, perm, typeT: nil, tperm: :int32, name: "ConjugateTranspose")
  self.execute("ConjugateTranspose", [x, perm], T: typeT, Tperm: tperm, name: name)
end
const(value: nil, dtype: nil, name: "Const") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 774
def self.const(value: nil, dtype: nil, name: "Const")
  self.execute("Const", [], value: value, dtype: dtype, name: name)
end
consume_mutex_lock(mutex_lock, name: "ConsumeMutexLock") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 778
def self.consume_mutex_lock(mutex_lock, name: "ConsumeMutexLock")
  self.execute("ConsumeMutexLock", [mutex_lock], name: name)
end
control_trigger(name: "ControlTrigger") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 782
def self.control_trigger(name: "ControlTrigger")
  self.execute("ControlTrigger", [], name: name)
end
conv2_d(input, filter, typeT: nil, strides: nil, use_cudnn_on_gpu: true, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], name: "Conv2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 786
def self.conv2_d(input, filter, typeT: nil, strides: nil, use_cudnn_on_gpu: true, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], name: "Conv2D")
  self.execute("Conv2D", [input, filter], T: typeT, strides: strides, use_cudnn_on_gpu: use_cudnn_on_gpu, padding: padding, explicit_paddings: explicit_paddings, data_format: data_format, dilations: dilations, name: name)
end
conv2_d_backprop_filter(input, filter_sizes, out_backprop, typeT: nil, strides: nil, use_cudnn_on_gpu: true, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], name: "Conv2DBackpropFilter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 790
def self.conv2_d_backprop_filter(input, filter_sizes, out_backprop, typeT: nil, strides: nil, use_cudnn_on_gpu: true, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], name: "Conv2DBackpropFilter")
  self.execute("Conv2DBackpropFilter", [input, filter_sizes, out_backprop], T: typeT, strides: strides, use_cudnn_on_gpu: use_cudnn_on_gpu, padding: padding, explicit_paddings: explicit_paddings, data_format: data_format, dilations: dilations, name: name)
end
conv2_d_backprop_input(input_sizes, filter, out_backprop, typeT: nil, strides: nil, use_cudnn_on_gpu: true, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], name: "Conv2DBackpropInput") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 794
def self.conv2_d_backprop_input(input_sizes, filter, out_backprop, typeT: nil, strides: nil, use_cudnn_on_gpu: true, padding: nil, explicit_paddings: [], data_format: "NHWC", dilations: [], name: "Conv2DBackpropInput")
  self.execute("Conv2DBackpropInput", [input_sizes, filter, out_backprop], T: typeT, strides: strides, use_cudnn_on_gpu: use_cudnn_on_gpu, padding: padding, explicit_paddings: explicit_paddings, data_format: data_format, dilations: dilations, name: name)
end
conv3_d(input, filter, typeT: nil, strides: nil, padding: nil, data_format: "NDHWC", dilations: [], name: "Conv3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 798
def self.conv3_d(input, filter, typeT: nil, strides: nil, padding: nil, data_format: "NDHWC", dilations: [], name: "Conv3D")
  self.execute("Conv3D", [input, filter], T: typeT, strides: strides, padding: padding, data_format: data_format, dilations: dilations, name: name)
end
conv3_d_backprop_filter(input, filter, out_backprop, typeT: nil, strides: nil, padding: nil, dilations: [], name: "Conv3DBackpropFilter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 802
def self.conv3_d_backprop_filter(input, filter, out_backprop, typeT: nil, strides: nil, padding: nil, dilations: [], name: "Conv3DBackpropFilter")
  self.execute("Conv3DBackpropFilter", [input, filter, out_backprop], T: typeT, strides: strides, padding: padding, dilations: dilations, name: name)
end
conv3_d_backprop_filter_v2(input, filter_sizes, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NDHWC", dilations: [], name: "Conv3DBackpropFilterV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 806
def self.conv3_d_backprop_filter_v2(input, filter_sizes, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NDHWC", dilations: [], name: "Conv3DBackpropFilterV2")
  self.execute("Conv3DBackpropFilterV2", [input, filter_sizes, out_backprop], T: typeT, strides: strides, padding: padding, data_format: data_format, dilations: dilations, name: name)
end
conv3_d_backprop_input(input, filter, out_backprop, typeT: nil, strides: nil, padding: nil, dilations: [], name: "Conv3DBackpropInput") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 810
def self.conv3_d_backprop_input(input, filter, out_backprop, typeT: nil, strides: nil, padding: nil, dilations: [], name: "Conv3DBackpropInput")
  self.execute("Conv3DBackpropInput", [input, filter, out_backprop], T: typeT, strides: strides, padding: padding, dilations: dilations, name: name)
end
conv3_d_backprop_input_v2(input_sizes, filter, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NDHWC", dilations: [], tshape: :int32, name: "Conv3DBackpropInputV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 814
def self.conv3_d_backprop_input_v2(input_sizes, filter, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NDHWC", dilations: [], tshape: :int32, name: "Conv3DBackpropInputV2")
  self.execute("Conv3DBackpropInputV2", [input_sizes, filter, out_backprop], T: typeT, strides: strides, padding: padding, data_format: data_format, dilations: dilations, Tshape: tshape, name: name)
end
copy(input, typeT: nil, tensor_name: "", debug_ops_spec: [], name: "Copy") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 818
def self.copy(input, typeT: nil, tensor_name: "", debug_ops_spec: [], name: "Copy")
  self.execute("Copy", [input], T: typeT, tensor_name: tensor_name, debug_ops_spec: debug_ops_spec, name: name)
end
copy_host(input, typeT: nil, tensor_name: "", debug_ops_spec: [], name: "CopyHost") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 822
def self.copy_host(input, typeT: nil, tensor_name: "", debug_ops_spec: [], name: "CopyHost")
  self.execute("CopyHost", [input], T: typeT, tensor_name: tensor_name, debug_ops_spec: debug_ops_spec, name: name)
end
cos(x, typeT: nil, name: "Cos") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 826
def self.cos(x, typeT: nil, name: "Cos")
  self.execute("Cos", [x], T: typeT, name: name)
end
cosh(x, typeT: nil, name: "Cosh") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 830
def self.cosh(x, typeT: nil, name: "Cosh")
  self.execute("Cosh", [x], T: typeT, name: name)
end
count_up_to(ref, limit: nil, typeT: nil, name: "CountUpTo") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 834
def self.count_up_to(ref, limit: nil, typeT: nil, name: "CountUpTo")
  self.execute("CountUpTo", [ref], limit: limit, T: typeT, name: name)
end
create_summary_db_writer(writer, db_uri, experiment_name, run_name, user_name, name: "CreateSummaryDbWriter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 838
def self.create_summary_db_writer(writer, db_uri, experiment_name, run_name, user_name, name: "CreateSummaryDbWriter")
  self.execute("CreateSummaryDbWriter", [writer, db_uri, experiment_name, run_name, user_name], name: name)
end
create_summary_file_writer(writer, logdir, max_queue, flush_millis, filename_suffix, name: "CreateSummaryFileWriter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 842
def self.create_summary_file_writer(writer, logdir, max_queue, flush_millis, filename_suffix, name: "CreateSummaryFileWriter")
  self.execute("CreateSummaryFileWriter", [writer, logdir, max_queue, flush_millis, filename_suffix], name: name)
end
crop_and_resize(image, boxes, box_ind, crop_size, typeT: nil, method: "bilinear", extrapolation_value: 0.0, name: "CropAndResize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 846
def self.crop_and_resize(image, boxes, box_ind, crop_size, typeT: nil, method: "bilinear", extrapolation_value: 0.0, name: "CropAndResize")
  self.execute("CropAndResize", [image, boxes, box_ind, crop_size], T: typeT, method: method, extrapolation_value: extrapolation_value, name: name)
end
crop_and_resize_grad_boxes(grads, image, boxes, box_ind, typeT: nil, method: "bilinear", name: "CropAndResizeGradBoxes") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 850
def self.crop_and_resize_grad_boxes(grads, image, boxes, box_ind, typeT: nil, method: "bilinear", name: "CropAndResizeGradBoxes")
  self.execute("CropAndResizeGradBoxes", [grads, image, boxes, box_ind], T: typeT, method: method, name: name)
end
crop_and_resize_grad_image(grads, boxes, box_ind, image_size, typeT: nil, method: "bilinear", name: "CropAndResizeGradImage") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 854
def self.crop_and_resize_grad_image(grads, boxes, box_ind, image_size, typeT: nil, method: "bilinear", name: "CropAndResizeGradImage")
  self.execute("CropAndResizeGradImage", [grads, boxes, box_ind, image_size], T: typeT, method: method, name: name)
end
cross(a, b, typeT: nil, name: "Cross") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 858
def self.cross(a, b, typeT: nil, name: "Cross")
  self.execute("Cross", [a, b], T: typeT, name: name)
end
cross_replica_sum(input, group_assignment, typeT: nil, name: "CrossReplicaSum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 862
def self.cross_replica_sum(input, group_assignment, typeT: nil, name: "CrossReplicaSum")
  self.execute("CrossReplicaSum", [input, group_assignment], T: typeT, name: name)
end
csr_sparse_matrix_components(csr_sparse_matrix, index, type: nil, name: "CSRSparseMatrixComponents") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 622
def self.csr_sparse_matrix_components(csr_sparse_matrix, index, type: nil, name: "CSRSparseMatrixComponents")
  self.execute("CSRSparseMatrixComponents", [csr_sparse_matrix, index], type: type, name: name)
end
csr_sparse_matrix_to_dense(sparse_input, type: nil, name: "CSRSparseMatrixToDense") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 626
def self.csr_sparse_matrix_to_dense(sparse_input, type: nil, name: "CSRSparseMatrixToDense")
  self.execute("CSRSparseMatrixToDense", [sparse_input], type: type, name: name)
end
csr_sparse_matrix_to_sparse_tensor(sparse_matrix, type: nil, name: "CSRSparseMatrixToSparseTensor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 630
def self.csr_sparse_matrix_to_sparse_tensor(sparse_matrix, type: nil, name: "CSRSparseMatrixToSparseTensor")
  self.execute("CSRSparseMatrixToSparseTensor", [sparse_matrix], type: type, name: name)
end
csv_dataset(filenames, compression_type, buffer_size, header, field_delim, use_quote_delim, na_value, select_cols, record_defaults, output_types: nil, output_shapes: nil, name: "CSVDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 634
def self.csv_dataset(filenames, compression_type, buffer_size, header, field_delim, use_quote_delim, na_value, select_cols, record_defaults, output_types: nil, output_shapes: nil, name: "CSVDataset")
  self.execute("CSVDataset", [filenames, compression_type, buffer_size, header, field_delim, use_quote_delim, na_value, select_cols, record_defaults], output_types: output_types, output_shapes: output_shapes, name: name)
end
ctc_beam_search_decoder(inputs, sequence_length, beam_width: nil, top_paths: nil, merge_repeated: true, typeT: :float, name: "CTCBeamSearchDecoder") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 638
def self.ctc_beam_search_decoder(inputs, sequence_length, beam_width: nil, top_paths: nil, merge_repeated: true, typeT: :float, name: "CTCBeamSearchDecoder")
  self.execute("CTCBeamSearchDecoder", [inputs, sequence_length], beam_width: beam_width, top_paths: top_paths, merge_repeated: merge_repeated, T: typeT, name: name)
end
ctc_greedy_decoder(inputs, sequence_length, merge_repeated: false, typeT: :float, name: "CTCGreedyDecoder") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 642
def self.ctc_greedy_decoder(inputs, sequence_length, merge_repeated: false, typeT: :float, name: "CTCGreedyDecoder")
  self.execute("CTCGreedyDecoder", [inputs, sequence_length], merge_repeated: merge_repeated, T: typeT, name: name)
end
ctc_loss(inputs, labels_indices, labels_values, sequence_length, preprocess_collapse_repeated: false, ctc_merge_repeated: true, ignore_longer_outputs_than_inputs: false, typeT: :float, name: "CTCLoss") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 646
def self.ctc_loss(inputs, labels_indices, labels_values, sequence_length, preprocess_collapse_repeated: false, ctc_merge_repeated: true, ignore_longer_outputs_than_inputs: false, typeT: :float, name: "CTCLoss")
  self.execute("CTCLoss", [inputs, labels_indices, labels_values, sequence_length], preprocess_collapse_repeated: preprocess_collapse_repeated, ctc_merge_repeated: ctc_merge_repeated, ignore_longer_outputs_than_inputs: ignore_longer_outputs_than_inputs, T: typeT, name: name)
end
cudnn_rnn(input, input_h, input_c, params, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, is_training: true, name: "CudnnRNN") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 866
def self.cudnn_rnn(input, input_h, input_c, params, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, is_training: true, name: "CudnnRNN")
  self.execute("CudnnRNN", [input, input_h, input_c, params], T: typeT, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, is_training: is_training, name: name)
end
cudnn_rnn_backprop(input, input_h, input_c, params, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNBackprop") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 870
def self.cudnn_rnn_backprop(input, input_h, input_c, params, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNBackprop")
  self.execute("CudnnRNNBackprop", [input, input_h, input_c, params, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space], T: typeT, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, name: name)
end
cudnn_rnn_backprop_v2(input, input_h, input_c, params, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, host_reserved, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNBackpropV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 874
def self.cudnn_rnn_backprop_v2(input, input_h, input_c, params, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, host_reserved, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNBackpropV2")
  self.execute("CudnnRNNBackpropV2", [input, input_h, input_c, params, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, host_reserved], T: typeT, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, name: name)
end
cudnn_rnn_backprop_v3(input, input_h, input_c, params, sequence_lengths, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, host_reserved, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, time_major: true, name: "CudnnRNNBackpropV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 878
def self.cudnn_rnn_backprop_v3(input, input_h, input_c, params, sequence_lengths, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, host_reserved, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, time_major: true, name: "CudnnRNNBackpropV3")
  self.execute("CudnnRNNBackpropV3", [input, input_h, input_c, params, sequence_lengths, output, output_h, output_c, output_backprop, output_h_backprop, output_c_backprop, reserve_space, host_reserved], T: typeT, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, num_proj: num_proj, time_major: time_major, name: name)
end
cudnn_rnn_canonical_to_params(num_layers, num_units, input_size, weights, biases, typeT: nil, num_params: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNCanonicalToParams") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 882
def self.cudnn_rnn_canonical_to_params(num_layers, num_units, input_size, weights, biases, typeT: nil, num_params: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNCanonicalToParams")
  self.execute("CudnnRNNCanonicalToParams", [num_layers, num_units, input_size, weights, biases], T: typeT, num_params: num_params, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, name: name)
end
cudnn_rnn_canonical_to_params_v2(num_layers, num_units, input_size, weights, biases, typeT: nil, num_params_weights: nil, num_params_biases: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, name: "CudnnRNNCanonicalToParamsV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 886
def self.cudnn_rnn_canonical_to_params_v2(num_layers, num_units, input_size, weights, biases, typeT: nil, num_params_weights: nil, num_params_biases: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, name: "CudnnRNNCanonicalToParamsV2")
  self.execute("CudnnRNNCanonicalToParamsV2", [num_layers, num_units, input_size, weights, biases], T: typeT, num_params_weights: num_params_weights, num_params_biases: num_params_biases, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, num_proj: num_proj, name: name)
end
cudnn_rnn_params_size(num_layers, num_units, input_size, typeT: nil, s: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, name: "CudnnRNNParamsSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 890
def self.cudnn_rnn_params_size(num_layers, num_units, input_size, typeT: nil, s: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, name: "CudnnRNNParamsSize")
  self.execute("CudnnRNNParamsSize", [num_layers, num_units, input_size], T: typeT, S: s, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, num_proj: num_proj, name: name)
end
cudnn_rnn_params_to_canonical(num_layers, num_units, input_size, params, typeT: nil, num_params: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNParamsToCanonical") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 894
def self.cudnn_rnn_params_to_canonical(num_layers, num_units, input_size, params, typeT: nil, num_params: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, name: "CudnnRNNParamsToCanonical")
  self.execute("CudnnRNNParamsToCanonical", [num_layers, num_units, input_size, params], T: typeT, num_params: num_params, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, name: name)
end
cudnn_rnn_params_to_canonical_v2(num_layers, num_units, input_size, params, typeT: nil, num_params_weights: nil, num_params_biases: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, name: "CudnnRNNParamsToCanonicalV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 898
def self.cudnn_rnn_params_to_canonical_v2(num_layers, num_units, input_size, params, typeT: nil, num_params_weights: nil, num_params_biases: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, name: "CudnnRNNParamsToCanonicalV2")
  self.execute("CudnnRNNParamsToCanonicalV2", [num_layers, num_units, input_size, params], T: typeT, num_params_weights: num_params_weights, num_params_biases: num_params_biases, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, num_proj: num_proj, name: name)
end
cudnn_rnnv2(input, input_h, input_c, params, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, is_training: true, name: "CudnnRNNV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 902
def self.cudnn_rnnv2(input, input_h, input_c, params, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, is_training: true, name: "CudnnRNNV2")
  self.execute("CudnnRNNV2", [input, input_h, input_c, params], T: typeT, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, is_training: is_training, name: name)
end
cudnn_rnnv3(input, input_h, input_c, params, sequence_lengths, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, is_training: true, time_major: true, name: "CudnnRNNV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 906
def self.cudnn_rnnv3(input, input_h, input_c, params, sequence_lengths, typeT: nil, rnn_mode: "lstm", input_mode: "linear_input", direction: "unidirectional", dropout: 0.0, seed: 0, seed2: 0, num_proj: 0, is_training: true, time_major: true, name: "CudnnRNNV3")
  self.execute("CudnnRNNV3", [input, input_h, input_c, params, sequence_lengths], T: typeT, rnn_mode: rnn_mode, input_mode: input_mode, direction: direction, dropout: dropout, seed: seed, seed2: seed2, num_proj: num_proj, is_training: is_training, time_major: time_major, name: name)
end
cumprod(x, axis, exclusive: false, reverse: false, typeT: nil, tidx: :int32, name: "Cumprod") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 910
def self.cumprod(x, axis, exclusive: false, reverse: false, typeT: nil, tidx: :int32, name: "Cumprod")
  self.execute("Cumprod", [x, axis], exclusive: exclusive, reverse: reverse, T: typeT, Tidx: tidx, name: name)
end
cumsum(x, axis, exclusive: false, reverse: false, typeT: nil, tidx: :int32, name: "Cumsum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 914
def self.cumsum(x, axis, exclusive: false, reverse: false, typeT: nil, tidx: :int32, name: "Cumsum")
  self.execute("Cumsum", [x, axis], exclusive: exclusive, reverse: reverse, T: typeT, Tidx: tidx, name: name)
end
cumulative_logsumexp(x, axis, exclusive: false, reverse: false, typeT: nil, tidx: :int32, name: "CumulativeLogsumexp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 918
def self.cumulative_logsumexp(x, axis, exclusive: false, reverse: false, typeT: nil, tidx: :int32, name: "CumulativeLogsumexp")
  self.execute("CumulativeLogsumexp", [x, axis], exclusive: exclusive, reverse: reverse, T: typeT, Tidx: tidx, name: name)
end
data_format_dim_map(x, typeT: :int32, src_format: "NHWC", dst_format: "NCHW", name: "DataFormatDimMap") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 922
def self.data_format_dim_map(x, typeT: :int32, src_format: "NHWC", dst_format: "NCHW", name: "DataFormatDimMap")
  self.execute("DataFormatDimMap", [x], T: typeT, src_format: src_format, dst_format: dst_format, name: name)
end
data_format_vec_permute(x, typeT: :int32, src_format: "NHWC", dst_format: "NCHW", name: "DataFormatVecPermute") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 926
def self.data_format_vec_permute(x, typeT: :int32, src_format: "NHWC", dst_format: "NCHW", name: "DataFormatVecPermute")
  self.execute("DataFormatVecPermute", [x], T: typeT, src_format: src_format, dst_format: dst_format, name: name)
end
dataset_cardinality(input_dataset, name: "DatasetCardinality") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 930
def self.dataset_cardinality(input_dataset, name: "DatasetCardinality")
  self.execute("DatasetCardinality", [input_dataset], name: name)
end
dataset_from_graph(graph_def, name: "DatasetFromGraph") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 934
def self.dataset_from_graph(graph_def, name: "DatasetFromGraph")
  self.execute("DatasetFromGraph", [graph_def], name: name)
end
dataset_to_graph(input_dataset, stateful_whitelist: [], allow_stateful: false, strip_device_assignment: false, name: "DatasetToGraph") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 938
def self.dataset_to_graph(input_dataset, stateful_whitelist: [], allow_stateful: false, strip_device_assignment: false, name: "DatasetToGraph")
  self.execute("DatasetToGraph", [input_dataset], stateful_whitelist: stateful_whitelist, allow_stateful: allow_stateful, strip_device_assignment: strip_device_assignment, name: name)
end
dataset_to_graph_v2(input_dataset, external_state_policy: 0, strip_device_assignment: false, name: "DatasetToGraphV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 942
def self.dataset_to_graph_v2(input_dataset, external_state_policy: 0, strip_device_assignment: false, name: "DatasetToGraphV2")
  self.execute("DatasetToGraphV2", [input_dataset], external_state_policy: external_state_policy, strip_device_assignment: strip_device_assignment, name: name)
end
dataset_to_single_element(dataset, output_types: nil, output_shapes: nil, name: "DatasetToSingleElement") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 946
def self.dataset_to_single_element(dataset, output_types: nil, output_shapes: nil, name: "DatasetToSingleElement")
  self.execute("DatasetToSingleElement", [dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
dataset_to_tf_record(input_dataset, filename, compression_type, name: "DatasetToTFRecord") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 950
def self.dataset_to_tf_record(input_dataset, filename, compression_type, name: "DatasetToTFRecord")
  self.execute("DatasetToTFRecord", [input_dataset, filename, compression_type], name: name)
end
debug_gradient_identity(input, typeT: nil, name: "DebugGradientIdentity") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 954
def self.debug_gradient_identity(input, typeT: nil, name: "DebugGradientIdentity")
  self.execute("DebugGradientIdentity", [input], T: typeT, name: name)
end
debug_gradient_ref_identity(input, typeT: nil, name: "DebugGradientRefIdentity") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 958
def self.debug_gradient_ref_identity(input, typeT: nil, name: "DebugGradientRefIdentity")
  self.execute("DebugGradientRefIdentity", [input], T: typeT, name: name)
end
debug_identity(input, typeT: nil, device_name: "", tensor_name: "", debug_urls: [], gated_grpc: false, name: "DebugIdentity") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 962
def self.debug_identity(input, typeT: nil, device_name: "", tensor_name: "", debug_urls: [], gated_grpc: false, name: "DebugIdentity")
  self.execute("DebugIdentity", [input], T: typeT, device_name: device_name, tensor_name: tensor_name, debug_urls: debug_urls, gated_grpc: gated_grpc, name: name)
end
debug_identity_v2(input, typeT: nil, tfdbg_context_id: "", op_name: "", output_slot: -1, tensor_debug_mode: -1, debug_urls: [], name: "DebugIdentityV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 966
def self.debug_identity_v2(input, typeT: nil, tfdbg_context_id: "", op_name: "", output_slot: -1, tensor_debug_mode: -1, debug_urls: [], name: "DebugIdentityV2")
  self.execute("DebugIdentityV2", [input], T: typeT, tfdbg_context_id: tfdbg_context_id, op_name: op_name, output_slot: output_slot, tensor_debug_mode: tensor_debug_mode, debug_urls: debug_urls, name: name)
end
debug_nan_count(input, typeT: nil, device_name: "", tensor_name: "", debug_urls: [], gated_grpc: false, name: "DebugNanCount") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 970
def self.debug_nan_count(input, typeT: nil, device_name: "", tensor_name: "", debug_urls: [], gated_grpc: false, name: "DebugNanCount")
  self.execute("DebugNanCount", [input], T: typeT, device_name: device_name, tensor_name: tensor_name, debug_urls: debug_urls, gated_grpc: gated_grpc, name: name)
end
debug_numeric_summary(input, typeT: nil, device_name: "", tensor_name: "", debug_urls: [], lower_bound: -Infinity, upper_bound: Infinity, mute_if_healthy: false, gated_grpc: false, name: "DebugNumericSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 974
def self.debug_numeric_summary(input, typeT: nil, device_name: "", tensor_name: "", debug_urls: [], lower_bound: -Infinity, upper_bound: Infinity, mute_if_healthy: false, gated_grpc: false, name: "DebugNumericSummary")
  self.execute("DebugNumericSummary", [input], T: typeT, device_name: device_name, tensor_name: tensor_name, debug_urls: debug_urls, lower_bound: lower_bound, upper_bound: upper_bound, mute_if_healthy: mute_if_healthy, gated_grpc: gated_grpc, name: name)
end
decode_and_crop_jpeg(contents, crop_window, channels: 0, ratio: 1, fancy_upscaling: true, try_recover_truncated: false, acceptable_fraction: 1.0, dct_method: "", name: "DecodeAndCropJpeg") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 978
def self.decode_and_crop_jpeg(contents, crop_window, channels: 0, ratio: 1, fancy_upscaling: true, try_recover_truncated: false, acceptable_fraction: 1.0, dct_method: "", name: "DecodeAndCropJpeg")
  self.execute("DecodeAndCropJpeg", [contents, crop_window], channels: channels, ratio: ratio, fancy_upscaling: fancy_upscaling, try_recover_truncated: try_recover_truncated, acceptable_fraction: acceptable_fraction, dct_method: dct_method, name: name)
end
decode_base64(input, name: "DecodeBase64") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 982
def self.decode_base64(input, name: "DecodeBase64")
  self.execute("DecodeBase64", [input], name: name)
end
decode_bmp(contents, channels: 0, name: "DecodeBmp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 986
def self.decode_bmp(contents, channels: 0, name: "DecodeBmp")
  self.execute("DecodeBmp", [contents], channels: channels, name: name)
end
decode_compressed(bytes, compression_type: "", name: "DecodeCompressed") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 994
def self.decode_compressed(bytes, compression_type: "", name: "DecodeCompressed")
  self.execute("DecodeCompressed", [bytes], compression_type: compression_type, name: name)
end
decode_csv(records, record_defaults, out_type: nil, field_delim: ",", use_quote_delim: true, na_value: "", select_cols: [], name: "DecodeCSV") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 990
def self.decode_csv(records, record_defaults, out_type: nil, field_delim: ",", use_quote_delim: true, na_value: "", select_cols: [], name: "DecodeCSV")
  self.execute("DecodeCSV", [records, record_defaults], OUT_TYPE: out_type, field_delim: field_delim, use_quote_delim: use_quote_delim, na_value: na_value, select_cols: select_cols, name: name)
end
decode_gif(contents, name: "DecodeGif") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 998
def self.decode_gif(contents, name: "DecodeGif")
  self.execute("DecodeGif", [contents], name: name)
end
decode_jpeg(contents, channels: 0, ratio: 1, fancy_upscaling: true, try_recover_truncated: false, acceptable_fraction: 1.0, dct_method: "", name: "DecodeJpeg") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1006
def self.decode_jpeg(contents, channels: 0, ratio: 1, fancy_upscaling: true, try_recover_truncated: false, acceptable_fraction: 1.0, dct_method: "", name: "DecodeJpeg")
  self.execute("DecodeJpeg", [contents], channels: channels, ratio: ratio, fancy_upscaling: fancy_upscaling, try_recover_truncated: try_recover_truncated, acceptable_fraction: acceptable_fraction, dct_method: dct_method, name: name)
end
decode_json_example(json_examples, name: "DecodeJSONExample") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1002
def self.decode_json_example(json_examples, name: "DecodeJSONExample")
  self.execute("DecodeJSONExample", [json_examples], name: name)
end
decode_padded_raw(input_bytes, fixed_length, out_type: nil, little_endian: true, name: "DecodePaddedRaw") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1010
def self.decode_padded_raw(input_bytes, fixed_length, out_type: nil, little_endian: true, name: "DecodePaddedRaw")
  self.execute("DecodePaddedRaw", [input_bytes, fixed_length], out_type: out_type, little_endian: little_endian, name: name)
end
decode_png(contents, channels: 0, dtype: :uint8, name: "DecodePng") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1014
def self.decode_png(contents, channels: 0, dtype: :uint8, name: "DecodePng")
  self.execute("DecodePng", [contents], channels: channels, dtype: dtype, name: name)
end
decode_proto_v2(bytes, message_type: "", field_names: nil, output_types: nil, descriptor_source: "local://", message_format: "binary", sanitize: false, name: "DecodeProtoV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1018
def self.decode_proto_v2(bytes, message_type: "", field_names: nil, output_types: nil, descriptor_source: "local://", message_format: "binary", sanitize: false, name: "DecodeProtoV2")
  self.execute("DecodeProtoV2", [bytes], message_type: message_type, field_names: field_names, output_types: output_types, descriptor_source: descriptor_source, message_format: message_format, sanitize: sanitize, name: name)
end
decode_raw(bytes, out_type: nil, little_endian: true, name: "DecodeRaw") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1022
def self.decode_raw(bytes, out_type: nil, little_endian: true, name: "DecodeRaw")
  self.execute("DecodeRaw", [bytes], out_type: out_type, little_endian: little_endian, name: name)
end
decode_wav(contents, desired_channels: -1, desired_samples: -1, name: "DecodeWav") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1026
def self.decode_wav(contents, desired_channels: -1, desired_samples: -1, name: "DecodeWav")
  self.execute("DecodeWav", [contents], desired_channels: desired_channels, desired_samples: desired_samples, name: name)
end
deep_copy(x, typeT: nil, name: "DeepCopy") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1030
def self.deep_copy(x, typeT: nil, name: "DeepCopy")
  self.execute("DeepCopy", [x], T: typeT, name: name)
end
delete_iterator(handle, deleter, name: "DeleteIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1034
def self.delete_iterator(handle, deleter, name: "DeleteIterator")
  self.execute("DeleteIterator", [handle, deleter], name: name)
end
delete_memory_cache(handle, deleter, name: "DeleteMemoryCache") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1038
def self.delete_memory_cache(handle, deleter, name: "DeleteMemoryCache")
  self.execute("DeleteMemoryCache", [handle, deleter], name: name)
end
delete_multi_device_iterator(multi_device_iterator, iterators, deleter, n: nil, name: "DeleteMultiDeviceIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1042
def self.delete_multi_device_iterator(multi_device_iterator, iterators, deleter, n: nil, name: "DeleteMultiDeviceIterator")
  self.execute("DeleteMultiDeviceIterator", [multi_device_iterator, iterators, deleter], N: n, name: name)
end
delete_random_seed_generator(handle, deleter, name: "DeleteRandomSeedGenerator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1046
def self.delete_random_seed_generator(handle, deleter, name: "DeleteRandomSeedGenerator")
  self.execute("DeleteRandomSeedGenerator", [handle, deleter], name: name)
end
delete_session_tensor(handle, name: "DeleteSessionTensor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1050
def self.delete_session_tensor(handle, name: "DeleteSessionTensor")
  self.execute("DeleteSessionTensor", [handle], name: name)
end
dense_to_csr_sparse_matrix(dense_input, indices, typeT: nil, name: "DenseToCSRSparseMatrix") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1054
def self.dense_to_csr_sparse_matrix(dense_input, indices, typeT: nil, name: "DenseToCSRSparseMatrix")
  self.execute("DenseToCSRSparseMatrix", [dense_input, indices], T: typeT, name: name)
end
dense_to_dense_set_operation(set1, set2, set_operation: "", validate_indices: true, typeT: nil, name: "DenseToDenseSetOperation") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1058
def self.dense_to_dense_set_operation(set1, set2, set_operation: "", validate_indices: true, typeT: nil, name: "DenseToDenseSetOperation")
  self.execute("DenseToDenseSetOperation", [set1, set2], set_operation: set_operation, validate_indices: validate_indices, T: typeT, name: name)
end
dense_to_sparse_batch_dataset(input_dataset, batch_size, row_shape, output_types: nil, output_shapes: nil, name: "DenseToSparseBatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1062
def self.dense_to_sparse_batch_dataset(input_dataset, batch_size, row_shape, output_types: nil, output_shapes: nil, name: "DenseToSparseBatchDataset")
  self.execute("DenseToSparseBatchDataset", [input_dataset, batch_size, row_shape], output_types: output_types, output_shapes: output_shapes, name: name)
end
dense_to_sparse_set_operation(set1, set2_indices, set2_values, set2_shape, set_operation: "", validate_indices: true, typeT: nil, name: "DenseToSparseSetOperation") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1066
def self.dense_to_sparse_set_operation(set1, set2_indices, set2_values, set2_shape, set_operation: "", validate_indices: true, typeT: nil, name: "DenseToSparseSetOperation")
  self.execute("DenseToSparseSetOperation", [set1, set2_indices, set2_values, set2_shape], set_operation: set_operation, validate_indices: validate_indices, T: typeT, name: name)
end
depth_to_space(input, typeT: nil, block_size: nil, data_format: "NHWC", name: "DepthToSpace") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1070
def self.depth_to_space(input, typeT: nil, block_size: nil, data_format: "NHWC", name: "DepthToSpace")
  self.execute("DepthToSpace", [input], T: typeT, block_size: block_size, data_format: data_format, name: name)
end
depthwise_conv2d_native(input, filter, typeT: nil, strides: nil, padding: nil, data_format: "NHWC", dilations: [], name: "DepthwiseConv2dNative") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1074
def self.depthwise_conv2d_native(input, filter, typeT: nil, strides: nil, padding: nil, data_format: "NHWC", dilations: [], name: "DepthwiseConv2dNative")
  self.execute("DepthwiseConv2dNative", [input, filter], T: typeT, strides: strides, padding: padding, data_format: data_format, dilations: dilations, name: name)
end
depthwise_conv2d_native_backprop_filter(input, filter_sizes, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NHWC", dilations: [], name: "DepthwiseConv2dNativeBackpropFilter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1078
def self.depthwise_conv2d_native_backprop_filter(input, filter_sizes, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NHWC", dilations: [], name: "DepthwiseConv2dNativeBackpropFilter")
  self.execute("DepthwiseConv2dNativeBackpropFilter", [input, filter_sizes, out_backprop], T: typeT, strides: strides, padding: padding, data_format: data_format, dilations: dilations, name: name)
end
depthwise_conv2d_native_backprop_input(input_sizes, filter, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NHWC", dilations: [], name: "DepthwiseConv2dNativeBackpropInput") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1082
def self.depthwise_conv2d_native_backprop_input(input_sizes, filter, out_backprop, typeT: nil, strides: nil, padding: nil, data_format: "NHWC", dilations: [], name: "DepthwiseConv2dNativeBackpropInput")
  self.execute("DepthwiseConv2dNativeBackpropInput", [input_sizes, filter, out_backprop], T: typeT, strides: strides, padding: padding, data_format: data_format, dilations: dilations, name: name)
end
dequantize(input, min_range, max_range, typeT: nil, mode: "MIN_COMBINED", narrow_range: false, axis: -1, name: "Dequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1086
def self.dequantize(input, min_range, max_range, typeT: nil, mode: "MIN_COMBINED", narrow_range: false, axis: -1, name: "Dequantize")
  self.execute("Dequantize", [input, min_range, max_range], T: typeT, mode: mode, narrow_range: narrow_range, axis: axis, name: name)
end
deserialize_iterator(resource_handle, serialized, name: "DeserializeIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1090
def self.deserialize_iterator(resource_handle, serialized, name: "DeserializeIterator")
  self.execute("DeserializeIterator", [resource_handle, serialized], name: name)
end
deserialize_many_sparse(serialized_sparse, dtype: nil, name: "DeserializeManySparse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1094
def self.deserialize_many_sparse(serialized_sparse, dtype: nil, name: "DeserializeManySparse")
  self.execute("DeserializeManySparse", [serialized_sparse], dtype: dtype, name: name)
end
deserialize_sparse(serialized_sparse, dtype: nil, tserialized: :string, name: "DeserializeSparse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1098
def self.deserialize_sparse(serialized_sparse, dtype: nil, tserialized: :string, name: "DeserializeSparse")
  self.execute("DeserializeSparse", [serialized_sparse], dtype: dtype, Tserialized: tserialized, name: name)
end
destroy_resource_op(resource, ignore_lookup_error: true, name: "DestroyResourceOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1102
def self.destroy_resource_op(resource, ignore_lookup_error: true, name: "DestroyResourceOp")
  self.execute("DestroyResourceOp", [resource], ignore_lookup_error: ignore_lookup_error, name: name)
end
destroy_temporary_variable(ref, typeT: nil, var_name: "", name: "DestroyTemporaryVariable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1106
def self.destroy_temporary_variable(ref, typeT: nil, var_name: "", name: "DestroyTemporaryVariable")
  self.execute("DestroyTemporaryVariable", [ref], T: typeT, var_name: var_name, name: name)
end
diag(diagonal, typeT: nil, name: "Diag") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1110
def self.diag(diagonal, typeT: nil, name: "Diag")
  self.execute("Diag", [diagonal], T: typeT, name: name)
end
diag_part(input, typeT: nil, name: "DiagPart") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1114
def self.diag_part(input, typeT: nil, name: "DiagPart")
  self.execute("DiagPart", [input], T: typeT, name: name)
end
digamma(x, typeT: nil, name: "Digamma") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1118
def self.digamma(x, typeT: nil, name: "Digamma")
  self.execute("Digamma", [x], T: typeT, name: name)
end
dilation2_d(input, filter, typeT: nil, strides: nil, rates: nil, padding: nil, name: "Dilation2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1122
def self.dilation2_d(input, filter, typeT: nil, strides: nil, rates: nil, padding: nil, name: "Dilation2D")
  self.execute("Dilation2D", [input, filter], T: typeT, strides: strides, rates: rates, padding: padding, name: name)
end
dilation2_d_backprop_filter(input, filter, out_backprop, typeT: nil, strides: nil, rates: nil, padding: nil, name: "Dilation2DBackpropFilter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1126
def self.dilation2_d_backprop_filter(input, filter, out_backprop, typeT: nil, strides: nil, rates: nil, padding: nil, name: "Dilation2DBackpropFilter")
  self.execute("Dilation2DBackpropFilter", [input, filter, out_backprop], T: typeT, strides: strides, rates: rates, padding: padding, name: name)
end
dilation2_d_backprop_input(input, filter, out_backprop, typeT: nil, strides: nil, rates: nil, padding: nil, name: "Dilation2DBackpropInput") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1130
def self.dilation2_d_backprop_input(input, filter, out_backprop, typeT: nil, strides: nil, rates: nil, padding: nil, name: "Dilation2DBackpropInput")
  self.execute("Dilation2DBackpropInput", [input, filter, out_backprop], T: typeT, strides: strides, rates: rates, padding: padding, name: name)
end
directed_interleave_dataset(selector_input_dataset, data_input_datasets, output_types: nil, output_shapes: nil, n: nil, name: "DirectedInterleaveDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1134
def self.directed_interleave_dataset(selector_input_dataset, data_input_datasets, output_types: nil, output_shapes: nil, n: nil, name: "DirectedInterleaveDataset")
  self.execute("DirectedInterleaveDataset", [selector_input_dataset, data_input_datasets], output_types: output_types, output_shapes: output_shapes, N: n, name: name)
end
div(x, y, typeT: nil, name: "Div") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1138
def self.div(x, y, typeT: nil, name: "Div")
  self.execute("Div", [x, y], T: typeT, name: name)
end
div_no_nan(x, y, typeT: nil, name: "DivNoNan") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1142
def self.div_no_nan(x, y, typeT: nil, name: "DivNoNan")
  self.execute("DivNoNan", [x, y], T: typeT, name: name)
end
draw_bounding_boxes(images, boxes, typeT: :float, name: "DrawBoundingBoxes") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1146
def self.draw_bounding_boxes(images, boxes, typeT: :float, name: "DrawBoundingBoxes")
  self.execute("DrawBoundingBoxes", [images, boxes], T: typeT, name: name)
end
draw_bounding_boxes_v2(images, boxes, colors, typeT: :float, name: "DrawBoundingBoxesV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1150
def self.draw_bounding_boxes_v2(images, boxes, colors, typeT: :float, name: "DrawBoundingBoxesV2")
  self.execute("DrawBoundingBoxesV2", [images, boxes, colors], T: typeT, name: name)
end
dynamic_partition(data, partitions, num_partitions: nil, typeT: nil, name: "DynamicPartition") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1154
def self.dynamic_partition(data, partitions, num_partitions: nil, typeT: nil, name: "DynamicPartition")
  self.execute("DynamicPartition", [data, partitions], num_partitions: num_partitions, T: typeT, name: name)
end
dynamic_stitch(indices, data, n: nil, typeT: nil, name: "DynamicStitch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1158
def self.dynamic_stitch(indices, data, n: nil, typeT: nil, name: "DynamicStitch")
  self.execute("DynamicStitch", [indices, data], N: n, T: typeT, name: name)
end
eager_py_func(input, token: "", is_async: false, tin: nil, tout: nil, name: "EagerPyFunc") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1162
def self.eager_py_func(input, token: "", is_async: false, tin: nil, tout: nil, name: "EagerPyFunc")
  self.execute("EagerPyFunc", [input], token: token, is_async: is_async, Tin: tin, Tout: tout, name: name)
end
edit_distance(hypothesis_indices, hypothesis_values, hypothesis_shape, truth_indices, truth_values, truth_shape, normalize: true, typeT: nil, name: "EditDistance") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1166
def self.edit_distance(hypothesis_indices, hypothesis_values, hypothesis_shape, truth_indices, truth_values, truth_shape, normalize: true, typeT: nil, name: "EditDistance")
  self.execute("EditDistance", [hypothesis_indices, hypothesis_values, hypothesis_shape, truth_indices, truth_values, truth_shape], normalize: normalize, T: typeT, name: name)
end
eig(input, compute_v: true, typeT: nil, tout: nil, name: "Eig") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1170
def self.eig(input, compute_v: true, typeT: nil, tout: nil, name: "Eig")
  self.execute("Eig", [input], compute_v: compute_v, T: typeT, Tout: tout, name: name)
end
einsum(inputs, equation: "", n: nil, typeT: nil, name: "Einsum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1174
def self.einsum(inputs, equation: "", n: nil, typeT: nil, name: "Einsum")
  self.execute("Einsum", [inputs], equation: equation, N: n, T: typeT, name: name)
end
elu(features, typeT: nil, name: "Elu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1178
def self.elu(features, typeT: nil, name: "Elu")
  self.execute("Elu", [features], T: typeT, name: name)
end
elu_grad(gradients, outputs, typeT: nil, name: "EluGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1182
def self.elu_grad(gradients, outputs, typeT: nil, name: "EluGrad")
  self.execute("EluGrad", [gradients, outputs], T: typeT, name: name)
end
empty(shape, dtype: nil, init: false, name: "Empty") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1186
def self.empty(shape, dtype: nil, init: false, name: "Empty")
  self.execute("Empty", [shape], dtype: dtype, init: init, name: name)
end
empty_tensor_list(element_shape, max_num_elements, element_dtype: nil, shape_type: nil, name: "EmptyTensorList") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1190
def self.empty_tensor_list(element_shape, max_num_elements, element_dtype: nil, shape_type: nil, name: "EmptyTensorList")
  self.execute("EmptyTensorList", [element_shape, max_num_elements], element_dtype: element_dtype, shape_type: shape_type, name: name)
end
encode_base64(input, pad: false, name: "EncodeBase64") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1194
def self.encode_base64(input, pad: false, name: "EncodeBase64")
  self.execute("EncodeBase64", [input], pad: pad, name: name)
end
encode_jpeg(image, format: "", quality: 95, progressive: false, optimize_size: false, chroma_downsampling: true, density_unit: "in", x_density: 300, y_density: 300, xmp_metadata: "", name: "EncodeJpeg") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1198
def self.encode_jpeg(image, format: "", quality: 95, progressive: false, optimize_size: false, chroma_downsampling: true, density_unit: "in", x_density: 300, y_density: 300, xmp_metadata: "", name: "EncodeJpeg")
  self.execute("EncodeJpeg", [image], format: format, quality: quality, progressive: progressive, optimize_size: optimize_size, chroma_downsampling: chroma_downsampling, density_unit: density_unit, x_density: x_density, y_density: y_density, xmp_metadata: xmp_metadata, name: name)
end
encode_jpeg_variable_quality(images, quality, name: "EncodeJpegVariableQuality") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1202
def self.encode_jpeg_variable_quality(images, quality, name: "EncodeJpegVariableQuality")
  self.execute("EncodeJpegVariableQuality", [images, quality], name: name)
end
encode_png(image, compression: -1, typeT: :uint8, name: "EncodePng") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1206
def self.encode_png(image, compression: -1, typeT: :uint8, name: "EncodePng")
  self.execute("EncodePng", [image], compression: compression, T: typeT, name: name)
end
encode_proto(sizes, values, field_names: nil, message_type: "", descriptor_source: "local://", tinput_types: nil, name: "EncodeProto") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1210
def self.encode_proto(sizes, values, field_names: nil, message_type: "", descriptor_source: "local://", tinput_types: nil, name: "EncodeProto")
  self.execute("EncodeProto", [sizes, values], field_names: field_names, message_type: message_type, descriptor_source: descriptor_source, Tinput_types: tinput_types, name: name)
end
encode_wav(audio, sample_rate, name: "EncodeWav") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1214
def self.encode_wav(audio, sample_rate, name: "EncodeWav")
  self.execute("EncodeWav", [audio, sample_rate], name: name)
end
enqueue_tpu_embedding_integer_batch(batch, mode_override, n: nil, device_ordinal: -1, name: "EnqueueTPUEmbeddingIntegerBatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1218
def self.enqueue_tpu_embedding_integer_batch(batch, mode_override, n: nil, device_ordinal: -1, name: "EnqueueTPUEmbeddingIntegerBatch")
  self.execute("EnqueueTPUEmbeddingIntegerBatch", [batch, mode_override], N: n, device_ordinal: device_ordinal, name: name)
end
enqueue_tpu_embedding_sparse_batch(sample_indices, embedding_indices, aggregation_weights, mode_override, t1: :int32, t2: :int32, t3: :float, n: nil, device_ordinal: -1, combiners: [], name: "EnqueueTPUEmbeddingSparseBatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1222
def self.enqueue_tpu_embedding_sparse_batch(sample_indices, embedding_indices, aggregation_weights, mode_override, t1: :int32, t2: :int32, t3: :float, n: nil, device_ordinal: -1, combiners: [], name: "EnqueueTPUEmbeddingSparseBatch")
  self.execute("EnqueueTPUEmbeddingSparseBatch", [sample_indices, embedding_indices, aggregation_weights, mode_override], T1: t1, T2: t2, T3: t3, N: n, device_ordinal: device_ordinal, combiners: combiners, name: name)
end
enqueue_tpu_embedding_sparse_tensor_batch(sample_indices, embedding_indices, aggregation_weights, mode_override, t1: :int32, t2: :int32, t3: :float, n: nil, device_ordinal: -1, combiners: [], table_ids: nil, max_sequence_lengths: [], name: "EnqueueTPUEmbeddingSparseTensorBatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1226
def self.enqueue_tpu_embedding_sparse_tensor_batch(sample_indices, embedding_indices, aggregation_weights, mode_override, t1: :int32, t2: :int32, t3: :float, n: nil, device_ordinal: -1, combiners: [], table_ids: nil, max_sequence_lengths: [], name: "EnqueueTPUEmbeddingSparseTensorBatch")
  self.execute("EnqueueTPUEmbeddingSparseTensorBatch", [sample_indices, embedding_indices, aggregation_weights, mode_override], T1: t1, T2: t2, T3: t3, N: n, device_ordinal: device_ordinal, combiners: combiners, table_ids: table_ids, max_sequence_lengths: max_sequence_lengths, name: name)
end
ensure_shape(input, shape: nil, typeT: nil, name: "EnsureShape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1230
def self.ensure_shape(input, shape: nil, typeT: nil, name: "EnsureShape")
  self.execute("EnsureShape", [input], shape: shape, T: typeT, name: name)
end
enter(data, typeT: nil, frame_name: "", is_constant: false, parallel_iterations: 10, name: "Enter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1234
def self.enter(data, typeT: nil, frame_name: "", is_constant: false, parallel_iterations: 10, name: "Enter")
  self.execute("Enter", [data], T: typeT, frame_name: frame_name, is_constant: is_constant, parallel_iterations: parallel_iterations, name: name)
end
equal(x, y, typeT: nil, incompatible_shape_error: true, name: "Equal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1238
def self.equal(x, y, typeT: nil, incompatible_shape_error: true, name: "Equal")
  self.execute("Equal", [x, y], T: typeT, incompatible_shape_error: incompatible_shape_error, name: name)
end
erf(x, typeT: nil, name: "Erf") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1242
def self.erf(x, typeT: nil, name: "Erf")
  self.execute("Erf", [x], T: typeT, name: name)
end
erfc(x, typeT: nil, name: "Erfc") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1246
def self.erfc(x, typeT: nil, name: "Erfc")
  self.execute("Erfc", [x], T: typeT, name: name)
end
erfinv(x, typeT: nil, name: "Erfinv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1250
def self.erfinv(x, typeT: nil, name: "Erfinv")
  self.execute("Erfinv", [x], T: typeT, name: name)
end
euclidean_norm(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "EuclideanNorm") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1254
def self.euclidean_norm(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "EuclideanNorm")
  self.execute("EuclideanNorm", [input, reduction_indices], keep_dims: keep_dims, T: typeT, Tidx: tidx, name: name)
end
execute(op_type, inputs=[], attrs={}) click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5
def self.execute(op_type, inputs=[], attrs={})
  context = ExecutionContext.current(inputs)
  attrs = attrs.compact
  operation = context.create_operation(op_type, inputs, attrs)
  if context.is_a?(Graph::Graph)
    operation
  else
    context.execute(operation)
  end
end
exit(data, typeT: nil, name: "Exit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1258
def self.exit(data, typeT: nil, name: "Exit")
  self.execute("Exit", [data], T: typeT, name: name)
end
exp(x, typeT: nil, name: "Exp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1262
def self.exp(x, typeT: nil, name: "Exp")
  self.execute("Exp", [x], T: typeT, name: name)
end
expand_dims(input, dim, typeT: nil, tdim: :int32, name: "ExpandDims") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1266
def self.expand_dims(input, dim, typeT: nil, tdim: :int32, name: "ExpandDims")
  self.execute("ExpandDims", [input, dim], T: typeT, Tdim: tdim, name: name)
end
experimental_assert_next_dataset(input_dataset, transformations, output_types: nil, output_shapes: nil, name: "ExperimentalAssertNextDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1270
def self.experimental_assert_next_dataset(input_dataset, transformations, output_types: nil, output_shapes: nil, name: "ExperimentalAssertNextDataset")
  self.execute("ExperimentalAssertNextDataset", [input_dataset, transformations], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_auto_shard_dataset(input_dataset, num_workers, index, auto_shard_policy: 0, output_types: nil, output_shapes: nil, name: "ExperimentalAutoShardDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1274
def self.experimental_auto_shard_dataset(input_dataset, num_workers, index, auto_shard_policy: 0, output_types: nil, output_shapes: nil, name: "ExperimentalAutoShardDataset")
  self.execute("ExperimentalAutoShardDataset", [input_dataset, num_workers, index], auto_shard_policy: auto_shard_policy, output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_bytes_produced_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "ExperimentalBytesProducedStatsDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1278
def self.experimental_bytes_produced_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "ExperimentalBytesProducedStatsDataset")
  self.execute("ExperimentalBytesProducedStatsDataset", [input_dataset, tag], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_choose_fastest_dataset(input_datasets, n: nil, num_experiments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalChooseFastestDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1286
def self.experimental_choose_fastest_dataset(input_datasets, n: nil, num_experiments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalChooseFastestDataset")
  self.execute("ExperimentalChooseFastestDataset", [input_datasets], N: n, num_experiments: num_experiments, output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_csv_dataset(filenames, compression_type, buffer_size, header, field_delim, use_quote_delim, na_value, select_cols, record_defaults, output_types: nil, output_shapes: nil, name: "ExperimentalCSVDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1282
def self.experimental_csv_dataset(filenames, compression_type, buffer_size, header, field_delim, use_quote_delim, na_value, select_cols, record_defaults, output_types: nil, output_shapes: nil, name: "ExperimentalCSVDataset")
  self.execute("ExperimentalCSVDataset", [filenames, compression_type, buffer_size, header, field_delim, use_quote_delim, na_value, select_cols, record_defaults], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_dataset_cardinality(input_dataset, name: "ExperimentalDatasetCardinality") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1290
def self.experimental_dataset_cardinality(input_dataset, name: "ExperimentalDatasetCardinality")
  self.execute("ExperimentalDatasetCardinality", [input_dataset], name: name)
end
experimental_dataset_to_tf_record(input_dataset, filename, compression_type, name: "ExperimentalDatasetToTFRecord") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1294
def self.experimental_dataset_to_tf_record(input_dataset, filename, compression_type, name: "ExperimentalDatasetToTFRecord")
  self.execute("ExperimentalDatasetToTFRecord", [input_dataset, filename, compression_type], name: name)
end
experimental_dense_to_sparse_batch_dataset(input_dataset, batch_size, row_shape, output_types: nil, output_shapes: nil, name: "ExperimentalDenseToSparseBatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1298
def self.experimental_dense_to_sparse_batch_dataset(input_dataset, batch_size, row_shape, output_types: nil, output_shapes: nil, name: "ExperimentalDenseToSparseBatchDataset")
  self.execute("ExperimentalDenseToSparseBatchDataset", [input_dataset, batch_size, row_shape], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_directed_interleave_dataset(selector_input_dataset, data_input_datasets, output_types: nil, output_shapes: nil, n: nil, name: "ExperimentalDirectedInterleaveDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1302
def self.experimental_directed_interleave_dataset(selector_input_dataset, data_input_datasets, output_types: nil, output_shapes: nil, n: nil, name: "ExperimentalDirectedInterleaveDataset")
  self.execute("ExperimentalDirectedInterleaveDataset", [selector_input_dataset, data_input_datasets], output_types: output_types, output_shapes: output_shapes, N: n, name: name)
end
experimental_group_by_reducer_dataset(input_dataset, key_func_other_arguments, init_func_other_arguments, reduce_func_other_arguments, finalize_func_other_arguments, key_func: nil, init_func: nil, reduce_func: nil, finalize_func: nil, tkey_func_other_arguments: nil, tinit_func_other_arguments: nil, treduce_func_other_arguments: nil, tfinalize_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalGroupByReducerDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1306
def self.experimental_group_by_reducer_dataset(input_dataset, key_func_other_arguments, init_func_other_arguments, reduce_func_other_arguments, finalize_func_other_arguments, key_func: nil, init_func: nil, reduce_func: nil, finalize_func: nil, tkey_func_other_arguments: nil, tinit_func_other_arguments: nil, treduce_func_other_arguments: nil, tfinalize_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalGroupByReducerDataset")
  self.execute("ExperimentalGroupByReducerDataset", [input_dataset, key_func_other_arguments, init_func_other_arguments, reduce_func_other_arguments, finalize_func_other_arguments], key_func: key_func, init_func: init_func, reduce_func: reduce_func, finalize_func: finalize_func, Tkey_func_other_arguments: tkey_func_other_arguments, Tinit_func_other_arguments: tinit_func_other_arguments, Treduce_func_other_arguments: treduce_func_other_arguments, Tfinalize_func_other_arguments: tfinalize_func_other_arguments, output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_group_by_window_dataset(input_dataset, key_func_other_arguments, reduce_func_other_arguments, window_size_func_other_arguments, key_func: nil, reduce_func: nil, window_size_func: nil, tkey_func_other_arguments: nil, treduce_func_other_arguments: nil, twindow_size_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalGroupByWindowDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1310
def self.experimental_group_by_window_dataset(input_dataset, key_func_other_arguments, reduce_func_other_arguments, window_size_func_other_arguments, key_func: nil, reduce_func: nil, window_size_func: nil, tkey_func_other_arguments: nil, treduce_func_other_arguments: nil, twindow_size_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalGroupByWindowDataset")
  self.execute("ExperimentalGroupByWindowDataset", [input_dataset, key_func_other_arguments, reduce_func_other_arguments, window_size_func_other_arguments], key_func: key_func, reduce_func: reduce_func, window_size_func: window_size_func, Tkey_func_other_arguments: tkey_func_other_arguments, Treduce_func_other_arguments: treduce_func_other_arguments, Twindow_size_func_other_arguments: twindow_size_func_other_arguments, output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_ignore_errors_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalIgnoreErrorsDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1314
def self.experimental_ignore_errors_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalIgnoreErrorsDataset")
  self.execute("ExperimentalIgnoreErrorsDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_iterator_get_device(resource, name: "ExperimentalIteratorGetDevice") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1318
def self.experimental_iterator_get_device(resource, name: "ExperimentalIteratorGetDevice")
  self.execute("ExperimentalIteratorGetDevice", [resource], name: name)
end
experimental_latency_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "ExperimentalLatencyStatsDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1326
def self.experimental_latency_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "ExperimentalLatencyStatsDataset")
  self.execute("ExperimentalLatencyStatsDataset", [input_dataset, tag], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_lmdb_dataset(filenames, output_types: nil, output_shapes: nil, name: "ExperimentalLMDBDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1322
def self.experimental_lmdb_dataset(filenames, output_types: nil, output_shapes: nil, name: "ExperimentalLMDBDataset")
  self.execute("ExperimentalLMDBDataset", [filenames], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_map_and_batch_dataset(input_dataset, other_arguments, batch_size, num_parallel_calls, drop_remainder, f: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, name: "ExperimentalMapAndBatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1330
def self.experimental_map_and_batch_dataset(input_dataset, other_arguments, batch_size, num_parallel_calls, drop_remainder, f: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, name: "ExperimentalMapAndBatchDataset")
  self.execute("ExperimentalMapAndBatchDataset", [input_dataset, other_arguments, batch_size, num_parallel_calls, drop_remainder], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, preserve_cardinality: preserve_cardinality, name: name)
end
experimental_map_dataset(input_dataset, other_arguments, f: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, preserve_cardinality: false, name: "ExperimentalMapDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1334
def self.experimental_map_dataset(input_dataset, other_arguments, f: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, preserve_cardinality: false, name: "ExperimentalMapDataset")
  self.execute("ExperimentalMapDataset", [input_dataset, other_arguments], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, use_inter_op_parallelism: use_inter_op_parallelism, preserve_cardinality: preserve_cardinality, name: name)
end
experimental_matching_files_dataset(patterns, name: "ExperimentalMatchingFilesDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1338
def self.experimental_matching_files_dataset(patterns, name: "ExperimentalMatchingFilesDataset")
  self.execute("ExperimentalMatchingFilesDataset", [patterns], name: name)
end
experimental_max_intra_op_parallelism_dataset(input_dataset, max_intra_op_parallelism, output_types: nil, output_shapes: nil, name: "ExperimentalMaxIntraOpParallelismDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1342
def self.experimental_max_intra_op_parallelism_dataset(input_dataset, max_intra_op_parallelism, output_types: nil, output_shapes: nil, name: "ExperimentalMaxIntraOpParallelismDataset")
  self.execute("ExperimentalMaxIntraOpParallelismDataset", [input_dataset, max_intra_op_parallelism], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_non_serializable_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalNonSerializableDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1346
def self.experimental_non_serializable_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalNonSerializableDataset")
  self.execute("ExperimentalNonSerializableDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_parallel_interleave_dataset(input_dataset, other_arguments, cycle_length, block_length, sloppy, buffer_output_elements, prefetch_input_elements, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalParallelInterleaveDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1350
def self.experimental_parallel_interleave_dataset(input_dataset, other_arguments, cycle_length, block_length, sloppy, buffer_output_elements, prefetch_input_elements, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalParallelInterleaveDataset")
  self.execute("ExperimentalParallelInterleaveDataset", [input_dataset, other_arguments, cycle_length, block_length, sloppy, buffer_output_elements, prefetch_input_elements], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_parse_example_dataset(input_dataset, num_parallel_calls, dense_defaults, sparse_keys: nil, dense_keys: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, output_types: nil, output_shapes: nil, sloppy: false, name: "ExperimentalParseExampleDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1354
def self.experimental_parse_example_dataset(input_dataset, num_parallel_calls, dense_defaults, sparse_keys: nil, dense_keys: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, output_types: nil, output_shapes: nil, sloppy: false, name: "ExperimentalParseExampleDataset")
  self.execute("ExperimentalParseExampleDataset", [input_dataset, num_parallel_calls, dense_defaults], sparse_keys: sparse_keys, dense_keys: dense_keys, sparse_types: sparse_types, Tdense: tdense, dense_shapes: dense_shapes, output_types: output_types, output_shapes: output_shapes, sloppy: sloppy, name: name)
end
experimental_private_thread_pool_dataset(input_dataset, num_threads, output_types: nil, output_shapes: nil, name: "ExperimentalPrivateThreadPoolDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1358
def self.experimental_private_thread_pool_dataset(input_dataset, num_threads, output_types: nil, output_shapes: nil, name: "ExperimentalPrivateThreadPoolDataset")
  self.execute("ExperimentalPrivateThreadPoolDataset", [input_dataset, num_threads], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_random_dataset(seed, seed2, output_types: nil, output_shapes: nil, name: "ExperimentalRandomDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1362
def self.experimental_random_dataset(seed, seed2, output_types: nil, output_shapes: nil, name: "ExperimentalRandomDataset")
  self.execute("ExperimentalRandomDataset", [seed, seed2], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_rebatch_dataset(input_dataset, num_replicas, output_types: nil, output_shapes: nil, use_fallback: true, name: "ExperimentalRebatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1366
def self.experimental_rebatch_dataset(input_dataset, num_replicas, output_types: nil, output_shapes: nil, use_fallback: true, name: "ExperimentalRebatchDataset")
  self.execute("ExperimentalRebatchDataset", [input_dataset, num_replicas], output_types: output_types, output_shapes: output_shapes, use_fallback: use_fallback, name: name)
end
experimental_scan_dataset(input_dataset, initial_state, other_arguments, f: nil, tstate: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, name: "ExperimentalScanDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1370
def self.experimental_scan_dataset(input_dataset, initial_state, other_arguments, f: nil, tstate: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, name: "ExperimentalScanDataset")
  self.execute("ExperimentalScanDataset", [input_dataset, initial_state, other_arguments], f: f, Tstate: tstate, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, preserve_cardinality: preserve_cardinality, name: name)
end
experimental_set_stats_aggregator_dataset(input_dataset, stats_aggregator, tag, counter_prefix, output_types: nil, output_shapes: nil, name: "ExperimentalSetStatsAggregatorDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1374
def self.experimental_set_stats_aggregator_dataset(input_dataset, stats_aggregator, tag, counter_prefix, output_types: nil, output_shapes: nil, name: "ExperimentalSetStatsAggregatorDataset")
  self.execute("ExperimentalSetStatsAggregatorDataset", [input_dataset, stats_aggregator, tag, counter_prefix], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_sleep_dataset(input_dataset, sleep_microseconds, output_types: nil, output_shapes: nil, name: "ExperimentalSleepDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1378
def self.experimental_sleep_dataset(input_dataset, sleep_microseconds, output_types: nil, output_shapes: nil, name: "ExperimentalSleepDataset")
  self.execute("ExperimentalSleepDataset", [input_dataset, sleep_microseconds], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_sliding_window_dataset(input_dataset, window_size, window_shift, window_stride, output_types: nil, output_shapes: nil, name: "ExperimentalSlidingWindowDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1382
def self.experimental_sliding_window_dataset(input_dataset, window_size, window_shift, window_stride, output_types: nil, output_shapes: nil, name: "ExperimentalSlidingWindowDataset")
  self.execute("ExperimentalSlidingWindowDataset", [input_dataset, window_size, window_shift, window_stride], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_sql_dataset(driver_name, data_source_name, query, output_types: nil, output_shapes: nil, name: "ExperimentalSqlDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1386
def self.experimental_sql_dataset(driver_name, data_source_name, query, output_types: nil, output_shapes: nil, name: "ExperimentalSqlDataset")
  self.execute("ExperimentalSqlDataset", [driver_name, data_source_name, query], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_stats_aggregator_handle(container: "", shared_name: "", name: "ExperimentalStatsAggregatorHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1390
def self.experimental_stats_aggregator_handle(container: "", shared_name: "", name: "ExperimentalStatsAggregatorHandle")
  self.execute("ExperimentalStatsAggregatorHandle", [], container: container, shared_name: shared_name, name: name)
end
experimental_stats_aggregator_summary(iterator, name: "ExperimentalStatsAggregatorSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1394
def self.experimental_stats_aggregator_summary(iterator, name: "ExperimentalStatsAggregatorSummary")
  self.execute("ExperimentalStatsAggregatorSummary", [iterator], name: name)
end
experimental_take_while_dataset(input_dataset, other_arguments, predicate: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalTakeWhileDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1398
def self.experimental_take_while_dataset(input_dataset, other_arguments, predicate: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "ExperimentalTakeWhileDataset")
  self.execute("ExperimentalTakeWhileDataset", [input_dataset, other_arguments], predicate: predicate, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_thread_pool_dataset(input_dataset, thread_pool, output_types: nil, output_shapes: nil, name: "ExperimentalThreadPoolDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1402
def self.experimental_thread_pool_dataset(input_dataset, thread_pool, output_types: nil, output_shapes: nil, name: "ExperimentalThreadPoolDataset")
  self.execute("ExperimentalThreadPoolDataset", [input_dataset, thread_pool], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_thread_pool_handle(num_threads: nil, max_intra_op_parallelism: 1, display_name: "", container: "", shared_name: "", name: "ExperimentalThreadPoolHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1406
def self.experimental_thread_pool_handle(num_threads: nil, max_intra_op_parallelism: 1, display_name: "", container: "", shared_name: "", name: "ExperimentalThreadPoolHandle")
  self.execute("ExperimentalThreadPoolHandle", [], num_threads: num_threads, max_intra_op_parallelism: max_intra_op_parallelism, display_name: display_name, container: container, shared_name: shared_name, name: name)
end
experimental_unbatch_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalUnbatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1410
def self.experimental_unbatch_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalUnbatchDataset")
  self.execute("ExperimentalUnbatchDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
experimental_unique_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalUniqueDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1414
def self.experimental_unique_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "ExperimentalUniqueDataset")
  self.execute("ExperimentalUniqueDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
expm1(x, typeT: nil, name: "Expm1") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1418
def self.expm1(x, typeT: nil, name: "Expm1")
  self.execute("Expm1", [x], T: typeT, name: name)
end
extract_glimpse(input, size, offsets, centered: true, normalized: true, uniform_noise: true, noise: "uniform", name: "ExtractGlimpse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1422
def self.extract_glimpse(input, size, offsets, centered: true, normalized: true, uniform_noise: true, noise: "uniform", name: "ExtractGlimpse")
  self.execute("ExtractGlimpse", [input, size, offsets], centered: centered, normalized: normalized, uniform_noise: uniform_noise, noise: noise, name: name)
end
extract_image_patches(images, ksizes: nil, strides: nil, rates: nil, typeT: nil, padding: nil, name: "ExtractImagePatches") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1426
def self.extract_image_patches(images, ksizes: nil, strides: nil, rates: nil, typeT: nil, padding: nil, name: "ExtractImagePatches")
  self.execute("ExtractImagePatches", [images], ksizes: ksizes, strides: strides, rates: rates, T: typeT, padding: padding, name: name)
end
extract_jpeg_shape(contents, output_type: :int32, name: "ExtractJpegShape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1430
def self.extract_jpeg_shape(contents, output_type: :int32, name: "ExtractJpegShape")
  self.execute("ExtractJpegShape", [contents], output_type: output_type, name: name)
end
extract_volume_patches(input, ksizes: nil, strides: nil, typeT: nil, padding: nil, name: "ExtractVolumePatches") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1434
def self.extract_volume_patches(input, ksizes: nil, strides: nil, typeT: nil, padding: nil, name: "ExtractVolumePatches")
  self.execute("ExtractVolumePatches", [input], ksizes: ksizes, strides: strides, T: typeT, padding: padding, name: name)
end
fact(name: "Fact") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1458
def self.fact(name: "Fact")
  self.execute("Fact", [], name: name)
end
fake_param(dtype: nil, shape: nil, name: "FakeParam") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1462
def self.fake_param(dtype: nil, shape: nil, name: "FakeParam")
  self.execute("FakeParam", [], dtype: dtype, shape: shape, name: name)
end
fake_quant_with_min_max_args(inputs, min: -6.0, max: 6.0, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxArgs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1466
def self.fake_quant_with_min_max_args(inputs, min: -6.0, max: 6.0, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxArgs")
  self.execute("FakeQuantWithMinMaxArgs", [inputs], min: min, max: max, num_bits: num_bits, narrow_range: narrow_range, name: name)
end
fake_quant_with_min_max_args_gradient(gradients, inputs, min: -6.0, max: 6.0, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxArgsGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1470
def self.fake_quant_with_min_max_args_gradient(gradients, inputs, min: -6.0, max: 6.0, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxArgsGradient")
  self.execute("FakeQuantWithMinMaxArgsGradient", [gradients, inputs], min: min, max: max, num_bits: num_bits, narrow_range: narrow_range, name: name)
end
fake_quant_with_min_max_vars(inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVars") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1474
def self.fake_quant_with_min_max_vars(inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVars")
  self.execute("FakeQuantWithMinMaxVars", [inputs, min, max], num_bits: num_bits, narrow_range: narrow_range, name: name)
end
fake_quant_with_min_max_vars_gradient(gradients, inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVarsGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1478
def self.fake_quant_with_min_max_vars_gradient(gradients, inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVarsGradient")
  self.execute("FakeQuantWithMinMaxVarsGradient", [gradients, inputs, min, max], num_bits: num_bits, narrow_range: narrow_range, name: name)
end
fake_quant_with_min_max_vars_per_channel(inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVarsPerChannel") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1482
def self.fake_quant_with_min_max_vars_per_channel(inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVarsPerChannel")
  self.execute("FakeQuantWithMinMaxVarsPerChannel", [inputs, min, max], num_bits: num_bits, narrow_range: narrow_range, name: name)
end
fake_quant_with_min_max_vars_per_channel_gradient(gradients, inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVarsPerChannelGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1486
def self.fake_quant_with_min_max_vars_per_channel_gradient(gradients, inputs, min, max, num_bits: 8, narrow_range: false, name: "FakeQuantWithMinMaxVarsPerChannelGradient")
  self.execute("FakeQuantWithMinMaxVarsPerChannelGradient", [gradients, inputs, min, max], num_bits: num_bits, narrow_range: narrow_range, name: name)
end
fake_queue(resource, name: "FakeQueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1490
def self.fake_queue(resource, name: "FakeQueue")
  self.execute("FakeQueue", [resource], name: name)
end
fft(input, tcomplex: :complex64, name: "FFT") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1438
def self.fft(input, tcomplex: :complex64, name: "FFT")
  self.execute("FFT", [input], Tcomplex: tcomplex, name: name)
end
fft2_d(input, tcomplex: :complex64, name: "FFT2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1442
def self.fft2_d(input, tcomplex: :complex64, name: "FFT2D")
  self.execute("FFT2D", [input], Tcomplex: tcomplex, name: name)
end
fft3_d(input, tcomplex: :complex64, name: "FFT3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1446
def self.fft3_d(input, tcomplex: :complex64, name: "FFT3D")
  self.execute("FFT3D", [input], Tcomplex: tcomplex, name: name)
end
fifo_queue(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "FIFOQueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1450
def self.fifo_queue(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "FIFOQueue")
  self.execute("FIFOQueue", [], component_types: component_types, shapes: shapes, capacity: capacity, container: container, shared_name: shared_name, name: name)
end
fifo_queue_v2(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "FIFOQueueV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1454
def self.fifo_queue_v2(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "FIFOQueueV2")
  self.execute("FIFOQueueV2", [], component_types: component_types, shapes: shapes, capacity: capacity, container: container, shared_name: shared_name, name: name)
end
fill(dims, value, typeT: nil, index_type: :int32, name: "Fill") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1494
def self.fill(dims, value, typeT: nil, index_type: :int32, name: "Fill")
  self.execute("Fill", [dims, value], T: typeT, index_type: index_type, name: name)
end
filter_by_last_component_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "FilterByLastComponentDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1498
def self.filter_by_last_component_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "FilterByLastComponentDataset")
  self.execute("FilterByLastComponentDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
filter_dataset(input_dataset, other_arguments, predicate: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "FilterDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1502
def self.filter_dataset(input_dataset, other_arguments, predicate: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "FilterDataset")
  self.execute("FilterDataset", [input_dataset, other_arguments], predicate: predicate, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, name: name)
end
fingerprint(data, method, typeT: nil, name: "Fingerprint") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1506
def self.fingerprint(data, method, typeT: nil, name: "Fingerprint")
  self.execute("Fingerprint", [data, method], T: typeT, name: name)
end
fixed_length_record_dataset(filenames, header_bytes, record_bytes, footer_bytes, buffer_size, name: "FixedLengthRecordDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1510
def self.fixed_length_record_dataset(filenames, header_bytes, record_bytes, footer_bytes, buffer_size, name: "FixedLengthRecordDataset")
  self.execute("FixedLengthRecordDataset", [filenames, header_bytes, record_bytes, footer_bytes, buffer_size], name: name)
end
fixed_length_record_dataset_v2(filenames, header_bytes, record_bytes, footer_bytes, buffer_size, compression_type, name: "FixedLengthRecordDatasetV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1514
def self.fixed_length_record_dataset_v2(filenames, header_bytes, record_bytes, footer_bytes, buffer_size, compression_type, name: "FixedLengthRecordDatasetV2")
  self.execute("FixedLengthRecordDatasetV2", [filenames, header_bytes, record_bytes, footer_bytes, buffer_size, compression_type], name: name)
end
fixed_length_record_reader(header_bytes: 0, record_bytes: nil, footer_bytes: 0, hop_bytes: 0, container: "", shared_name: "", name: "FixedLengthRecordReader") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1518
def self.fixed_length_record_reader(header_bytes: 0, record_bytes: nil, footer_bytes: 0, hop_bytes: 0, container: "", shared_name: "", name: "FixedLengthRecordReader")
  self.execute("FixedLengthRecordReader", [], header_bytes: header_bytes, record_bytes: record_bytes, footer_bytes: footer_bytes, hop_bytes: hop_bytes, container: container, shared_name: shared_name, name: name)
end
fixed_length_record_reader_v2(header_bytes: 0, record_bytes: nil, footer_bytes: 0, hop_bytes: 0, container: "", shared_name: "", encoding: "", name: "FixedLengthRecordReaderV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1522
def self.fixed_length_record_reader_v2(header_bytes: 0, record_bytes: nil, footer_bytes: 0, hop_bytes: 0, container: "", shared_name: "", encoding: "", name: "FixedLengthRecordReaderV2")
  self.execute("FixedLengthRecordReaderV2", [], header_bytes: header_bytes, record_bytes: record_bytes, footer_bytes: footer_bytes, hop_bytes: hop_bytes, container: container, shared_name: shared_name, encoding: encoding, name: name)
end
fixed_unigram_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, vocab_file: "", distortion: 1.0, num_reserved_ids: 0, num_shards: 1, shard: 0, unigrams: [], seed: 0, seed2: 0, name: "FixedUnigramCandidateSampler") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1526
def self.fixed_unigram_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, vocab_file: "", distortion: 1.0, num_reserved_ids: 0, num_shards: 1, shard: 0, unigrams: [], seed: 0, seed2: 0, name: "FixedUnigramCandidateSampler")
  self.execute("FixedUnigramCandidateSampler", [true_classes], num_true: num_true, num_sampled: num_sampled, unique: unique, range_max: range_max, vocab_file: vocab_file, distortion: distortion, num_reserved_ids: num_reserved_ids, num_shards: num_shards, shard: shard, unigrams: unigrams, seed: seed, seed2: seed2, name: name)
end
flat_map_dataset(input_dataset, other_arguments, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "FlatMapDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1530
def self.flat_map_dataset(input_dataset, other_arguments, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "FlatMapDataset")
  self.execute("FlatMapDataset", [input_dataset, other_arguments], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, name: name)
end
floor(x, typeT: nil, name: "Floor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1534
def self.floor(x, typeT: nil, name: "Floor")
  self.execute("Floor", [x], T: typeT, name: name)
end
floor_div(x, y, typeT: nil, name: "FloorDiv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1538
def self.floor_div(x, y, typeT: nil, name: "FloorDiv")
  self.execute("FloorDiv", [x, y], T: typeT, name: name)
end
floor_mod(x, y, typeT: nil, name: "FloorMod") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1542
def self.floor_mod(x, y, typeT: nil, name: "FloorMod")
  self.execute("FloorMod", [x, y], T: typeT, name: name)
end
flush_summary_writer(writer, name: "FlushSummaryWriter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1546
def self.flush_summary_writer(writer, name: "FlushSummaryWriter")
  self.execute("FlushSummaryWriter", [writer], name: name)
end
for(start, limit, delta, input, typeT: nil, body: nil, name: "For") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1550
def self.for(start, limit, delta, input, typeT: nil, body: nil, name: "For")
  self.execute("For", [start, limit, delta, input], T: typeT, body: body, name: name)
end
fractional_avg_pool(value, pooling_ratio: nil, pseudo_random: false, overlapping: false, deterministic: false, seed: 0, seed2: 0, typeT: nil, name: "FractionalAvgPool") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1554
def self.fractional_avg_pool(value, pooling_ratio: nil, pseudo_random: false, overlapping: false, deterministic: false, seed: 0, seed2: 0, typeT: nil, name: "FractionalAvgPool")
  self.execute("FractionalAvgPool", [value], pooling_ratio: pooling_ratio, pseudo_random: pseudo_random, overlapping: overlapping, deterministic: deterministic, seed: seed, seed2: seed2, T: typeT, name: name)
end
fractional_avg_pool_grad(orig_input_tensor_shape, out_backprop, row_pooling_sequence, col_pooling_sequence, overlapping: false, typeT: nil, name: "FractionalAvgPoolGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1558
def self.fractional_avg_pool_grad(orig_input_tensor_shape, out_backprop, row_pooling_sequence, col_pooling_sequence, overlapping: false, typeT: nil, name: "FractionalAvgPoolGrad")
  self.execute("FractionalAvgPoolGrad", [orig_input_tensor_shape, out_backprop, row_pooling_sequence, col_pooling_sequence], overlapping: overlapping, T: typeT, name: name)
end
fractional_max_pool(value, pooling_ratio: nil, pseudo_random: false, overlapping: false, deterministic: false, seed: 0, seed2: 0, typeT: nil, name: "FractionalMaxPool") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1562
def self.fractional_max_pool(value, pooling_ratio: nil, pseudo_random: false, overlapping: false, deterministic: false, seed: 0, seed2: 0, typeT: nil, name: "FractionalMaxPool")
  self.execute("FractionalMaxPool", [value], pooling_ratio: pooling_ratio, pseudo_random: pseudo_random, overlapping: overlapping, deterministic: deterministic, seed: seed, seed2: seed2, T: typeT, name: name)
end
fractional_max_pool_grad(orig_input, orig_output, out_backprop, row_pooling_sequence, col_pooling_sequence, overlapping: false, typeT: nil, name: "FractionalMaxPoolGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1566
def self.fractional_max_pool_grad(orig_input, orig_output, out_backprop, row_pooling_sequence, col_pooling_sequence, overlapping: false, typeT: nil, name: "FractionalMaxPoolGrad")
  self.execute("FractionalMaxPoolGrad", [orig_input, orig_output, out_backprop, row_pooling_sequence, col_pooling_sequence], overlapping: overlapping, T: typeT, name: name)
end
fused_batch_norm(x, scale, offset, mean, variance, typeT: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNorm") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1570
def self.fused_batch_norm(x, scale, offset, mean, variance, typeT: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNorm")
  self.execute("FusedBatchNorm", [x, scale, offset, mean, variance], T: typeT, epsilon: epsilon, data_format: data_format, is_training: is_training, name: name)
end
fused_batch_norm_grad(y_backprop, x, scale, reserve_space_1, reserve_space_2, typeT: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1574
def self.fused_batch_norm_grad(y_backprop, x, scale, reserve_space_1, reserve_space_2, typeT: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormGrad")
  self.execute("FusedBatchNormGrad", [y_backprop, x, scale, reserve_space_1, reserve_space_2], T: typeT, epsilon: epsilon, data_format: data_format, is_training: is_training, name: name)
end
fused_batch_norm_grad_v2(y_backprop, x, scale, reserve_space_1, reserve_space_2, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormGradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1578
def self.fused_batch_norm_grad_v2(y_backprop, x, scale, reserve_space_1, reserve_space_2, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormGradV2")
  self.execute("FusedBatchNormGradV2", [y_backprop, x, scale, reserve_space_1, reserve_space_2], T: typeT, U: u, epsilon: epsilon, data_format: data_format, is_training: is_training, name: name)
end
fused_batch_norm_grad_v3(y_backprop, x, scale, reserve_space_1, reserve_space_2, reserve_space_3, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormGradV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1582
def self.fused_batch_norm_grad_v3(y_backprop, x, scale, reserve_space_1, reserve_space_2, reserve_space_3, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormGradV3")
  self.execute("FusedBatchNormGradV3", [y_backprop, x, scale, reserve_space_1, reserve_space_2, reserve_space_3], T: typeT, U: u, epsilon: epsilon, data_format: data_format, is_training: is_training, name: name)
end
fused_batch_norm_v2(x, scale, offset, mean, variance, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1586
def self.fused_batch_norm_v2(x, scale, offset, mean, variance, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormV2")
  self.execute("FusedBatchNormV2", [x, scale, offset, mean, variance], T: typeT, U: u, epsilon: epsilon, data_format: data_format, is_training: is_training, name: name)
end
fused_batch_norm_v3(x, scale, offset, mean, variance, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1590
def self.fused_batch_norm_v3(x, scale, offset, mean, variance, typeT: nil, u: nil, epsilon: 9.999999747378752e-05, data_format: "NHWC", is_training: true, name: "FusedBatchNormV3")
  self.execute("FusedBatchNormV3", [x, scale, offset, mean, variance], T: typeT, U: u, epsilon: epsilon, data_format: data_format, is_training: is_training, name: name)
end
fused_pad_conv2_d(input, paddings, filter, typeT: nil, mode: nil, strides: nil, padding: nil, name: "FusedPadConv2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1594
def self.fused_pad_conv2_d(input, paddings, filter, typeT: nil, mode: nil, strides: nil, padding: nil, name: "FusedPadConv2D")
  self.execute("FusedPadConv2D", [input, paddings, filter], T: typeT, mode: mode, strides: strides, padding: padding, name: name)
end
fused_resize_and_pad_conv2_d(input, size, paddings, filter, typeT: nil, resize_align_corners: false, mode: nil, strides: nil, padding: nil, name: "FusedResizeAndPadConv2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1598
def self.fused_resize_and_pad_conv2_d(input, size, paddings, filter, typeT: nil, resize_align_corners: false, mode: nil, strides: nil, padding: nil, name: "FusedResizeAndPadConv2D")
  self.execute("FusedResizeAndPadConv2D", [input, size, paddings, filter], T: typeT, resize_align_corners: resize_align_corners, mode: mode, strides: strides, padding: padding, name: name)
end
gather(params, indices, validate_indices: true, tparams: nil, tindices: nil, name: "Gather") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1610
def self.gather(params, indices, validate_indices: true, tparams: nil, tindices: nil, name: "Gather")
  self.execute("Gather", [params, indices], validate_indices: validate_indices, Tparams: tparams, Tindices: tindices, name: name)
end
gather_nd(params, indices, tparams: nil, tindices: nil, name: "GatherNd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1614
def self.gather_nd(params, indices, tparams: nil, tindices: nil, name: "GatherNd")
  self.execute("GatherNd", [params, indices], Tparams: tparams, Tindices: tindices, name: name)
end
gather_v2(params, indices, axis, batch_dims: 0, tparams: nil, tindices: nil, taxis: nil, name: "GatherV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1618
def self.gather_v2(params, indices, axis, batch_dims: 0, tparams: nil, tindices: nil, taxis: nil, name: "GatherV2")
  self.execute("GatherV2", [params, indices, axis], batch_dims: batch_dims, Tparams: tparams, Tindices: tindices, Taxis: taxis, name: name)
end
generate_vocab_remapping(new_vocab_file, old_vocab_file, new_vocab_offset: nil, num_new_vocab: nil, old_vocab_size: -1, name: "GenerateVocabRemapping") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1622
def self.generate_vocab_remapping(new_vocab_file, old_vocab_file, new_vocab_offset: nil, num_new_vocab: nil, old_vocab_size: -1, name: "GenerateVocabRemapping")
  self.execute("GenerateVocabRemapping", [new_vocab_file, old_vocab_file], new_vocab_offset: new_vocab_offset, num_new_vocab: num_new_vocab, old_vocab_size: old_vocab_size, name: name)
end
generator_dataset(init_func_other_args, next_func_other_args, finalize_func_other_args, init_func: nil, next_func: nil, finalize_func: nil, tinit_func_args: nil, tnext_func_args: nil, tfinalize_func_args: nil, output_types: nil, output_shapes: nil, name: "GeneratorDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1626
def self.generator_dataset(init_func_other_args, next_func_other_args, finalize_func_other_args, init_func: nil, next_func: nil, finalize_func: nil, tinit_func_args: nil, tnext_func_args: nil, tfinalize_func_args: nil, output_types: nil, output_shapes: nil, name: "GeneratorDataset")
  self.execute("GeneratorDataset", [init_func_other_args, next_func_other_args, finalize_func_other_args], init_func: init_func, next_func: next_func, finalize_func: finalize_func, Tinit_func_args: tinit_func_args, Tnext_func_args: tnext_func_args, Tfinalize_func_args: tfinalize_func_args, output_types: output_types, output_shapes: output_shapes, name: name)
end
get_session_handle(value, typeT: nil, name: "GetSessionHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1630
def self.get_session_handle(value, typeT: nil, name: "GetSessionHandle")
  self.execute("GetSessionHandle", [value], T: typeT, name: name)
end
get_session_handle_v2(value, typeT: nil, name: "GetSessionHandleV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1634
def self.get_session_handle_v2(value, typeT: nil, name: "GetSessionHandleV2")
  self.execute("GetSessionHandleV2", [value], T: typeT, name: name)
end
get_session_tensor(handle, dtype: nil, name: "GetSessionTensor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1638
def self.get_session_tensor(handle, dtype: nil, name: "GetSessionTensor")
  self.execute("GetSessionTensor", [handle], dtype: dtype, name: name)
end
greater(x, y, typeT: nil, name: "Greater") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1642
def self.greater(x, y, typeT: nil, name: "Greater")
  self.execute("Greater", [x, y], T: typeT, name: name)
end
greater_equal(x, y, typeT: nil, name: "GreaterEqual") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1646
def self.greater_equal(x, y, typeT: nil, name: "GreaterEqual")
  self.execute("GreaterEqual", [x, y], T: typeT, name: name)
end
group_by_reducer_dataset(input_dataset, key_func_other_arguments, init_func_other_arguments, reduce_func_other_arguments, finalize_func_other_arguments, key_func: nil, init_func: nil, reduce_func: nil, finalize_func: nil, tkey_func_other_arguments: nil, tinit_func_other_arguments: nil, treduce_func_other_arguments: nil, tfinalize_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "GroupByReducerDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1650
def self.group_by_reducer_dataset(input_dataset, key_func_other_arguments, init_func_other_arguments, reduce_func_other_arguments, finalize_func_other_arguments, key_func: nil, init_func: nil, reduce_func: nil, finalize_func: nil, tkey_func_other_arguments: nil, tinit_func_other_arguments: nil, treduce_func_other_arguments: nil, tfinalize_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "GroupByReducerDataset")
  self.execute("GroupByReducerDataset", [input_dataset, key_func_other_arguments, init_func_other_arguments, reduce_func_other_arguments, finalize_func_other_arguments], key_func: key_func, init_func: init_func, reduce_func: reduce_func, finalize_func: finalize_func, Tkey_func_other_arguments: tkey_func_other_arguments, Tinit_func_other_arguments: tinit_func_other_arguments, Treduce_func_other_arguments: treduce_func_other_arguments, Tfinalize_func_other_arguments: tfinalize_func_other_arguments, output_types: output_types, output_shapes: output_shapes, name: name)
end
group_by_window_dataset(input_dataset, key_func_other_arguments, reduce_func_other_arguments, window_size_func_other_arguments, key_func: nil, reduce_func: nil, window_size_func: nil, tkey_func_other_arguments: nil, treduce_func_other_arguments: nil, twindow_size_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "GroupByWindowDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1654
def self.group_by_window_dataset(input_dataset, key_func_other_arguments, reduce_func_other_arguments, window_size_func_other_arguments, key_func: nil, reduce_func: nil, window_size_func: nil, tkey_func_other_arguments: nil, treduce_func_other_arguments: nil, twindow_size_func_other_arguments: nil, output_types: nil, output_shapes: nil, name: "GroupByWindowDataset")
  self.execute("GroupByWindowDataset", [input_dataset, key_func_other_arguments, reduce_func_other_arguments, window_size_func_other_arguments], key_func: key_func, reduce_func: reduce_func, window_size_func: window_size_func, Tkey_func_other_arguments: tkey_func_other_arguments, Treduce_func_other_arguments: treduce_func_other_arguments, Twindow_size_func_other_arguments: twindow_size_func_other_arguments, output_types: output_types, output_shapes: output_shapes, name: name)
end
gru_block_cell(x, h_prev, w_ru, w_c, b_ru, b_c, typeT: nil, name: "GRUBlockCell") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1602
def self.gru_block_cell(x, h_prev, w_ru, w_c, b_ru, b_c, typeT: nil, name: "GRUBlockCell")
  self.execute("GRUBlockCell", [x, h_prev, w_ru, w_c, b_ru, b_c], T: typeT, name: name)
end
gru_block_cell_grad(x, h_prev, w_ru, w_c, b_ru, b_c, r, u, c, d_h, typeT: nil, name: "GRUBlockCellGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1606
def self.gru_block_cell_grad(x, h_prev, w_ru, w_c, b_ru, b_c, r, u, c, d_h, typeT: nil, name: "GRUBlockCellGrad")
  self.execute("GRUBlockCellGrad", [x, h_prev, w_ru, w_c, b_ru, b_c, r, u, c, d_h], T: typeT, name: name)
end
guarantee_const(input, typeT: nil, name: "GuaranteeConst") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1658
def self.guarantee_const(input, typeT: nil, name: "GuaranteeConst")
  self.execute("GuaranteeConst", [input], T: typeT, name: name)
end
hash_table(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "HashTable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1666
def self.hash_table(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "HashTable")
  self.execute("HashTable", [], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, name: name)
end
hash_table_v2(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "HashTableV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1670
def self.hash_table_v2(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "HashTableV2")
  self.execute("HashTableV2", [], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, name: name)
end
histogram_fixed_width(values, value_range, nbins, typeT: nil, dtype: :int32, name: "HistogramFixedWidth") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1674
def self.histogram_fixed_width(values, value_range, nbins, typeT: nil, dtype: :int32, name: "HistogramFixedWidth")
  self.execute("HistogramFixedWidth", [values, value_range, nbins], T: typeT, dtype: dtype, name: name)
end
histogram_summary(tag, values, typeT: :float, name: "HistogramSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1678
def self.histogram_summary(tag, values, typeT: :float, name: "HistogramSummary")
  self.execute("HistogramSummary", [tag, values], T: typeT, name: name)
end
host_const(value: nil, dtype: nil, name: "HostConst") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1682
def self.host_const(value: nil, dtype: nil, name: "HostConst")
  self.execute("HostConst", [], value: value, dtype: dtype, name: name)
end
hsv_to_rgb(images, typeT: :float, name: "HSVToRGB") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1662
def self.hsv_to_rgb(images, typeT: :float, name: "HSVToRGB")
  self.execute("HSVToRGB", [images], T: typeT, name: name)
end
identity(input, typeT: nil, name: "Identity") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1710
def self.identity(input, typeT: nil, name: "Identity")
  self.execute("Identity", [input], T: typeT, name: name)
end
identity_n(input, typeT: nil, name: "IdentityN") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1714
def self.identity_n(input, typeT: nil, name: "IdentityN")
  self.execute("IdentityN", [input], T: typeT, name: name)
end
identity_reader(container: "", shared_name: "", name: "IdentityReader") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1718
def self.identity_reader(container: "", shared_name: "", name: "IdentityReader")
  self.execute("IdentityReader", [], container: container, shared_name: shared_name, name: name)
end
identity_reader_v2(container: "", shared_name: "", name: "IdentityReaderV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1722
def self.identity_reader_v2(container: "", shared_name: "", name: "IdentityReaderV2")
  self.execute("IdentityReaderV2", [], container: container, shared_name: shared_name, name: name)
end
if(cond, input, tcond: nil, tin: nil, tout: nil, then_branch: nil, else_branch: nil, output_shapes: [], name: "If") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1726
def self.if(cond, input, tcond: nil, tin: nil, tout: nil, then_branch: nil, else_branch: nil, output_shapes: [], name: "If")
  self.execute("If", [cond, input], Tcond: tcond, Tin: tin, Tout: tout, then_branch: then_branch, else_branch: else_branch, output_shapes: output_shapes, name: name)
end
ifft(input, tcomplex: :complex64, name: "IFFT") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1686
def self.ifft(input, tcomplex: :complex64, name: "IFFT")
  self.execute("IFFT", [input], Tcomplex: tcomplex, name: name)
end
ifft2_d(input, tcomplex: :complex64, name: "IFFT2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1690
def self.ifft2_d(input, tcomplex: :complex64, name: "IFFT2D")
  self.execute("IFFT2D", [input], Tcomplex: tcomplex, name: name)
end
ifft3_d(input, tcomplex: :complex64, name: "IFFT3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1694
def self.ifft3_d(input, tcomplex: :complex64, name: "IFFT3D")
  self.execute("IFFT3D", [input], Tcomplex: tcomplex, name: name)
end
igamma(a, x, typeT: nil, name: "Igamma") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1730
def self.igamma(a, x, typeT: nil, name: "Igamma")
  self.execute("Igamma", [a, x], T: typeT, name: name)
end
igamma_grad_a(a, x, typeT: nil, name: "IgammaGradA") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1734
def self.igamma_grad_a(a, x, typeT: nil, name: "IgammaGradA")
  self.execute("IgammaGradA", [a, x], T: typeT, name: name)
end
igammac(a, x, typeT: nil, name: "Igammac") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1738
def self.igammac(a, x, typeT: nil, name: "Igammac")
  self.execute("Igammac", [a, x], T: typeT, name: name)
end
ignore_errors_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "IgnoreErrorsDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1742
def self.ignore_errors_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "IgnoreErrorsDataset")
  self.execute("IgnoreErrorsDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
imag(input, typeT: :complex64, tout: :float, name: "Imag") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1746
def self.imag(input, typeT: :complex64, tout: :float, name: "Imag")
  self.execute("Imag", [input], T: typeT, Tout: tout, name: name)
end
image_summary(tag, tensor, max_images: 3, typeT: :float, bad_color: [], name: "ImageSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1750
def self.image_summary(tag, tensor, max_images: 3, typeT: :float, bad_color: [], name: "ImageSummary")
  self.execute("ImageSummary", [tag, tensor], max_images: max_images, T: typeT, bad_color: bad_color, name: name)
end
immutable_const(dtype: nil, shape: nil, memory_region_name: "", name: "ImmutableConst") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1754
def self.immutable_const(dtype: nil, shape: nil, memory_region_name: "", name: "ImmutableConst")
  self.execute("ImmutableConst", [], dtype: dtype, shape: shape, memory_region_name: memory_region_name, name: name)
end
import_event(writer, event, name: "ImportEvent") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1758
def self.import_event(writer, event, name: "ImportEvent")
  self.execute("ImportEvent", [writer, event], name: name)
end
in_top_k(predictions, targets, k: nil, typeT: :int32, name: "InTopK") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1762
def self.in_top_k(predictions, targets, k: nil, typeT: :int32, name: "InTopK")
  self.execute("InTopK", [predictions, targets], k: k, T: typeT, name: name)
end
in_top_kv2(predictions, targets, k, typeT: :int32, name: "InTopKV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1766
def self.in_top_kv2(predictions, targets, k, typeT: :int32, name: "InTopKV2")
  self.execute("InTopKV2", [predictions, targets, k], T: typeT, name: name)
end
infeed_dequeue(dtype: nil, shape: nil, name: "InfeedDequeue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1770
def self.infeed_dequeue(dtype: nil, shape: nil, name: "InfeedDequeue")
  self.execute("InfeedDequeue", [], dtype: dtype, shape: shape, name: name)
end
infeed_dequeue_tuple(dtypes: nil, shapes: nil, name: "InfeedDequeueTuple") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1774
def self.infeed_dequeue_tuple(dtypes: nil, shapes: nil, name: "InfeedDequeueTuple")
  self.execute("InfeedDequeueTuple", [], dtypes: dtypes, shapes: shapes, name: name)
end
infeed_enqueue(input, dtype: nil, shape: [], layout: [], device_ordinal: -1, name: "InfeedEnqueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1778
def self.infeed_enqueue(input, dtype: nil, shape: [], layout: [], device_ordinal: -1, name: "InfeedEnqueue")
  self.execute("InfeedEnqueue", [input], dtype: dtype, shape: shape, layout: layout, device_ordinal: device_ordinal, name: name)
end
infeed_enqueue_prelinearized_buffer(input, device_ordinal: -1, name: "InfeedEnqueuePrelinearizedBuffer") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1782
def self.infeed_enqueue_prelinearized_buffer(input, device_ordinal: -1, name: "InfeedEnqueuePrelinearizedBuffer")
  self.execute("InfeedEnqueuePrelinearizedBuffer", [input], device_ordinal: device_ordinal, name: name)
end
infeed_enqueue_tuple(inputs, dtypes: nil, shapes: nil, layouts: [], device_ordinal: -1, name: "InfeedEnqueueTuple") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1786
def self.infeed_enqueue_tuple(inputs, dtypes: nil, shapes: nil, layouts: [], device_ordinal: -1, name: "InfeedEnqueueTuple")
  self.execute("InfeedEnqueueTuple", [inputs], dtypes: dtypes, shapes: shapes, layouts: layouts, device_ordinal: device_ordinal, name: name)
end
initialize_table(table_handle, keys, values, tkey: nil, tval: nil, name: "InitializeTable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1790
def self.initialize_table(table_handle, keys, values, tkey: nil, tval: nil, name: "InitializeTable")
  self.execute("InitializeTable", [table_handle, keys, values], Tkey: tkey, Tval: tval, name: name)
end
initialize_table_from_text_file(table_handle, filename, key_index: nil, value_index: nil, vocab_size: -1, delimiter: " ", name: "InitializeTableFromTextFile") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1794
def self.initialize_table_from_text_file(table_handle, filename, key_index: nil, value_index: nil, vocab_size: -1, delimiter: "     ", name: "InitializeTableFromTextFile")
  self.execute("InitializeTableFromTextFile", [table_handle, filename], key_index: key_index, value_index: value_index, vocab_size: vocab_size, delimiter: delimiter, name: name)
end
initialize_table_from_text_file_v2(table_handle, filename, key_index: nil, value_index: nil, vocab_size: -1, delimiter: " ", name: "InitializeTableFromTextFileV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1798
def self.initialize_table_from_text_file_v2(table_handle, filename, key_index: nil, value_index: nil, vocab_size: -1, delimiter: "  ", name: "InitializeTableFromTextFileV2")
  self.execute("InitializeTableFromTextFileV2", [table_handle, filename], key_index: key_index, value_index: value_index, vocab_size: vocab_size, delimiter: delimiter, name: name)
end
initialize_table_v2(table_handle, keys, values, tkey: nil, tval: nil, name: "InitializeTableV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1802
def self.initialize_table_v2(table_handle, keys, values, tkey: nil, tval: nil, name: "InitializeTableV2")
  self.execute("InitializeTableV2", [table_handle, keys, values], Tkey: tkey, Tval: tval, name: name)
end
inplace_add(x, i, v, typeT: nil, name: "InplaceAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1806
def self.inplace_add(x, i, v, typeT: nil, name: "InplaceAdd")
  self.execute("InplaceAdd", [x, i, v], T: typeT, name: name)
end
inplace_sub(x, i, v, typeT: nil, name: "InplaceSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1810
def self.inplace_sub(x, i, v, typeT: nil, name: "InplaceSub")
  self.execute("InplaceSub", [x, i, v], T: typeT, name: name)
end
inplace_update(x, i, v, typeT: nil, name: "InplaceUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1814
def self.inplace_update(x, i, v, typeT: nil, name: "InplaceUpdate")
  self.execute("InplaceUpdate", [x, i, v], T: typeT, name: name)
end
interleave_dataset(input_dataset, other_arguments, cycle_length, block_length, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "InterleaveDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1818
def self.interleave_dataset(input_dataset, other_arguments, cycle_length, block_length, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "InterleaveDataset")
  self.execute("InterleaveDataset", [input_dataset, other_arguments, cycle_length, block_length], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, name: name)
end
inv(x, typeT: nil, name: "Inv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1822
def self.inv(x, typeT: nil, name: "Inv")
  self.execute("Inv", [x], T: typeT, name: name)
end
inv_grad(y, dy, typeT: nil, name: "InvGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1826
def self.inv_grad(y, dy, typeT: nil, name: "InvGrad")
  self.execute("InvGrad", [y, dy], T: typeT, name: name)
end
invert(x, typeT: nil, name: "Invert") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1830
def self.invert(x, typeT: nil, name: "Invert")
  self.execute("Invert", [x], T: typeT, name: name)
end
invert_permutation(x, typeT: :int32, name: "InvertPermutation") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1834
def self.invert_permutation(x, typeT: :int32, name: "InvertPermutation")
  self.execute("InvertPermutation", [x], T: typeT, name: name)
end
irfft(input, fft_length, treal: :float, tcomplex: :complex64, name: "IRFFT") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1698
def self.irfft(input, fft_length, treal: :float, tcomplex: :complex64, name: "IRFFT")
  self.execute("IRFFT", [input, fft_length], Treal: treal, Tcomplex: tcomplex, name: name)
end
irfft2_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "IRFFT2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1702
def self.irfft2_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "IRFFT2D")
  self.execute("IRFFT2D", [input, fft_length], Treal: treal, Tcomplex: tcomplex, name: name)
end
irfft3_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "IRFFT3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1706
def self.irfft3_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "IRFFT3D")
  self.execute("IRFFT3D", [input, fft_length], Treal: treal, Tcomplex: tcomplex, name: name)
end
is_boosted_trees_ensemble_initialized(tree_ensemble_handle, name: "IsBoostedTreesEnsembleInitialized") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1838
def self.is_boosted_trees_ensemble_initialized(tree_ensemble_handle, name: "IsBoostedTreesEnsembleInitialized")
  self.execute("IsBoostedTreesEnsembleInitialized", [tree_ensemble_handle], name: name)
end
is_boosted_trees_quantile_stream_resource_initialized(quantile_stream_resource_handle, name: "IsBoostedTreesQuantileStreamResourceInitialized") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1842
def self.is_boosted_trees_quantile_stream_resource_initialized(quantile_stream_resource_handle, name: "IsBoostedTreesQuantileStreamResourceInitialized")
  self.execute("IsBoostedTreesQuantileStreamResourceInitialized", [quantile_stream_resource_handle], name: name)
end
is_finite(x, typeT: nil, name: "IsFinite") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1846
def self.is_finite(x, typeT: nil, name: "IsFinite")
  self.execute("IsFinite", [x], T: typeT, name: name)
end
is_inf(x, typeT: nil, name: "IsInf") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1850
def self.is_inf(x, typeT: nil, name: "IsInf")
  self.execute("IsInf", [x], T: typeT, name: name)
end
is_nan(x, typeT: nil, name: "IsNan") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1854
def self.is_nan(x, typeT: nil, name: "IsNan")
  self.execute("IsNan", [x], T: typeT, name: name)
end
is_variable_initialized(ref, dtype: nil, name: "IsVariableInitialized") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1858
def self.is_variable_initialized(ref, dtype: nil, name: "IsVariableInitialized")
  self.execute("IsVariableInitialized", [ref], dtype: dtype, name: name)
end
iterator(shared_name: "", container: "", output_types: nil, output_shapes: nil, name: "Iterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1862
def self.iterator(shared_name: "", container: "", output_types: nil, output_shapes: nil, name: "Iterator")
  self.execute("Iterator", [], shared_name: shared_name, container: container, output_types: output_types, output_shapes: output_shapes, name: name)
end
iterator_from_string_handle(string_handle, output_types: [], output_shapes: [], name: "IteratorFromStringHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1866
def self.iterator_from_string_handle(string_handle, output_types: [], output_shapes: [], name: "IteratorFromStringHandle")
  self.execute("IteratorFromStringHandle", [string_handle], output_types: output_types, output_shapes: output_shapes, name: name)
end
iterator_from_string_handle_v2(string_handle, output_types: [], output_shapes: [], name: "IteratorFromStringHandleV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1870
def self.iterator_from_string_handle_v2(string_handle, output_types: [], output_shapes: [], name: "IteratorFromStringHandleV2")
  self.execute("IteratorFromStringHandleV2", [string_handle], output_types: output_types, output_shapes: output_shapes, name: name)
end
iterator_get_device(resource, name: "IteratorGetDevice") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1874
def self.iterator_get_device(resource, name: "IteratorGetDevice")
  self.execute("IteratorGetDevice", [resource], name: name)
end
iterator_get_next(iterator, output_types: nil, output_shapes: nil, name: "IteratorGetNext") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1878
def self.iterator_get_next(iterator, output_types: nil, output_shapes: nil, name: "IteratorGetNext")
  self.execute("IteratorGetNext", [iterator], output_types: output_types, output_shapes: output_shapes, name: name)
end
iterator_get_next_as_optional(iterator, output_types: nil, output_shapes: nil, name: "IteratorGetNextAsOptional") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1882
def self.iterator_get_next_as_optional(iterator, output_types: nil, output_shapes: nil, name: "IteratorGetNextAsOptional")
  self.execute("IteratorGetNextAsOptional", [iterator], output_types: output_types, output_shapes: output_shapes, name: name)
end
iterator_get_next_sync(iterator, output_types: nil, output_shapes: nil, name: "IteratorGetNextSync") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1886
def self.iterator_get_next_sync(iterator, output_types: nil, output_shapes: nil, name: "IteratorGetNextSync")
  self.execute("IteratorGetNextSync", [iterator], output_types: output_types, output_shapes: output_shapes, name: name)
end
iterator_to_string_handle(resource_handle, name: "IteratorToStringHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1890
def self.iterator_to_string_handle(resource_handle, name: "IteratorToStringHandle")
  self.execute("IteratorToStringHandle", [resource_handle], name: name)
end
iterator_v2(shared_name: "", container: "", output_types: nil, output_shapes: nil, name: "IteratorV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1894
def self.iterator_v2(shared_name: "", container: "", output_types: nil, output_shapes: nil, name: "IteratorV2")
  self.execute("IteratorV2", [], shared_name: shared_name, container: container, output_types: output_types, output_shapes: output_shapes, name: name)
end
kmc2_chain_initialization(distances, seed, name: "KMC2ChainInitialization") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1898
def self.kmc2_chain_initialization(distances, seed, name: "KMC2ChainInitialization")
  self.execute("KMC2ChainInitialization", [distances, seed], name: name)
end
kmeans_plus_plus_initialization(points, num_to_sample, seed, num_retries_per_sample, name: "KmeansPlusPlusInitialization") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1902
def self.kmeans_plus_plus_initialization(points, num_to_sample, seed, num_retries_per_sample, name: "KmeansPlusPlusInitialization")
  self.execute("KmeansPlusPlusInitialization", [points, num_to_sample, seed, num_retries_per_sample], name: name)
end
l2_loss(t, typeT: nil, name: "L2Loss") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1906
def self.l2_loss(t, typeT: nil, name: "L2Loss")
  self.execute("L2Loss", [t], T: typeT, name: name)
end
latency_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "LatencyStatsDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1934
def self.latency_stats_dataset(input_dataset, tag, output_types: nil, output_shapes: nil, name: "LatencyStatsDataset")
  self.execute("LatencyStatsDataset", [input_dataset, tag], output_types: output_types, output_shapes: output_shapes, name: name)
end
leaky_relu(features, alpha: 0.20000000298023224, typeT: :float, name: "LeakyRelu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1938
def self.leaky_relu(features, alpha: 0.20000000298023224, typeT: :float, name: "LeakyRelu")
  self.execute("LeakyRelu", [features], alpha: alpha, T: typeT, name: name)
end
leaky_relu_grad(gradients, features, alpha: 0.20000000298023224, typeT: :float, name: "LeakyReluGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1942
def self.leaky_relu_grad(gradients, features, alpha: 0.20000000298023224, typeT: :float, name: "LeakyReluGrad")
  self.execute("LeakyReluGrad", [gradients, features], alpha: alpha, T: typeT, name: name)
end
learned_unigram_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "LearnedUnigramCandidateSampler") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1946
def self.learned_unigram_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "LearnedUnigramCandidateSampler")
  self.execute("LearnedUnigramCandidateSampler", [true_classes], num_true: num_true, num_sampled: num_sampled, unique: unique, range_max: range_max, seed: seed, seed2: seed2, name: name)
end
left_shift(x, y, typeT: nil, name: "LeftShift") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1950
def self.left_shift(x, y, typeT: nil, name: "LeftShift")
  self.execute("LeftShift", [x, y], T: typeT, name: name)
end
less(x, y, typeT: nil, name: "Less") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1954
def self.less(x, y, typeT: nil, name: "Less")
  self.execute("Less", [x, y], T: typeT, name: name)
end
less_equal(x, y, typeT: nil, name: "LessEqual") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1958
def self.less_equal(x, y, typeT: nil, name: "LessEqual")
  self.execute("LessEqual", [x, y], T: typeT, name: name)
end
lgamma(x, typeT: nil, name: "Lgamma") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1962
def self.lgamma(x, typeT: nil, name: "Lgamma")
  self.execute("Lgamma", [x], T: typeT, name: name)
end
lin_space(start, stop, num, typeT: nil, tidx: :int32, name: "LinSpace") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1966
def self.lin_space(start, stop, num, typeT: nil, tidx: :int32, name: "LinSpace")
  self.execute("LinSpace", [start, stop, num], T: typeT, Tidx: tidx, name: name)
end
list_diff(x, y, typeT: nil, out_idx: :int32, name: "ListDiff") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1970
def self.list_diff(x, y, typeT: nil, out_idx: :int32, name: "ListDiff")
  self.execute("ListDiff", [x, y], T: typeT, out_idx: out_idx, name: name)
end
lmdb_dataset(filenames, output_types: nil, output_shapes: nil, name: "LMDBDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1910
def self.lmdb_dataset(filenames, output_types: nil, output_shapes: nil, name: "LMDBDataset")
  self.execute("LMDBDataset", [filenames], output_types: output_types, output_shapes: output_shapes, name: name)
end
lmdb_reader(container: "", shared_name: "", name: "LMDBReader") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1914
def self.lmdb_reader(container: "", shared_name: "", name: "LMDBReader")
  self.execute("LMDBReader", [], container: container, shared_name: shared_name, name: name)
end
load_and_remap_matrix(ckpt_path, old_tensor_name, row_remapping, col_remapping, initializing_values, num_rows: nil, num_cols: nil, max_rows_in_memory: -1, name: "LoadAndRemapMatrix") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1974
def self.load_and_remap_matrix(ckpt_path, old_tensor_name, row_remapping, col_remapping, initializing_values, num_rows: nil, num_cols: nil, max_rows_in_memory: -1, name: "LoadAndRemapMatrix")
  self.execute("LoadAndRemapMatrix", [ckpt_path, old_tensor_name, row_remapping, col_remapping, initializing_values], num_rows: num_rows, num_cols: num_cols, max_rows_in_memory: max_rows_in_memory, name: name)
end
load_tpu_embedding_adadelta_parameters(parameters, accumulators, updates, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdadeltaParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1986
def self.load_tpu_embedding_adadelta_parameters(parameters, accumulators, updates, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdadeltaParameters")
  self.execute("LoadTPUEmbeddingAdadeltaParameters", [parameters, accumulators, updates], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_adadelta_parameters_grad_accum_debug(parameters, accumulators, updates, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdadeltaParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1990
def self.load_tpu_embedding_adadelta_parameters_grad_accum_debug(parameters, accumulators, updates, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdadeltaParametersGradAccumDebug")
  self.execute("LoadTPUEmbeddingAdadeltaParametersGradAccumDebug", [parameters, accumulators, updates, gradient_accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_adagrad_parameters(parameters, accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdagradParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1994
def self.load_tpu_embedding_adagrad_parameters(parameters, accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdagradParameters")
  self.execute("LoadTPUEmbeddingAdagradParameters", [parameters, accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_adagrad_parameters_grad_accum_debug(parameters, accumulators, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdagradParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1998
def self.load_tpu_embedding_adagrad_parameters_grad_accum_debug(parameters, accumulators, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingAdagradParametersGradAccumDebug")
  self.execute("LoadTPUEmbeddingAdagradParametersGradAccumDebug", [parameters, accumulators, gradient_accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_adam_parameters(parameters, momenta, velocities, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingADAMParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1978
def self.load_tpu_embedding_adam_parameters(parameters, momenta, velocities, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingADAMParameters")
  self.execute("LoadTPUEmbeddingADAMParameters", [parameters, momenta, velocities], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_adam_parameters_grad_accum_debug(parameters, momenta, velocities, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingADAMParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1982
def self.load_tpu_embedding_adam_parameters_grad_accum_debug(parameters, momenta, velocities, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingADAMParametersGradAccumDebug")
  self.execute("LoadTPUEmbeddingADAMParametersGradAccumDebug", [parameters, momenta, velocities, gradient_accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_centered_rms_prop_parameters(parameters, ms, mom, mg, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingCenteredRMSPropParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2002
def self.load_tpu_embedding_centered_rms_prop_parameters(parameters, ms, mom, mg, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingCenteredRMSPropParameters")
  self.execute("LoadTPUEmbeddingCenteredRMSPropParameters", [parameters, ms, mom, mg], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_ftrl_parameters(parameters, accumulators, linears, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingFTRLParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2006
def self.load_tpu_embedding_ftrl_parameters(parameters, accumulators, linears, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingFTRLParameters")
  self.execute("LoadTPUEmbeddingFTRLParameters", [parameters, accumulators, linears], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_ftrl_parameters_grad_accum_debug(parameters, accumulators, linears, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingFTRLParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2010
def self.load_tpu_embedding_ftrl_parameters_grad_accum_debug(parameters, accumulators, linears, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingFTRLParametersGradAccumDebug")
  self.execute("LoadTPUEmbeddingFTRLParametersGradAccumDebug", [parameters, accumulators, linears, gradient_accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_mdl_adagrad_light_parameters(parameters, accumulators, weights, benefits, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingMDLAdagradLightParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2014
def self.load_tpu_embedding_mdl_adagrad_light_parameters(parameters, accumulators, weights, benefits, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingMDLAdagradLightParameters")
  self.execute("LoadTPUEmbeddingMDLAdagradLightParameters", [parameters, accumulators, weights, benefits], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_momentum_parameters(parameters, momenta, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingMomentumParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2018
def self.load_tpu_embedding_momentum_parameters(parameters, momenta, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingMomentumParameters")
  self.execute("LoadTPUEmbeddingMomentumParameters", [parameters, momenta], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_momentum_parameters_grad_accum_debug(parameters, momenta, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingMomentumParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2022
def self.load_tpu_embedding_momentum_parameters_grad_accum_debug(parameters, momenta, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingMomentumParametersGradAccumDebug")
  self.execute("LoadTPUEmbeddingMomentumParametersGradAccumDebug", [parameters, momenta, gradient_accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_proximal_adagrad_parameters(parameters, accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingProximalAdagradParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2026
def self.load_tpu_embedding_proximal_adagrad_parameters(parameters, accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingProximalAdagradParameters")
  self.execute("LoadTPUEmbeddingProximalAdagradParameters", [parameters, accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_proximal_adagrad_parameters_grad_accum_debug(parameters, accumulators, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2030
def self.load_tpu_embedding_proximal_adagrad_parameters_grad_accum_debug(parameters, accumulators, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug")
  self.execute("LoadTPUEmbeddingProximalAdagradParametersGradAccumDebug", [parameters, accumulators, gradient_accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_rms_prop_parameters(parameters, ms, mom, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingRMSPropParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2034
def self.load_tpu_embedding_rms_prop_parameters(parameters, ms, mom, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingRMSPropParameters")
  self.execute("LoadTPUEmbeddingRMSPropParameters", [parameters, ms, mom], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_rms_prop_parameters_grad_accum_debug(parameters, ms, mom, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingRMSPropParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2038
def self.load_tpu_embedding_rms_prop_parameters_grad_accum_debug(parameters, ms, mom, gradient_accumulators, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingRMSPropParametersGradAccumDebug")
  self.execute("LoadTPUEmbeddingRMSPropParametersGradAccumDebug", [parameters, ms, mom, gradient_accumulators], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
load_tpu_embedding_stochastic_gradient_descent_parameters(parameters, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingStochasticGradientDescentParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2042
def self.load_tpu_embedding_stochastic_gradient_descent_parameters(parameters, table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "LoadTPUEmbeddingStochasticGradientDescentParameters")
  self.execute("LoadTPUEmbeddingStochasticGradientDescentParameters", [parameters], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
log(x, typeT: nil, name: "Log") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2046
def self.log(x, typeT: nil, name: "Log")
  self.execute("Log", [x], T: typeT, name: name)
end
log1p(x, typeT: nil, name: "Log1p") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2050
def self.log1p(x, typeT: nil, name: "Log1p")
  self.execute("Log1p", [x], T: typeT, name: name)
end
log_matrix_determinant(input, typeT: nil, name: "LogMatrixDeterminant") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2054
def self.log_matrix_determinant(input, typeT: nil, name: "LogMatrixDeterminant")
  self.execute("LogMatrixDeterminant", [input], T: typeT, name: name)
end
log_softmax(logits, typeT: nil, name: "LogSoftmax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2058
def self.log_softmax(logits, typeT: nil, name: "LogSoftmax")
  self.execute("LogSoftmax", [logits], T: typeT, name: name)
end
log_uniform_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "LogUniformCandidateSampler") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2062
def self.log_uniform_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "LogUniformCandidateSampler")
  self.execute("LogUniformCandidateSampler", [true_classes], num_true: num_true, num_sampled: num_sampled, unique: unique, range_max: range_max, seed: seed, seed2: seed2, name: name)
end
logical_and(x, y, name: "LogicalAnd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2066
def self.logical_and(x, y, name: "LogicalAnd")
  self.execute("LogicalAnd", [x, y], name: name)
end
logical_not(x, name: "LogicalNot") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2070
def self.logical_not(x, name: "LogicalNot")
  self.execute("LogicalNot", [x], name: name)
end
logical_or(x, y, name: "LogicalOr") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2074
def self.logical_or(x, y, name: "LogicalOr")
  self.execute("LogicalOr", [x, y], name: name)
end
lookup_table_export(table_handle, tkeys: nil, tvalues: nil, name: "LookupTableExport") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2078
def self.lookup_table_export(table_handle, tkeys: nil, tvalues: nil, name: "LookupTableExport")
  self.execute("LookupTableExport", [table_handle], Tkeys: tkeys, Tvalues: tvalues, name: name)
end
lookup_table_export_v2(table_handle, tkeys: nil, tvalues: nil, name: "LookupTableExportV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2082
def self.lookup_table_export_v2(table_handle, tkeys: nil, tvalues: nil, name: "LookupTableExportV2")
  self.execute("LookupTableExportV2", [table_handle], Tkeys: tkeys, Tvalues: tvalues, name: name)
end
lookup_table_find(table_handle, keys, default_value, tin: nil, tout: nil, name: "LookupTableFind") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2086
def self.lookup_table_find(table_handle, keys, default_value, tin: nil, tout: nil, name: "LookupTableFind")
  self.execute("LookupTableFind", [table_handle, keys, default_value], Tin: tin, Tout: tout, name: name)
end
lookup_table_find_v2(table_handle, keys, default_value, tin: nil, tout: nil, name: "LookupTableFindV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2090
def self.lookup_table_find_v2(table_handle, keys, default_value, tin: nil, tout: nil, name: "LookupTableFindV2")
  self.execute("LookupTableFindV2", [table_handle, keys, default_value], Tin: tin, Tout: tout, name: name)
end
lookup_table_import(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableImport") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2094
def self.lookup_table_import(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableImport")
  self.execute("LookupTableImport", [table_handle, keys, values], Tin: tin, Tout: tout, name: name)
end
lookup_table_import_v2(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableImportV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2098
def self.lookup_table_import_v2(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableImportV2")
  self.execute("LookupTableImportV2", [table_handle, keys, values], Tin: tin, Tout: tout, name: name)
end
lookup_table_insert(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableInsert") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2102
def self.lookup_table_insert(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableInsert")
  self.execute("LookupTableInsert", [table_handle, keys, values], Tin: tin, Tout: tout, name: name)
end
lookup_table_insert_v2(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableInsertV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2106
def self.lookup_table_insert_v2(table_handle, keys, values, tin: nil, tout: nil, name: "LookupTableInsertV2")
  self.execute("LookupTableInsertV2", [table_handle, keys, values], Tin: tin, Tout: tout, name: name)
end
lookup_table_remove_v2(table_handle, keys, tin: nil, name: "LookupTableRemoveV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2110
def self.lookup_table_remove_v2(table_handle, keys, tin: nil, name: "LookupTableRemoveV2")
  self.execute("LookupTableRemoveV2", [table_handle, keys], Tin: tin, name: name)
end
lookup_table_size(table_handle, name: "LookupTableSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2114
def self.lookup_table_size(table_handle, name: "LookupTableSize")
  self.execute("LookupTableSize", [table_handle], name: name)
end
lookup_table_size_v2(table_handle, name: "LookupTableSizeV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2118
def self.lookup_table_size_v2(table_handle, name: "LookupTableSizeV2")
  self.execute("LookupTableSizeV2", [table_handle], name: name)
end
loop_cond(input, name: "LoopCond") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2122
def self.loop_cond(input, name: "LoopCond")
  self.execute("LoopCond", [input], name: name)
end
lower_bound(sorted_inputs, values, typeT: nil, out_type: :int32, name: "LowerBound") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2126
def self.lower_bound(sorted_inputs, values, typeT: nil, out_type: :int32, name: "LowerBound")
  self.execute("LowerBound", [sorted_inputs, values], T: typeT, out_type: out_type, name: name)
end
lrn(input, depth_radius: 5, bias: 1.0, alpha: 1.0, beta: 0.5, typeT: :float, name: "LRN") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1918
def self.lrn(input, depth_radius: 5, bias: 1.0, alpha: 1.0, beta: 0.5, typeT: :float, name: "LRN")
  self.execute("LRN", [input], depth_radius: depth_radius, bias: bias, alpha: alpha, beta: beta, T: typeT, name: name)
end
lrn_grad(input_grads, input_image, output_image, depth_radius: 5, bias: 1.0, alpha: 1.0, beta: 0.5, typeT: :float, name: "LRNGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1922
def self.lrn_grad(input_grads, input_image, output_image, depth_radius: 5, bias: 1.0, alpha: 1.0, beta: 0.5, typeT: :float, name: "LRNGrad")
  self.execute("LRNGrad", [input_grads, input_image, output_image], depth_radius: depth_radius, bias: bias, alpha: alpha, beta: beta, T: typeT, name: name)
end
lstm_block_cell(x, cs_prev, h_prev, w, wci, wcf, wco, b, forget_bias: 1.0, cell_clip: 3.0, use_peephole: false, typeT: nil, name: "LSTMBlockCell") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1926
def self.lstm_block_cell(x, cs_prev, h_prev, w, wci, wcf, wco, b, forget_bias: 1.0, cell_clip: 3.0, use_peephole: false, typeT: nil, name: "LSTMBlockCell")
  self.execute("LSTMBlockCell", [x, cs_prev, h_prev, w, wci, wcf, wco, b], forget_bias: forget_bias, cell_clip: cell_clip, use_peephole: use_peephole, T: typeT, name: name)
end
lstm_block_cell_grad(x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, cs_grad, h_grad, use_peephole: nil, typeT: nil, name: "LSTMBlockCellGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 1930
def self.lstm_block_cell_grad(x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, cs_grad, h_grad, use_peephole: nil, typeT: nil, name: "LSTMBlockCellGrad")
  self.execute("LSTMBlockCellGrad", [x, cs_prev, h_prev, w, wci, wcf, wco, b, i, cs, f, o, ci, co, cs_grad, h_grad], use_peephole: use_peephole, T: typeT, name: name)
end
lu(input, typeT: nil, output_idx_type: :int32, name: "Lu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2130
def self.lu(input, typeT: nil, output_idx_type: :int32, name: "Lu")
  self.execute("Lu", [input], T: typeT, output_idx_type: output_idx_type, name: name)
end
make_iterator(dataset, iterator, name: "MakeIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2134
def self.make_iterator(dataset, iterator, name: "MakeIterator")
  self.execute("MakeIterator", [dataset, iterator], name: name)
end
map_and_batch_dataset(input_dataset, other_arguments, batch_size, num_parallel_calls, drop_remainder, f: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, name: "MapAndBatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2138
def self.map_and_batch_dataset(input_dataset, other_arguments, batch_size, num_parallel_calls, drop_remainder, f: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, name: "MapAndBatchDataset")
  self.execute("MapAndBatchDataset", [input_dataset, other_arguments, batch_size, num_parallel_calls, drop_remainder], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, preserve_cardinality: preserve_cardinality, name: name)
end
map_clear(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapClear") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2142
def self.map_clear(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapClear")
  self.execute("MapClear", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
map_dataset(input_dataset, other_arguments, f: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, preserve_cardinality: false, name: "MapDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2146
def self.map_dataset(input_dataset, other_arguments, f: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, preserve_cardinality: false, name: "MapDataset")
  self.execute("MapDataset", [input_dataset, other_arguments], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, use_inter_op_parallelism: use_inter_op_parallelism, preserve_cardinality: preserve_cardinality, name: name)
end
map_defun(arguments, captured_inputs, targuments: nil, tcaptured: [], output_types: nil, output_shapes: nil, f: nil, max_intra_op_parallelism: 1, name: "MapDefun") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2150
def self.map_defun(arguments, captured_inputs, targuments: nil, tcaptured: [], output_types: nil, output_shapes: nil, f: nil, max_intra_op_parallelism: 1, name: "MapDefun")
  self.execute("MapDefun", [arguments, captured_inputs], Targuments: targuments, Tcaptured: tcaptured, output_types: output_types, output_shapes: output_shapes, f: f, max_intra_op_parallelism: max_intra_op_parallelism, name: name)
end
map_incomplete_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapIncompleteSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2154
def self.map_incomplete_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapIncompleteSize")
  self.execute("MapIncompleteSize", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
map_peek(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapPeek") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2158
def self.map_peek(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapPeek")
  self.execute("MapPeek", [key, indices], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
map_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2162
def self.map_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapSize")
  self.execute("MapSize", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
map_stage(key, indices, values, capacity: 0, memory_limit: 0, dtypes: nil, fake_dtypes: nil, container: "", shared_name: "", name: "MapStage") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2166
def self.map_stage(key, indices, values, capacity: 0, memory_limit: 0, dtypes: nil, fake_dtypes: nil, container: "", shared_name: "", name: "MapStage")
  self.execute("MapStage", [key, indices, values], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, fake_dtypes: fake_dtypes, container: container, shared_name: shared_name, name: name)
end
map_unstage(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapUnstage") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2170
def self.map_unstage(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapUnstage")
  self.execute("MapUnstage", [key, indices], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
map_unstage_no_key(indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapUnstageNoKey") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2174
def self.map_unstage_no_key(indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "MapUnstageNoKey")
  self.execute("MapUnstageNoKey", [indices], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
mat_mul(a, b, transpose_a: false, transpose_b: false, typeT: nil, name: "MatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2178
def self.mat_mul(a, b, transpose_a: false, transpose_b: false, typeT: nil, name: "MatMul")
  self.execute("MatMul", [a, b], transpose_a: transpose_a, transpose_b: transpose_b, T: typeT, name: name)
end
matching_files(pattern, name: "MatchingFiles") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2182
def self.matching_files(pattern, name: "MatchingFiles")
  self.execute("MatchingFiles", [pattern], name: name)
end
matching_files_dataset(patterns, name: "MatchingFilesDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2186
def self.matching_files_dataset(patterns, name: "MatchingFilesDataset")
  self.execute("MatchingFilesDataset", [patterns], name: name)
end
matrix_band_part(input, num_lower, num_upper, typeT: nil, tindex: :int64, name: "MatrixBandPart") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2190
def self.matrix_band_part(input, num_lower, num_upper, typeT: nil, tindex: :int64, name: "MatrixBandPart")
  self.execute("MatrixBandPart", [input, num_lower, num_upper], T: typeT, Tindex: tindex, name: name)
end
matrix_determinant(input, typeT: nil, name: "MatrixDeterminant") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2194
def self.matrix_determinant(input, typeT: nil, name: "MatrixDeterminant")
  self.execute("MatrixDeterminant", [input], T: typeT, name: name)
end
matrix_diag(diagonal, typeT: nil, name: "MatrixDiag") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2198
def self.matrix_diag(diagonal, typeT: nil, name: "MatrixDiag")
  self.execute("MatrixDiag", [diagonal], T: typeT, name: name)
end
matrix_diag_part(input, typeT: nil, name: "MatrixDiagPart") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2202
def self.matrix_diag_part(input, typeT: nil, name: "MatrixDiagPart")
  self.execute("MatrixDiagPart", [input], T: typeT, name: name)
end
matrix_diag_part_v2(input, k, padding_value, typeT: nil, name: "MatrixDiagPartV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2206
def self.matrix_diag_part_v2(input, k, padding_value, typeT: nil, name: "MatrixDiagPartV2")
  self.execute("MatrixDiagPartV2", [input, k, padding_value], T: typeT, name: name)
end
matrix_diag_v2(diagonal, k, num_rows, num_cols, padding_value, typeT: nil, name: "MatrixDiagV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2210
def self.matrix_diag_v2(diagonal, k, num_rows, num_cols, padding_value, typeT: nil, name: "MatrixDiagV2")
  self.execute("MatrixDiagV2", [diagonal, k, num_rows, num_cols, padding_value], T: typeT, name: name)
end
matrix_exponential(input, typeT: nil, name: "MatrixExponential") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2214
def self.matrix_exponential(input, typeT: nil, name: "MatrixExponential")
  self.execute("MatrixExponential", [input], T: typeT, name: name)
end
matrix_inverse(input, adjoint: false, typeT: nil, name: "MatrixInverse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2218
def self.matrix_inverse(input, adjoint: false, typeT: nil, name: "MatrixInverse")
  self.execute("MatrixInverse", [input], adjoint: adjoint, T: typeT, name: name)
end
matrix_logarithm(input, typeT: nil, name: "MatrixLogarithm") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2222
def self.matrix_logarithm(input, typeT: nil, name: "MatrixLogarithm")
  self.execute("MatrixLogarithm", [input], T: typeT, name: name)
end
matrix_set_diag(input, diagonal, typeT: nil, name: "MatrixSetDiag") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2226
def self.matrix_set_diag(input, diagonal, typeT: nil, name: "MatrixSetDiag")
  self.execute("MatrixSetDiag", [input, diagonal], T: typeT, name: name)
end
matrix_set_diag_v2(input, diagonal, k, typeT: nil, name: "MatrixSetDiagV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2230
def self.matrix_set_diag_v2(input, diagonal, k, typeT: nil, name: "MatrixSetDiagV2")
  self.execute("MatrixSetDiagV2", [input, diagonal, k], T: typeT, name: name)
end
matrix_solve(matrix, rhs, adjoint: false, typeT: nil, name: "MatrixSolve") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2234
def self.matrix_solve(matrix, rhs, adjoint: false, typeT: nil, name: "MatrixSolve")
  self.execute("MatrixSolve", [matrix, rhs], adjoint: adjoint, T: typeT, name: name)
end
matrix_solve_ls(matrix, rhs, l2_regularizer, typeT: nil, fast: true, name: "MatrixSolveLs") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2238
def self.matrix_solve_ls(matrix, rhs, l2_regularizer, typeT: nil, fast: true, name: "MatrixSolveLs")
  self.execute("MatrixSolveLs", [matrix, rhs, l2_regularizer], T: typeT, fast: fast, name: name)
end
matrix_square_root(input, typeT: nil, name: "MatrixSquareRoot") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2242
def self.matrix_square_root(input, typeT: nil, name: "MatrixSquareRoot")
  self.execute("MatrixSquareRoot", [input], T: typeT, name: name)
end
matrix_triangular_solve(matrix, rhs, lower: true, adjoint: false, typeT: nil, name: "MatrixTriangularSolve") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2246
def self.matrix_triangular_solve(matrix, rhs, lower: true, adjoint: false, typeT: nil, name: "MatrixTriangularSolve")
  self.execute("MatrixTriangularSolve", [matrix, rhs], lower: lower, adjoint: adjoint, T: typeT, name: name)
end
max(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Max") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2250
def self.max(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Max")
  self.execute("Max", [input, reduction_indices], keep_dims: keep_dims, T: typeT, Tidx: tidx, name: name)
end
max_intra_op_parallelism_dataset(input_dataset, max_intra_op_parallelism, output_types: nil, output_shapes: nil, name: "MaxIntraOpParallelismDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2254
def self.max_intra_op_parallelism_dataset(input_dataset, max_intra_op_parallelism, output_types: nil, output_shapes: nil, name: "MaxIntraOpParallelismDataset")
  self.execute("MaxIntraOpParallelismDataset", [input_dataset, max_intra_op_parallelism], output_types: output_types, output_shapes: output_shapes, name: name)
end
max_pool(input, typeT: :float, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", name: "MaxPool") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2258
def self.max_pool(input, typeT: :float, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", name: "MaxPool")
  self.execute("MaxPool", [input], T: typeT, ksize: ksize, strides: strides, padding: padding, data_format: data_format, name: name)
end
max_pool3_d(input, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "MaxPool3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2262
def self.max_pool3_d(input, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "MaxPool3D")
  self.execute("MaxPool3D", [input], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
max_pool3_d_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: :float, tinput: :float, name: "MaxPool3DGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2266
def self.max_pool3_d_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: :float, tinput: :float, name: "MaxPool3DGrad")
  self.execute("MaxPool3DGrad", [orig_input, orig_output, grad], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, TInput: tinput, name: name)
end
max_pool3_d_grad_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "MaxPool3DGradGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2270
def self.max_pool3_d_grad_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NDHWC", typeT: nil, name: "MaxPool3DGradGrad")
  self.execute("MaxPool3DGradGrad", [orig_input, orig_output, grad], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
max_pool_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: :float, name: "MaxPoolGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2274
def self.max_pool_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: :float, name: "MaxPoolGrad")
  self.execute("MaxPoolGrad", [orig_input, orig_output, grad], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
max_pool_grad_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: nil, name: "MaxPoolGradGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2278
def self.max_pool_grad_grad(orig_input, orig_output, grad, ksize: nil, strides: nil, padding: nil, data_format: "NHWC", typeT: nil, name: "MaxPoolGradGrad")
  self.execute("MaxPoolGradGrad", [orig_input, orig_output, grad], ksize: ksize, strides: strides, padding: padding, data_format: data_format, T: typeT, name: name)
end
max_pool_grad_grad_v2(orig_input, orig_output, grad, ksize, strides, padding: nil, data_format: "NHWC", typeT: nil, name: "MaxPoolGradGradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2282
def self.max_pool_grad_grad_v2(orig_input, orig_output, grad, ksize, strides, padding: nil, data_format: "NHWC", typeT: nil, name: "MaxPoolGradGradV2")
  self.execute("MaxPoolGradGradV2", [orig_input, orig_output, grad, ksize, strides], padding: padding, data_format: data_format, T: typeT, name: name)
end
max_pool_grad_grad_with_argmax(input, grad, argmax, ksize: nil, strides: nil, padding: nil, include_batch_in_index: false, targmax: nil, typeT: nil, name: "MaxPoolGradGradWithArgmax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2286
def self.max_pool_grad_grad_with_argmax(input, grad, argmax, ksize: nil, strides: nil, padding: nil, include_batch_in_index: false, targmax: nil, typeT: nil, name: "MaxPoolGradGradWithArgmax")
  self.execute("MaxPoolGradGradWithArgmax", [input, grad, argmax], ksize: ksize, strides: strides, padding: padding, include_batch_in_index: include_batch_in_index, Targmax: targmax, T: typeT, name: name)
end
max_pool_grad_v2(orig_input, orig_output, grad, ksize, strides, padding: nil, data_format: "NHWC", typeT: :float, name: "MaxPoolGradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2290
def self.max_pool_grad_v2(orig_input, orig_output, grad, ksize, strides, padding: nil, data_format: "NHWC", typeT: :float, name: "MaxPoolGradV2")
  self.execute("MaxPoolGradV2", [orig_input, orig_output, grad, ksize, strides], padding: padding, data_format: data_format, T: typeT, name: name)
end
max_pool_grad_with_argmax(input, grad, argmax, ksize: nil, strides: nil, padding: nil, include_batch_in_index: false, targmax: nil, typeT: nil, name: "MaxPoolGradWithArgmax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2294
def self.max_pool_grad_with_argmax(input, grad, argmax, ksize: nil, strides: nil, padding: nil, include_batch_in_index: false, targmax: nil, typeT: nil, name: "MaxPoolGradWithArgmax")
  self.execute("MaxPoolGradWithArgmax", [input, grad, argmax], ksize: ksize, strides: strides, padding: padding, include_batch_in_index: include_batch_in_index, Targmax: targmax, T: typeT, name: name)
end
max_pool_v2(input, ksize, strides, typeT: :float, padding: nil, data_format: "NHWC", name: "MaxPoolV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2298
def self.max_pool_v2(input, ksize, strides, typeT: :float, padding: nil, data_format: "NHWC", name: "MaxPoolV2")
  self.execute("MaxPoolV2", [input, ksize, strides], T: typeT, padding: padding, data_format: data_format, name: name)
end
max_pool_with_argmax(input, ksize: nil, strides: nil, targmax: :int64, padding: nil, include_batch_in_index: false, typeT: nil, name: "MaxPoolWithArgmax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2302
def self.max_pool_with_argmax(input, ksize: nil, strides: nil, targmax: :int64, padding: nil, include_batch_in_index: false, typeT: nil, name: "MaxPoolWithArgmax")
  self.execute("MaxPoolWithArgmax", [input], ksize: ksize, strides: strides, Targmax: targmax, padding: padding, include_batch_in_index: include_batch_in_index, T: typeT, name: name)
end
maximum(x, y, typeT: nil, name: "Maximum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2306
def self.maximum(x, y, typeT: nil, name: "Maximum")
  self.execute("Maximum", [x, y], T: typeT, name: name)
end
mean(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Mean") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2310
def self.mean(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Mean")
  self.execute("Mean", [input, reduction_indices], keep_dims: keep_dims, T: typeT, Tidx: tidx, name: name)
end
merge(inputs, typeT: nil, n: nil, name: "Merge") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2314
def self.merge(inputs, typeT: nil, n: nil, name: "Merge")
  self.execute("Merge", [inputs], T: typeT, N: n, name: name)
end
merge_summary(inputs, n: nil, name: "MergeSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2318
def self.merge_summary(inputs, n: nil, name: "MergeSummary")
  self.execute("MergeSummary", [inputs], N: n, name: name)
end
merge_v2_checkpoints(checkpoint_prefixes, destination_prefix, delete_old_dirs: true, name: "MergeV2Checkpoints") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2322
def self.merge_v2_checkpoints(checkpoint_prefixes, destination_prefix, delete_old_dirs: true, name: "MergeV2Checkpoints")
  self.execute("MergeV2Checkpoints", [checkpoint_prefixes, destination_prefix], delete_old_dirs: delete_old_dirs, name: name)
end
mfcc(spectrogram, sample_rate, upper_frequency_limit: 4000.0, lower_frequency_limit: 20.0, filterbank_channel_count: 40, dct_coefficient_count: 13, name: "Mfcc") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2326
def self.mfcc(spectrogram, sample_rate, upper_frequency_limit: 4000.0, lower_frequency_limit: 20.0, filterbank_channel_count: 40, dct_coefficient_count: 13, name: "Mfcc")
  self.execute("Mfcc", [spectrogram, sample_rate], upper_frequency_limit: upper_frequency_limit, lower_frequency_limit: lower_frequency_limit, filterbank_channel_count: filterbank_channel_count, dct_coefficient_count: dct_coefficient_count, name: name)
end
min(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Min") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2330
def self.min(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Min")
  self.execute("Min", [input, reduction_indices], keep_dims: keep_dims, T: typeT, Tidx: tidx, name: name)
end
minimum(x, y, typeT: nil, name: "Minimum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2334
def self.minimum(x, y, typeT: nil, name: "Minimum")
  self.execute("Minimum", [x, y], T: typeT, name: name)
end
mirror_pad(input, paddings, typeT: nil, tpaddings: :int32, mode: nil, name: "MirrorPad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2338
def self.mirror_pad(input, paddings, typeT: nil, tpaddings: :int32, mode: nil, name: "MirrorPad")
  self.execute("MirrorPad", [input, paddings], T: typeT, Tpaddings: tpaddings, mode: mode, name: name)
end
mirror_pad_grad(input, paddings, typeT: nil, tpaddings: :int32, mode: nil, name: "MirrorPadGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2342
def self.mirror_pad_grad(input, paddings, typeT: nil, tpaddings: :int32, mode: nil, name: "MirrorPadGrad")
  self.execute("MirrorPadGrad", [input, paddings], T: typeT, Tpaddings: tpaddings, mode: mode, name: name)
end
mlir_passthrough_op(inputs, mlir_module: "", tinputs: nil, toutputs: nil, name: "MlirPassthroughOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2346
def self.mlir_passthrough_op(inputs, mlir_module: "", tinputs: nil, toutputs: nil, name: "MlirPassthroughOp")
  self.execute("MlirPassthroughOp", [inputs], mlir_module: mlir_module, Tinputs: tinputs, Toutputs: toutputs, name: name)
end
mod(x, y, typeT: nil, name: "Mod") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2350
def self.mod(x, y, typeT: nil, name: "Mod")
  self.execute("Mod", [x, y], T: typeT, name: name)
end
model_dataset(input_dataset, algorithm: 0, cpu_budget: 0, output_types: nil, output_shapes: nil, name: "ModelDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2354
def self.model_dataset(input_dataset, algorithm: 0, cpu_budget: 0, output_types: nil, output_shapes: nil, name: "ModelDataset")
  self.execute("ModelDataset", [input_dataset], algorithm: algorithm, cpu_budget: cpu_budget, output_types: output_types, output_shapes: output_shapes, name: name)
end
mul(x, y, typeT: nil, name: "Mul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2358
def self.mul(x, y, typeT: nil, name: "Mul")
  self.execute("Mul", [x, y], T: typeT, name: name)
end
mul_no_nan(x, y, typeT: nil, name: "MulNoNan") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2362
def self.mul_no_nan(x, y, typeT: nil, name: "MulNoNan")
  self.execute("MulNoNan", [x, y], T: typeT, name: name)
end
multi_device_iterator(devices: nil, shared_name: "", container: "", output_types: nil, output_shapes: nil, name: "MultiDeviceIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2366
def self.multi_device_iterator(devices: nil, shared_name: "", container: "", output_types: nil, output_shapes: nil, name: "MultiDeviceIterator")
  self.execute("MultiDeviceIterator", [], devices: devices, shared_name: shared_name, container: container, output_types: output_types, output_shapes: output_shapes, name: name)
end
multi_device_iterator_from_string_handle(string_handle, output_types: [], output_shapes: [], name: "MultiDeviceIteratorFromStringHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2370
def self.multi_device_iterator_from_string_handle(string_handle, output_types: [], output_shapes: [], name: "MultiDeviceIteratorFromStringHandle")
  self.execute("MultiDeviceIteratorFromStringHandle", [string_handle], output_types: output_types, output_shapes: output_shapes, name: name)
end
multi_device_iterator_get_next_from_shard(multi_device_iterator, shard_num, incarnation_id, output_types: nil, output_shapes: nil, name: "MultiDeviceIteratorGetNextFromShard") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2374
def self.multi_device_iterator_get_next_from_shard(multi_device_iterator, shard_num, incarnation_id, output_types: nil, output_shapes: nil, name: "MultiDeviceIteratorGetNextFromShard")
  self.execute("MultiDeviceIteratorGetNextFromShard", [multi_device_iterator, shard_num, incarnation_id], output_types: output_types, output_shapes: output_shapes, name: name)
end
multi_device_iterator_init(dataset, multi_device_iterator, max_buffer_size, name: "MultiDeviceIteratorInit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2378
def self.multi_device_iterator_init(dataset, multi_device_iterator, max_buffer_size, name: "MultiDeviceIteratorInit")
  self.execute("MultiDeviceIteratorInit", [dataset, multi_device_iterator, max_buffer_size], name: name)
end
multi_device_iterator_to_string_handle(multi_device_iterator, name: "MultiDeviceIteratorToStringHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2382
def self.multi_device_iterator_to_string_handle(multi_device_iterator, name: "MultiDeviceIteratorToStringHandle")
  self.execute("MultiDeviceIteratorToStringHandle", [multi_device_iterator], name: name)
end
multinomial(logits, num_samples, seed: 0, seed2: 0, typeT: nil, output_dtype: :int64, name: "Multinomial") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2386
def self.multinomial(logits, num_samples, seed: 0, seed2: 0, typeT: nil, output_dtype: :int64, name: "Multinomial")
  self.execute("Multinomial", [logits, num_samples], seed: seed, seed2: seed2, T: typeT, output_dtype: output_dtype, name: name)
end
mutable_dense_hash_table(empty_key, container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], initial_num_buckets: 131072, max_load_factor: 0.800000011920929, name: "MutableDenseHashTable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2390
def self.mutable_dense_hash_table(empty_key, container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], initial_num_buckets: 131072, max_load_factor: 0.800000011920929, name: "MutableDenseHashTable")
  self.execute("MutableDenseHashTable", [empty_key], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, value_shape: value_shape, initial_num_buckets: initial_num_buckets, max_load_factor: max_load_factor, name: name)
end
mutable_dense_hash_table_v2(empty_key, deleted_key, container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], initial_num_buckets: 131072, max_load_factor: 0.800000011920929, name: "MutableDenseHashTableV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2394
def self.mutable_dense_hash_table_v2(empty_key, deleted_key, container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], initial_num_buckets: 131072, max_load_factor: 0.800000011920929, name: "MutableDenseHashTableV2")
  self.execute("MutableDenseHashTableV2", [empty_key, deleted_key], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, value_shape: value_shape, initial_num_buckets: initial_num_buckets, max_load_factor: max_load_factor, name: name)
end
mutable_hash_table(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "MutableHashTable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2398
def self.mutable_hash_table(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "MutableHashTable")
  self.execute("MutableHashTable", [], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, name: name)
end
mutable_hash_table_of_tensors(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], name: "MutableHashTableOfTensors") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2402
def self.mutable_hash_table_of_tensors(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], name: "MutableHashTableOfTensors")
  self.execute("MutableHashTableOfTensors", [], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, value_shape: value_shape, name: name)
end
mutable_hash_table_of_tensors_v2(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], name: "MutableHashTableOfTensorsV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2406
def self.mutable_hash_table_of_tensors_v2(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, value_shape: [], name: "MutableHashTableOfTensorsV2")
  self.execute("MutableHashTableOfTensorsV2", [], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, value_shape: value_shape, name: name)
end
mutable_hash_table_v2(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "MutableHashTableV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2410
def self.mutable_hash_table_v2(container: "", shared_name: "", use_node_name_sharing: false, key_dtype: nil, value_dtype: nil, name: "MutableHashTableV2")
  self.execute("MutableHashTableV2", [], container: container, shared_name: shared_name, use_node_name_sharing: use_node_name_sharing, key_dtype: key_dtype, value_dtype: value_dtype, name: name)
end
mutex_lock(mutex, name: "MutexLock") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2414
def self.mutex_lock(mutex, name: "MutexLock")
  self.execute("MutexLock", [mutex], name: name)
end
mutex_v2(container: "", shared_name: "", name: "MutexV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2418
def self.mutex_v2(container: "", shared_name: "", name: "MutexV2")
  self.execute("MutexV2", [], container: container, shared_name: shared_name, name: name)
end
nccl_all_reduce(input, reduction: nil, typeT: nil, num_devices: nil, shared_name: "", name: "NcclAllReduce") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2422
def self.nccl_all_reduce(input, reduction: nil, typeT: nil, num_devices: nil, shared_name: "", name: "NcclAllReduce")
  self.execute("NcclAllReduce", [input], reduction: reduction, T: typeT, num_devices: num_devices, shared_name: shared_name, name: name)
end
nccl_broadcast(input, typeT: nil, shape: nil, name: "NcclBroadcast") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2426
def self.nccl_broadcast(input, typeT: nil, shape: nil, name: "NcclBroadcast")
  self.execute("NcclBroadcast", [input], T: typeT, shape: shape, name: name)
end
nccl_reduce(input, reduction: nil, typeT: nil, num_devices: nil, name: "NcclReduce") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2430
def self.nccl_reduce(input, reduction: nil, typeT: nil, num_devices: nil, name: "NcclReduce")
  self.execute("NcclReduce", [input], reduction: reduction, T: typeT, num_devices: num_devices, name: name)
end
ndtri(x, typeT: nil, name: "Ndtri") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2434
def self.ndtri(x, typeT: nil, name: "Ndtri")
  self.execute("Ndtri", [x], T: typeT, name: name)
end
nearest_neighbors(points, centers, k, name: "NearestNeighbors") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2438
def self.nearest_neighbors(points, centers, k, name: "NearestNeighbors")
  self.execute("NearestNeighbors", [points, centers, k], name: name)
end
neg(x, typeT: nil, name: "Neg") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2442
def self.neg(x, typeT: nil, name: "Neg")
  self.execute("Neg", [x], T: typeT, name: name)
end
neg_train(w_in, w_out, examples, labels, lr, vocab_count: nil, num_negative_samples: nil, name: "NegTrain") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2446
def self.neg_train(w_in, w_out, examples, labels, lr, vocab_count: nil, num_negative_samples: nil, name: "NegTrain")
  self.execute("NegTrain", [w_in, w_out, examples, labels, lr], vocab_count: vocab_count, num_negative_samples: num_negative_samples, name: name)
end
next_after(x1, x2, typeT: :float, name: "NextAfter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2450
def self.next_after(x1, x2, typeT: :float, name: "NextAfter")
  self.execute("NextAfter", [x1, x2], T: typeT, name: name)
end
next_iteration(data, typeT: nil, name: "NextIteration") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2454
def self.next_iteration(data, typeT: nil, name: "NextIteration")
  self.execute("NextIteration", [data], T: typeT, name: name)
end
no_op(name: "NoOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2458
def self.no_op(name: "NoOp")
  self.execute("NoOp", [], name: name)
end
non_deterministic_ints(shape, dtype: :int64, shape_dtype: :int64, name: "NonDeterministicInts") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2462
def self.non_deterministic_ints(shape, dtype: :int64, shape_dtype: :int64, name: "NonDeterministicInts")
  self.execute("NonDeterministicInts", [shape], dtype: dtype, shape_dtype: shape_dtype, name: name)
end
non_max_suppression(boxes, scores, max_output_size, iou_threshold: 0.5, name: "NonMaxSuppression") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2466
def self.non_max_suppression(boxes, scores, max_output_size, iou_threshold: 0.5, name: "NonMaxSuppression")
  self.execute("NonMaxSuppression", [boxes, scores, max_output_size], iou_threshold: iou_threshold, name: name)
end
non_max_suppression_v2(boxes, scores, max_output_size, iou_threshold, typeT: :float, t_threshold: :float, name: "NonMaxSuppressionV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2470
def self.non_max_suppression_v2(boxes, scores, max_output_size, iou_threshold, typeT: :float, t_threshold: :float, name: "NonMaxSuppressionV2")
  self.execute("NonMaxSuppressionV2", [boxes, scores, max_output_size, iou_threshold], T: typeT, T_threshold: t_threshold, name: name)
end
non_max_suppression_v3(boxes, scores, max_output_size, iou_threshold, score_threshold, typeT: :float, t_threshold: :float, name: "NonMaxSuppressionV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2474
def self.non_max_suppression_v3(boxes, scores, max_output_size, iou_threshold, score_threshold, typeT: :float, t_threshold: :float, name: "NonMaxSuppressionV3")
  self.execute("NonMaxSuppressionV3", [boxes, scores, max_output_size, iou_threshold, score_threshold], T: typeT, T_threshold: t_threshold, name: name)
end
non_max_suppression_v4(boxes, scores, max_output_size, iou_threshold, score_threshold, typeT: :float, t_threshold: :float, pad_to_max_output_size: false, name: "NonMaxSuppressionV4") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2478
def self.non_max_suppression_v4(boxes, scores, max_output_size, iou_threshold, score_threshold, typeT: :float, t_threshold: :float, pad_to_max_output_size: false, name: "NonMaxSuppressionV4")
  self.execute("NonMaxSuppressionV4", [boxes, scores, max_output_size, iou_threshold, score_threshold], T: typeT, T_threshold: t_threshold, pad_to_max_output_size: pad_to_max_output_size, name: name)
end
non_max_suppression_v5(boxes, scores, max_output_size, iou_threshold, score_threshold, soft_nms_sigma, typeT: :float, pad_to_max_output_size: false, name: "NonMaxSuppressionV5") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2482
def self.non_max_suppression_v5(boxes, scores, max_output_size, iou_threshold, score_threshold, soft_nms_sigma, typeT: :float, pad_to_max_output_size: false, name: "NonMaxSuppressionV5")
  self.execute("NonMaxSuppressionV5", [boxes, scores, max_output_size, iou_threshold, score_threshold, soft_nms_sigma], T: typeT, pad_to_max_output_size: pad_to_max_output_size, name: name)
end
non_max_suppression_with_overlaps(overlaps, scores, max_output_size, overlap_threshold, score_threshold, name: "NonMaxSuppressionWithOverlaps") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2486
def self.non_max_suppression_with_overlaps(overlaps, scores, max_output_size, overlap_threshold, score_threshold, name: "NonMaxSuppressionWithOverlaps")
  self.execute("NonMaxSuppressionWithOverlaps", [overlaps, scores, max_output_size, overlap_threshold, score_threshold], name: name)
end
non_serializable_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "NonSerializableDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2490
def self.non_serializable_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "NonSerializableDataset")
  self.execute("NonSerializableDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
not_equal(x, y, typeT: nil, incompatible_shape_error: true, name: "NotEqual") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2494
def self.not_equal(x, y, typeT: nil, incompatible_shape_error: true, name: "NotEqual")
  self.execute("NotEqual", [x, y], T: typeT, incompatible_shape_error: incompatible_shape_error, name: name)
end
nth_element(input, n, reverse: false, typeT: nil, name: "NthElement") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2498
def self.nth_element(input, n, reverse: false, typeT: nil, name: "NthElement")
  self.execute("NthElement", [input, n], reverse: reverse, T: typeT, name: name)
end
one_hot(indices, depth, on_value, off_value, axis: -1, typeT: nil, ti: :int64, name: "OneHot") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2502
def self.one_hot(indices, depth, on_value, off_value, axis: -1, typeT: nil, ti: :int64, name: "OneHot")
  self.execute("OneHot", [indices, depth, on_value, off_value], axis: axis, T: typeT, TI: ti, name: name)
end
one_shot_iterator(dataset_factory: nil, output_types: nil, output_shapes: nil, container: "", shared_name: "", name: "OneShotIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2506
def self.one_shot_iterator(dataset_factory: nil, output_types: nil, output_shapes: nil, container: "", shared_name: "", name: "OneShotIterator")
  self.execute("OneShotIterator", [], dataset_factory: dataset_factory, output_types: output_types, output_shapes: output_shapes, container: container, shared_name: shared_name, name: name)
end
ones_like(x, typeT: nil, name: "OnesLike") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2510
def self.ones_like(x, typeT: nil, name: "OnesLike")
  self.execute("OnesLike", [x], T: typeT, name: name)
end
optimize_dataset(input_dataset, optimizations, output_types: nil, output_shapes: nil, optimization_configs: [], name: "OptimizeDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2514
def self.optimize_dataset(input_dataset, optimizations, output_types: nil, output_shapes: nil, optimization_configs: [], name: "OptimizeDataset")
  self.execute("OptimizeDataset", [input_dataset, optimizations], output_types: output_types, output_shapes: output_shapes, optimization_configs: optimization_configs, name: name)
end
optional_from_value(components, toutput_types: nil, name: "OptionalFromValue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2518
def self.optional_from_value(components, toutput_types: nil, name: "OptionalFromValue")
  self.execute("OptionalFromValue", [components], Toutput_types: toutput_types, name: name)
end
optional_get_value(optional, output_types: nil, output_shapes: nil, name: "OptionalGetValue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2522
def self.optional_get_value(optional, output_types: nil, output_shapes: nil, name: "OptionalGetValue")
  self.execute("OptionalGetValue", [optional], output_types: output_types, output_shapes: output_shapes, name: name)
end
optional_has_value(optional, name: "OptionalHasValue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2526
def self.optional_has_value(optional, name: "OptionalHasValue")
  self.execute("OptionalHasValue", [optional], name: name)
end
optional_none(name: "OptionalNone") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2530
def self.optional_none(name: "OptionalNone")
  self.execute("OptionalNone", [], name: name)
end
ordered_map_clear(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapClear") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2534
def self.ordered_map_clear(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapClear")
  self.execute("OrderedMapClear", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
ordered_map_incomplete_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapIncompleteSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2538
def self.ordered_map_incomplete_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapIncompleteSize")
  self.execute("OrderedMapIncompleteSize", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
ordered_map_peek(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapPeek") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2542
def self.ordered_map_peek(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapPeek")
  self.execute("OrderedMapPeek", [key, indices], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
ordered_map_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2546
def self.ordered_map_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapSize")
  self.execute("OrderedMapSize", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
ordered_map_stage(key, indices, values, capacity: 0, memory_limit: 0, dtypes: nil, fake_dtypes: nil, container: "", shared_name: "", name: "OrderedMapStage") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2550
def self.ordered_map_stage(key, indices, values, capacity: 0, memory_limit: 0, dtypes: nil, fake_dtypes: nil, container: "", shared_name: "", name: "OrderedMapStage")
  self.execute("OrderedMapStage", [key, indices, values], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, fake_dtypes: fake_dtypes, container: container, shared_name: shared_name, name: name)
end
ordered_map_unstage(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapUnstage") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2554
def self.ordered_map_unstage(key, indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapUnstage")
  self.execute("OrderedMapUnstage", [key, indices], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
ordered_map_unstage_no_key(indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapUnstageNoKey") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2558
def self.ordered_map_unstage_no_key(indices, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "OrderedMapUnstageNoKey")
  self.execute("OrderedMapUnstageNoKey", [indices], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
outfeed_dequeue(dtype: nil, shape: nil, device_ordinal: -1, name: "OutfeedDequeue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2562
def self.outfeed_dequeue(dtype: nil, shape: nil, device_ordinal: -1, name: "OutfeedDequeue")
  self.execute("OutfeedDequeue", [], dtype: dtype, shape: shape, device_ordinal: device_ordinal, name: name)
end
outfeed_dequeue_tuple(dtypes: nil, shapes: nil, device_ordinal: -1, name: "OutfeedDequeueTuple") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2566
def self.outfeed_dequeue_tuple(dtypes: nil, shapes: nil, device_ordinal: -1, name: "OutfeedDequeueTuple")
  self.execute("OutfeedDequeueTuple", [], dtypes: dtypes, shapes: shapes, device_ordinal: device_ordinal, name: name)
end
outfeed_enqueue(input, dtype: nil, name: "OutfeedEnqueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2570
def self.outfeed_enqueue(input, dtype: nil, name: "OutfeedEnqueue")
  self.execute("OutfeedEnqueue", [input], dtype: dtype, name: name)
end
outfeed_enqueue_tuple(inputs, dtypes: nil, name: "OutfeedEnqueueTuple") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2574
def self.outfeed_enqueue_tuple(inputs, dtypes: nil, name: "OutfeedEnqueueTuple")
  self.execute("OutfeedEnqueueTuple", [inputs], dtypes: dtypes, name: name)
end
pack(values, n: nil, typeT: nil, axis: 0, name: "Pack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2578
def self.pack(values, n: nil, typeT: nil, axis: 0, name: "Pack")
  self.execute("Pack", [values], N: n, T: typeT, axis: axis, name: name)
end
pad(input, paddings, typeT: nil, tpaddings: :int32, name: "Pad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2582
def self.pad(input, paddings, typeT: nil, tpaddings: :int32, name: "Pad")
  self.execute("Pad", [input, paddings], T: typeT, Tpaddings: tpaddings, name: name)
end
pad_v2(input, paddings, constant_values, typeT: nil, tpaddings: :int32, name: "PadV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2586
def self.pad_v2(input, paddings, constant_values, typeT: nil, tpaddings: :int32, name: "PadV2")
  self.execute("PadV2", [input, paddings, constant_values], T: typeT, Tpaddings: tpaddings, name: name)
end
padded_batch_dataset(input_dataset, batch_size, padded_shapes, padding_values, toutput_types: nil, output_shapes: nil, n: nil, name: "PaddedBatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2590
def self.padded_batch_dataset(input_dataset, batch_size, padded_shapes, padding_values, toutput_types: nil, output_shapes: nil, n: nil, name: "PaddedBatchDataset")
  self.execute("PaddedBatchDataset", [input_dataset, batch_size, padded_shapes, padding_values], Toutput_types: toutput_types, output_shapes: output_shapes, N: n, name: name)
end
padded_batch_dataset_v2(input_dataset, batch_size, padded_shapes, padding_values, drop_remainder, parallel_copy: false, toutput_types: nil, output_shapes: nil, n: nil, name: "PaddedBatchDatasetV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2594
def self.padded_batch_dataset_v2(input_dataset, batch_size, padded_shapes, padding_values, drop_remainder, parallel_copy: false, toutput_types: nil, output_shapes: nil, n: nil, name: "PaddedBatchDatasetV2")
  self.execute("PaddedBatchDatasetV2", [input_dataset, batch_size, padded_shapes, padding_values, drop_remainder], parallel_copy: parallel_copy, Toutput_types: toutput_types, output_shapes: output_shapes, N: n, name: name)
end
padding_fifo_queue(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "PaddingFIFOQueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2598
def self.padding_fifo_queue(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "PaddingFIFOQueue")
  self.execute("PaddingFIFOQueue", [], component_types: component_types, shapes: shapes, capacity: capacity, container: container, shared_name: shared_name, name: name)
end
padding_fifo_queue_v2(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "PaddingFIFOQueueV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2602
def self.padding_fifo_queue_v2(component_types: nil, shapes: [], capacity: -1, container: "", shared_name: "", name: "PaddingFIFOQueueV2")
  self.execute("PaddingFIFOQueueV2", [], component_types: component_types, shapes: shapes, capacity: capacity, container: container, shared_name: shared_name, name: name)
end
parallel_concat(values, n: nil, typeT: nil, shape: nil, name: "ParallelConcat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2606
def self.parallel_concat(values, n: nil, typeT: nil, shape: nil, name: "ParallelConcat")
  self.execute("ParallelConcat", [values], N: n, T: typeT, shape: shape, name: name)
end
parallel_dynamic_stitch(indices, data, n: nil, typeT: nil, name: "ParallelDynamicStitch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2610
def self.parallel_dynamic_stitch(indices, data, n: nil, typeT: nil, name: "ParallelDynamicStitch")
  self.execute("ParallelDynamicStitch", [indices, data], N: n, T: typeT, name: name)
end
parallel_interleave_dataset(input_dataset, other_arguments, cycle_length, block_length, sloppy, buffer_output_elements, prefetch_input_elements, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "ParallelInterleaveDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2614
def self.parallel_interleave_dataset(input_dataset, other_arguments, cycle_length, block_length, sloppy, buffer_output_elements, prefetch_input_elements, f: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "ParallelInterleaveDataset")
  self.execute("ParallelInterleaveDataset", [input_dataset, other_arguments, cycle_length, block_length, sloppy, buffer_output_elements, prefetch_input_elements], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, name: name)
end
parallel_interleave_dataset_v2(input_dataset, other_arguments, cycle_length, block_length, num_parallel_calls, f: nil, targuments: nil, output_types: nil, output_shapes: nil, sloppy: false, name: "ParallelInterleaveDatasetV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2618
def self.parallel_interleave_dataset_v2(input_dataset, other_arguments, cycle_length, block_length, num_parallel_calls, f: nil, targuments: nil, output_types: nil, output_shapes: nil, sloppy: false, name: "ParallelInterleaveDatasetV2")
  self.execute("ParallelInterleaveDatasetV2", [input_dataset, other_arguments, cycle_length, block_length, num_parallel_calls], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, sloppy: sloppy, name: name)
end
parallel_map_dataset(input_dataset, other_arguments, num_parallel_calls, f: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, sloppy: false, preserve_cardinality: false, name: "ParallelMapDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2622
def self.parallel_map_dataset(input_dataset, other_arguments, num_parallel_calls, f: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, sloppy: false, preserve_cardinality: false, name: "ParallelMapDataset")
  self.execute("ParallelMapDataset", [input_dataset, other_arguments, num_parallel_calls], f: f, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, use_inter_op_parallelism: use_inter_op_parallelism, sloppy: sloppy, preserve_cardinality: preserve_cardinality, name: name)
end
parameterized_truncated_normal(shape, means, stdevs, minvals, maxvals, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "ParameterizedTruncatedNormal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2626
def self.parameterized_truncated_normal(shape, means, stdevs, minvals, maxvals, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "ParameterizedTruncatedNormal")
  self.execute("ParameterizedTruncatedNormal", [shape, means, stdevs, minvals, maxvals], seed: seed, seed2: seed2, dtype: dtype, T: typeT, name: name)
end
parse_example(serialized, names, sparse_keys, dense_keys, dense_defaults, nsparse: nil, ndense: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, name: "ParseExample") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2630
def self.parse_example(serialized, names, sparse_keys, dense_keys, dense_defaults, nsparse: nil, ndense: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, name: "ParseExample")
  self.execute("ParseExample", [serialized, names, sparse_keys, dense_keys, dense_defaults], Nsparse: nsparse, Ndense: ndense, sparse_types: sparse_types, Tdense: tdense, dense_shapes: dense_shapes, name: name)
end
parse_example_dataset(input_dataset, num_parallel_calls, dense_defaults, sparse_keys: nil, dense_keys: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, output_types: nil, output_shapes: nil, sloppy: false, ragged_keys: [], ragged_value_types: [], ragged_split_types: [], name: "ParseExampleDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2634
def self.parse_example_dataset(input_dataset, num_parallel_calls, dense_defaults, sparse_keys: nil, dense_keys: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, output_types: nil, output_shapes: nil, sloppy: false, ragged_keys: [], ragged_value_types: [], ragged_split_types: [], name: "ParseExampleDataset")
  self.execute("ParseExampleDataset", [input_dataset, num_parallel_calls, dense_defaults], sparse_keys: sparse_keys, dense_keys: dense_keys, sparse_types: sparse_types, Tdense: tdense, dense_shapes: dense_shapes, output_types: output_types, output_shapes: output_shapes, sloppy: sloppy, ragged_keys: ragged_keys, ragged_value_types: ragged_value_types, ragged_split_types: ragged_split_types, name: name)
end
parse_example_v2(serialized, names, sparse_keys, dense_keys, ragged_keys, dense_defaults, tdense: nil, num_sparse: nil, sparse_types: nil, ragged_value_types: nil, ragged_split_types: nil, dense_shapes: nil, name: "ParseExampleV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2638
def self.parse_example_v2(serialized, names, sparse_keys, dense_keys, ragged_keys, dense_defaults, tdense: nil, num_sparse: nil, sparse_types: nil, ragged_value_types: nil, ragged_split_types: nil, dense_shapes: nil, name: "ParseExampleV2")
  self.execute("ParseExampleV2", [serialized, names, sparse_keys, dense_keys, ragged_keys, dense_defaults], Tdense: tdense, num_sparse: num_sparse, sparse_types: sparse_types, ragged_value_types: ragged_value_types, ragged_split_types: ragged_split_types, dense_shapes: dense_shapes, name: name)
end
parse_sequence_example(serialized, debug_name, context_dense_defaults, feature_list_dense_missing_assumed_empty: nil, context_sparse_keys: nil, context_dense_keys: nil, feature_list_sparse_keys: nil, feature_list_dense_keys: nil, ncontext_sparse: 0, ncontext_dense: 0, nfeature_list_sparse: 0, nfeature_list_dense: 0, context_sparse_types: [], tcontext_dense: [], feature_list_dense_types: [], context_dense_shapes: [], feature_list_sparse_types: [], feature_list_dense_shapes: [], name: "ParseSequenceExample") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2642
def self.parse_sequence_example(serialized, debug_name, context_dense_defaults, feature_list_dense_missing_assumed_empty: nil, context_sparse_keys: nil, context_dense_keys: nil, feature_list_sparse_keys: nil, feature_list_dense_keys: nil, ncontext_sparse: 0, ncontext_dense: 0, nfeature_list_sparse: 0, nfeature_list_dense: 0, context_sparse_types: [], tcontext_dense: [], feature_list_dense_types: [], context_dense_shapes: [], feature_list_sparse_types: [], feature_list_dense_shapes: [], name: "ParseSequenceExample")
  self.execute("ParseSequenceExample", [serialized, debug_name, context_dense_defaults], feature_list_dense_missing_assumed_empty: feature_list_dense_missing_assumed_empty, context_sparse_keys: context_sparse_keys, context_dense_keys: context_dense_keys, feature_list_sparse_keys: feature_list_sparse_keys, feature_list_dense_keys: feature_list_dense_keys, Ncontext_sparse: ncontext_sparse, Ncontext_dense: ncontext_dense, Nfeature_list_sparse: nfeature_list_sparse, Nfeature_list_dense: nfeature_list_dense, context_sparse_types: context_sparse_types, Tcontext_dense: tcontext_dense, feature_list_dense_types: feature_list_dense_types, context_dense_shapes: context_dense_shapes, feature_list_sparse_types: feature_list_sparse_types, feature_list_dense_shapes: feature_list_dense_shapes, name: name)
end
parse_sequence_example_v2(serialized, debug_name, context_sparse_keys, context_dense_keys, context_ragged_keys, feature_list_sparse_keys, feature_list_dense_keys, feature_list_ragged_keys, feature_list_dense_missing_assumed_empty, context_dense_defaults, ncontext_sparse: 0, tcontext_dense: [], context_sparse_types: [], context_ragged_value_types: [], context_ragged_split_types: [], context_dense_shapes: [], nfeature_list_sparse: 0, nfeature_list_dense: 0, feature_list_dense_types: [], feature_list_sparse_types: [], feature_list_ragged_value_types: [], feature_list_ragged_split_types: [], feature_list_dense_shapes: [], name: "ParseSequenceExampleV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2646
def self.parse_sequence_example_v2(serialized, debug_name, context_sparse_keys, context_dense_keys, context_ragged_keys, feature_list_sparse_keys, feature_list_dense_keys, feature_list_ragged_keys, feature_list_dense_missing_assumed_empty, context_dense_defaults, ncontext_sparse: 0, tcontext_dense: [], context_sparse_types: [], context_ragged_value_types: [], context_ragged_split_types: [], context_dense_shapes: [], nfeature_list_sparse: 0, nfeature_list_dense: 0, feature_list_dense_types: [], feature_list_sparse_types: [], feature_list_ragged_value_types: [], feature_list_ragged_split_types: [], feature_list_dense_shapes: [], name: "ParseSequenceExampleV2")
  self.execute("ParseSequenceExampleV2", [serialized, debug_name, context_sparse_keys, context_dense_keys, context_ragged_keys, feature_list_sparse_keys, feature_list_dense_keys, feature_list_ragged_keys, feature_list_dense_missing_assumed_empty, context_dense_defaults], Ncontext_sparse: ncontext_sparse, Tcontext_dense: tcontext_dense, context_sparse_types: context_sparse_types, context_ragged_value_types: context_ragged_value_types, context_ragged_split_types: context_ragged_split_types, context_dense_shapes: context_dense_shapes, Nfeature_list_sparse: nfeature_list_sparse, Nfeature_list_dense: nfeature_list_dense, feature_list_dense_types: feature_list_dense_types, feature_list_sparse_types: feature_list_sparse_types, feature_list_ragged_value_types: feature_list_ragged_value_types, feature_list_ragged_split_types: feature_list_ragged_split_types, feature_list_dense_shapes: feature_list_dense_shapes, name: name)
end
parse_single_example(serialized, dense_defaults, num_sparse: nil, sparse_keys: nil, dense_keys: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, name: "ParseSingleExample") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2650
def self.parse_single_example(serialized, dense_defaults, num_sparse: nil, sparse_keys: nil, dense_keys: nil, sparse_types: nil, tdense: nil, dense_shapes: nil, name: "ParseSingleExample")
  self.execute("ParseSingleExample", [serialized, dense_defaults], num_sparse: num_sparse, sparse_keys: sparse_keys, dense_keys: dense_keys, sparse_types: sparse_types, Tdense: tdense, dense_shapes: dense_shapes, name: name)
end
parse_single_sequence_example(serialized, feature_list_dense_missing_assumed_empty, context_sparse_keys, context_dense_keys, feature_list_sparse_keys, feature_list_dense_keys, context_dense_defaults, debug_name, ncontext_sparse: 0, ncontext_dense: 0, nfeature_list_sparse: 0, nfeature_list_dense: 0, context_sparse_types: [], tcontext_dense: [], feature_list_dense_types: [], context_dense_shapes: [], feature_list_sparse_types: [], feature_list_dense_shapes: [], name: "ParseSingleSequenceExample") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2654
def self.parse_single_sequence_example(serialized, feature_list_dense_missing_assumed_empty, context_sparse_keys, context_dense_keys, feature_list_sparse_keys, feature_list_dense_keys, context_dense_defaults, debug_name, ncontext_sparse: 0, ncontext_dense: 0, nfeature_list_sparse: 0, nfeature_list_dense: 0, context_sparse_types: [], tcontext_dense: [], feature_list_dense_types: [], context_dense_shapes: [], feature_list_sparse_types: [], feature_list_dense_shapes: [], name: "ParseSingleSequenceExample")
  self.execute("ParseSingleSequenceExample", [serialized, feature_list_dense_missing_assumed_empty, context_sparse_keys, context_dense_keys, feature_list_sparse_keys, feature_list_dense_keys, context_dense_defaults, debug_name], Ncontext_sparse: ncontext_sparse, Ncontext_dense: ncontext_dense, Nfeature_list_sparse: nfeature_list_sparse, Nfeature_list_dense: nfeature_list_dense, context_sparse_types: context_sparse_types, Tcontext_dense: tcontext_dense, feature_list_dense_types: feature_list_dense_types, context_dense_shapes: context_dense_shapes, feature_list_sparse_types: feature_list_sparse_types, feature_list_dense_shapes: feature_list_dense_shapes, name: name)
end
parse_tensor(serialized, out_type: nil, name: "ParseTensor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2658
def self.parse_tensor(serialized, out_type: nil, name: "ParseTensor")
  self.execute("ParseTensor", [serialized], out_type: out_type, name: name)
end
partitioned_call(args, tin: nil, tout: nil, f: nil, config: "", config_proto: "", executor_type: "", name: "PartitionedCall") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2662
def self.partitioned_call(args, tin: nil, tout: nil, f: nil, config: "", config_proto: "", executor_type: "", name: "PartitionedCall")
  self.execute("PartitionedCall", [args], Tin: tin, Tout: tout, f: f, config: config, config_proto: config_proto, executor_type: executor_type, name: name)
end
placeholder(dtype: nil, shape: [], name: "Placeholder") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2666
def self.placeholder(dtype: nil, shape: [], name: "Placeholder")
  self.execute("Placeholder", [], dtype: dtype, shape: shape, name: name)
end
placeholder_v2(dtype: nil, shape: nil, name: "PlaceholderV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2670
def self.placeholder_v2(dtype: nil, shape: nil, name: "PlaceholderV2")
  self.execute("PlaceholderV2", [], dtype: dtype, shape: shape, name: name)
end
placeholder_with_default(input, dtype: nil, shape: nil, name: "PlaceholderWithDefault") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2674
def self.placeholder_with_default(input, dtype: nil, shape: nil, name: "PlaceholderWithDefault")
  self.execute("PlaceholderWithDefault", [input], dtype: dtype, shape: shape, name: name)
end
polygamma(a, x, typeT: nil, name: "Polygamma") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2678
def self.polygamma(a, x, typeT: nil, name: "Polygamma")
  self.execute("Polygamma", [a, x], T: typeT, name: name)
end
population_count(x, typeT: nil, name: "PopulationCount") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2682
def self.population_count(x, typeT: nil, name: "PopulationCount")
  self.execute("PopulationCount", [x], T: typeT, name: name)
end
pow(x, y, typeT: nil, name: "Pow") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2686
def self.pow(x, y, typeT: nil, name: "Pow")
  self.execute("Pow", [x, y], T: typeT, name: name)
end
prefetch_dataset(input_dataset, buffer_size, output_types: nil, output_shapes: nil, slack_period: 0, legacy_autotune: true, name: "PrefetchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2690
def self.prefetch_dataset(input_dataset, buffer_size, output_types: nil, output_shapes: nil, slack_period: 0, legacy_autotune: true, name: "PrefetchDataset")
  self.execute("PrefetchDataset", [input_dataset, buffer_size], output_types: output_types, output_shapes: output_shapes, slack_period: slack_period, legacy_autotune: legacy_autotune, name: name)
end
prelinearize(input, dtype: nil, shape: [], layout: [], name: "Prelinearize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2694
def self.prelinearize(input, dtype: nil, shape: [], layout: [], name: "Prelinearize")
  self.execute("Prelinearize", [input], dtype: dtype, shape: shape, layout: layout, name: name)
end
prelinearize_tuple(inputs, dtypes: nil, shapes: nil, layouts: [], name: "PrelinearizeTuple") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2698
def self.prelinearize_tuple(inputs, dtypes: nil, shapes: nil, layouts: [], name: "PrelinearizeTuple")
  self.execute("PrelinearizeTuple", [inputs], dtypes: dtypes, shapes: shapes, layouts: layouts, name: name)
end
prevent_gradient(input, typeT: nil, message: "", name: "PreventGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2702
def self.prevent_gradient(input, typeT: nil, message: "", name: "PreventGradient")
  self.execute("PreventGradient", [input], T: typeT, message: message, name: name)
end
print(input, data, typeT: nil, u: nil, message: "", first_n: -1, summarize: 3, name: "Print") click to toggle source
print_v2(input, output_stream: "stderr", stop: " ", name: "PrintV2") click to toggle source
priority_queue(component_types: [], shapes: nil, capacity: -1, container: "", shared_name: "", name: "PriorityQueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2715
def self.priority_queue(component_types: [], shapes: nil, capacity: -1, container: "", shared_name: "", name: "PriorityQueue")
  self.execute("PriorityQueue", [], component_types: component_types, shapes: shapes, capacity: capacity, container: container, shared_name: shared_name, name: name)
end
priority_queue_v2(component_types: [], shapes: nil, capacity: -1, container: "", shared_name: "", name: "PriorityQueueV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2719
def self.priority_queue_v2(component_types: [], shapes: nil, capacity: -1, container: "", shared_name: "", name: "PriorityQueueV2")
  self.execute("PriorityQueueV2", [], component_types: component_types, shapes: shapes, capacity: capacity, container: container, shared_name: shared_name, name: name)
end
private_thread_pool_dataset(input_dataset, num_threads, output_types: nil, output_shapes: nil, name: "PrivateThreadPoolDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2723
def self.private_thread_pool_dataset(input_dataset, num_threads, output_types: nil, output_shapes: nil, name: "PrivateThreadPoolDataset")
  self.execute("PrivateThreadPoolDataset", [input_dataset, num_threads], output_types: output_types, output_shapes: output_shapes, name: name)
end
prod(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Prod") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2727
def self.prod(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Prod")
  self.execute("Prod", [input, reduction_indices], keep_dims: keep_dims, T: typeT, Tidx: tidx, name: name)
end
py_func(input, token: "", tin: nil, tout: nil, name: "PyFunc") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2731
def self.py_func(input, token: "", tin: nil, tout: nil, name: "PyFunc")
  self.execute("PyFunc", [input], token: token, Tin: tin, Tout: tout, name: name)
end
py_func_stateless(input, token: "", tin: nil, tout: nil, name: "PyFuncStateless") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2735
def self.py_func_stateless(input, token: "", tin: nil, tout: nil, name: "PyFuncStateless")
  self.execute("PyFuncStateless", [input], token: token, Tin: tin, Tout: tout, name: name)
end
qr(input, full_matrices: false, typeT: nil, name: "Qr") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2739
def self.qr(input, full_matrices: false, typeT: nil, name: "Qr")
  self.execute("Qr", [input], full_matrices: full_matrices, T: typeT, name: name)
end
quantize_and_dequantize(input, signed_input: true, num_bits: 8, range_given: false, input_min: 0.0, input_max: 0.0, typeT: nil, name: "QuantizeAndDequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2743
def self.quantize_and_dequantize(input, signed_input: true, num_bits: 8, range_given: false, input_min: 0.0, input_max: 0.0, typeT: nil, name: "QuantizeAndDequantize")
  self.execute("QuantizeAndDequantize", [input], signed_input: signed_input, num_bits: num_bits, range_given: range_given, input_min: input_min, input_max: input_max, T: typeT, name: name)
end
quantize_and_dequantize_v2(input, input_min, input_max, signed_input: true, num_bits: 8, range_given: false, typeT: nil, round_mode: "HALF_TO_EVEN", narrow_range: false, axis: -1, name: "QuantizeAndDequantizeV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2747
def self.quantize_and_dequantize_v2(input, input_min, input_max, signed_input: true, num_bits: 8, range_given: false, typeT: nil, round_mode: "HALF_TO_EVEN", narrow_range: false, axis: -1, name: "QuantizeAndDequantizeV2")
  self.execute("QuantizeAndDequantizeV2", [input, input_min, input_max], signed_input: signed_input, num_bits: num_bits, range_given: range_given, T: typeT, round_mode: round_mode, narrow_range: narrow_range, axis: axis, name: name)
end
quantize_and_dequantize_v3(input, input_min, input_max, num_bits, signed_input: true, range_given: true, typeT: nil, narrow_range: false, axis: -1, name: "QuantizeAndDequantizeV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2751
def self.quantize_and_dequantize_v3(input, input_min, input_max, num_bits, signed_input: true, range_given: true, typeT: nil, narrow_range: false, axis: -1, name: "QuantizeAndDequantizeV3")
  self.execute("QuantizeAndDequantizeV3", [input, input_min, input_max, num_bits], signed_input: signed_input, range_given: range_given, T: typeT, narrow_range: narrow_range, axis: axis, name: name)
end
quantize_down_and_shrink_range(input, input_min, input_max, tinput: nil, out_type: nil, name: "QuantizeDownAndShrinkRange") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2755
def self.quantize_down_and_shrink_range(input, input_min, input_max, tinput: nil, out_type: nil, name: "QuantizeDownAndShrinkRange")
  self.execute("QuantizeDownAndShrinkRange", [input, input_min, input_max], Tinput: tinput, out_type: out_type, name: name)
end
quantize_v2(input, min_range, max_range, typeT: nil, mode: "MIN_COMBINED", round_mode: "HALF_AWAY_FROM_ZERO", narrow_range: false, axis: -1, ensure_minimum_range: 0.009999999776482582, name: "QuantizeV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2759
def self.quantize_v2(input, min_range, max_range, typeT: nil, mode: "MIN_COMBINED", round_mode: "HALF_AWAY_FROM_ZERO", narrow_range: false, axis: -1, ensure_minimum_range: 0.009999999776482582, name: "QuantizeV2")
  self.execute("QuantizeV2", [input, min_range, max_range], T: typeT, mode: mode, round_mode: round_mode, narrow_range: narrow_range, axis: axis, ensure_minimum_range: ensure_minimum_range, name: name)
end
quantized_add(x, y, min_x, max_x, min_y, max_y, t1: nil, t2: nil, toutput: :qint32, name: "QuantizedAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2763
def self.quantized_add(x, y, min_x, max_x, min_y, max_y, t1: nil, t2: nil, toutput: :qint32, name: "QuantizedAdd")
  self.execute("QuantizedAdd", [x, y, min_x, max_x, min_y, max_y], T1: t1, T2: t2, Toutput: toutput, name: name)
end
quantized_avg_pool(input, min_input, max_input, typeT: nil, ksize: nil, strides: nil, padding: nil, name: "QuantizedAvgPool") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2767
def self.quantized_avg_pool(input, min_input, max_input, typeT: nil, ksize: nil, strides: nil, padding: nil, name: "QuantizedAvgPool")
  self.execute("QuantizedAvgPool", [input, min_input, max_input], T: typeT, ksize: ksize, strides: strides, padding: padding, name: name)
end
quantized_batch_norm_with_global_normalization(t, t_min, t_max, m, m_min, m_max, v, v_min, v_max, beta, beta_min, beta_max, gamma, gamma_min, gamma_max, tinput: nil, out_type: nil, variance_epsilon: nil, scale_after_normalization: nil, name: "QuantizedBatchNormWithGlobalNormalization") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2771
def self.quantized_batch_norm_with_global_normalization(t, t_min, t_max, m, m_min, m_max, v, v_min, v_max, beta, beta_min, beta_max, gamma, gamma_min, gamma_max, tinput: nil, out_type: nil, variance_epsilon: nil, scale_after_normalization: nil, name: "QuantizedBatchNormWithGlobalNormalization")
  self.execute("QuantizedBatchNormWithGlobalNormalization", [t, t_min, t_max, m, m_min, m_max, v, v_min, v_max, beta, beta_min, beta_max, gamma, gamma_min, gamma_max], Tinput: tinput, out_type: out_type, variance_epsilon: variance_epsilon, scale_after_normalization: scale_after_normalization, name: name)
end
quantized_bias_add(input, bias, min_input, max_input, min_bias, max_bias, t1: nil, t2: nil, out_type: nil, name: "QuantizedBiasAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2775
def self.quantized_bias_add(input, bias, min_input, max_input, min_bias, max_bias, t1: nil, t2: nil, out_type: nil, name: "QuantizedBiasAdd")
  self.execute("QuantizedBiasAdd", [input, bias, min_input, max_input, min_bias, max_bias], T1: t1, T2: t2, out_type: out_type, name: name)
end
quantized_concat(concat_dim, values, input_mins, input_maxes, n: nil, typeT: nil, name: "QuantizedConcat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2779
def self.quantized_concat(concat_dim, values, input_mins, input_maxes, n: nil, typeT: nil, name: "QuantizedConcat")
  self.execute("QuantizedConcat", [concat_dim, values, input_mins, input_maxes], N: n, T: typeT, name: name)
end
quantized_conv2_d(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedConv2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2783
def self.quantized_conv2_d(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedConv2D")
  self.execute("QuantizedConv2D", [input, filter, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, name: name)
end
quantized_conv2_d_and_relu(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DAndRelu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2787
def self.quantized_conv2_d_and_relu(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DAndRelu")
  self.execute("QuantizedConv2DAndRelu", [input, filter, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_and_relu_and_requantize(input, filter, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DAndReluAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2791
def self.quantized_conv2_d_and_relu_and_requantize(input, filter, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DAndReluAndRequantize")
  self.execute("QuantizedConv2DAndReluAndRequantize", [input, filter, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_and_requantize(input, filter, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, out_type: :qint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2795
def self.quantized_conv2_d_and_requantize(input, filter, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, out_type: :qint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DAndRequantize")
  self.execute("QuantizedConv2DAndRequantize", [input, filter, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_per_channel(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedConv2DPerChannel") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2799
def self.quantized_conv2_d_per_channel(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedConv2DPerChannel")
  self.execute("QuantizedConv2DPerChannel", [input, filter, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, name: name)
end
quantized_conv2_d_with_bias(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBias") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2803
def self.quantized_conv2_d_with_bias(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBias")
  self.execute("QuantizedConv2DWithBias", [input, filter, bias, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_with_bias_and_relu(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasAndRelu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2807
def self.quantized_conv2_d_with_bias_and_relu(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasAndRelu")
  self.execute("QuantizedConv2DWithBiasAndRelu", [input, filter, bias, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_with_bias_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, tbias: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasAndReluAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2811
def self.quantized_conv2_d_with_bias_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, tbias: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasAndReluAndRequantize")
  self.execute("QuantizedConv2DWithBiasAndReluAndRequantize", [input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output], Tinput: tinput, Tfilter: tfilter, Tbias: tbias, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_with_bias_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, tbias: nil, out_type: :qint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2815
def self.quantized_conv2_d_with_bias_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, tbias: nil, out_type: :qint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasAndRequantize")
  self.execute("QuantizedConv2DWithBiasAndRequantize", [input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output], Tinput: tinput, Tfilter: tfilter, Tbias: tbias, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_with_bias_signed_sum_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, summand, min_summand, max_summand, tinput: nil, tfilter: nil, tbias: nil, tsummand: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasSignedSumAndReluAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2819
def self.quantized_conv2_d_with_bias_signed_sum_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, summand, min_summand, max_summand, tinput: nil, tfilter: nil, tbias: nil, tsummand: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasSignedSumAndReluAndRequantize")
  self.execute("QuantizedConv2DWithBiasSignedSumAndReluAndRequantize", [input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, summand, min_summand, max_summand], Tinput: tinput, Tfilter: tfilter, Tbias: tbias, Tsummand: tsummand, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_with_bias_sum_and_relu(input, filter, bias, min_input, max_input, min_filter, max_filter, summand, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasSumAndRelu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2823
def self.quantized_conv2_d_with_bias_sum_and_relu(input, filter, bias, min_input, max_input, min_filter, max_filter, summand, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasSumAndRelu")
  self.execute("QuantizedConv2DWithBiasSumAndRelu", [input, filter, bias, min_input, max_input, min_filter, max_filter, summand], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_conv2_d_with_bias_sum_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, summand, min_summand, max_summand, tinput: nil, tfilter: nil, tbias: nil, tsummand: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasSumAndReluAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2827
def self.quantized_conv2_d_with_bias_sum_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, summand, min_summand, max_summand, tinput: nil, tfilter: nil, tbias: nil, tsummand: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], padding_list: [], name: "QuantizedConv2DWithBiasSumAndReluAndRequantize")
  self.execute("QuantizedConv2DWithBiasSumAndReluAndRequantize", [input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, summand, min_summand, max_summand], Tinput: tinput, Tfilter: tfilter, Tbias: tbias, Tsummand: tsummand, out_type: out_type, strides: strides, padding: padding, dilations: dilations, padding_list: padding_list, name: name)
end
quantized_depthwise_conv2_d(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2831
def self.quantized_depthwise_conv2_d(input, filter, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2D")
  self.execute("QuantizedDepthwiseConv2D", [input, filter, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, name: name)
end
quantized_depthwise_conv2_d_with_bias(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2DWithBias") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2835
def self.quantized_depthwise_conv2_d_with_bias(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2DWithBias")
  self.execute("QuantizedDepthwiseConv2DWithBias", [input, filter, bias, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, name: name)
end
quantized_depthwise_conv2_d_with_bias_and_relu(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2DWithBiasAndRelu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2839
def self.quantized_depthwise_conv2_d_with_bias_and_relu(input, filter, bias, min_input, max_input, min_filter, max_filter, tinput: nil, tfilter: nil, out_type: :qint32, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2DWithBiasAndRelu")
  self.execute("QuantizedDepthwiseConv2DWithBiasAndRelu", [input, filter, bias, min_input, max_input, min_filter, max_filter], Tinput: tinput, Tfilter: tfilter, out_type: out_type, strides: strides, padding: padding, dilations: dilations, name: name)
end
quantized_depthwise_conv2_d_with_bias_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, tbias: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2843
def self.quantized_depthwise_conv2_d_with_bias_and_relu_and_requantize(input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output, tinput: nil, tfilter: nil, tbias: nil, out_type: :quint8, strides: nil, padding: nil, dilations: [], name: "QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize")
  self.execute("QuantizedDepthwiseConv2DWithBiasAndReluAndRequantize", [input, filter, bias, min_input, max_input, min_filter, max_filter, min_freezed_output, max_freezed_output], Tinput: tinput, Tfilter: tfilter, Tbias: tbias, out_type: out_type, strides: strides, padding: padding, dilations: dilations, name: name)
end
quantized_instance_norm(x, x_min, x_max, typeT: nil, output_range_given: false, given_y_min: 0.0, given_y_max: 0.0, variance_epsilon: 9.999999747378752e-06, min_separation: 0.0010000000474974513, name: "QuantizedInstanceNorm") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2847
def self.quantized_instance_norm(x, x_min, x_max, typeT: nil, output_range_given: false, given_y_min: 0.0, given_y_max: 0.0, variance_epsilon: 9.999999747378752e-06, min_separation: 0.0010000000474974513, name: "QuantizedInstanceNorm")
  self.execute("QuantizedInstanceNorm", [x, x_min, x_max], T: typeT, output_range_given: output_range_given, given_y_min: given_y_min, given_y_max: given_y_max, variance_epsilon: variance_epsilon, min_separation: min_separation, name: name)
end
quantized_mat_mul(a, b, min_a, max_a, min_b, max_b, t1: nil, t2: nil, toutput: :qint32, transpose_a: false, transpose_b: false, tactivation: :quint8, name: "QuantizedMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2851
def self.quantized_mat_mul(a, b, min_a, max_a, min_b, max_b, t1: nil, t2: nil, toutput: :qint32, transpose_a: false, transpose_b: false, tactivation: :quint8, name: "QuantizedMatMul")
  self.execute("QuantizedMatMul", [a, b, min_a, max_a, min_b, max_b], T1: t1, T2: t2, Toutput: toutput, transpose_a: transpose_a, transpose_b: transpose_b, Tactivation: tactivation, name: name)
end
quantized_mat_mul_with_bias(a, b, bias, min_a, max_a, min_b, max_b, t1: nil, t2: nil, tbias: nil, toutput: :qint32, transpose_a: false, transpose_b: false, input_quant_mode: "MIN_FIRST", name: "QuantizedMatMulWithBias") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2855
def self.quantized_mat_mul_with_bias(a, b, bias, min_a, max_a, min_b, max_b, t1: nil, t2: nil, tbias: nil, toutput: :qint32, transpose_a: false, transpose_b: false, input_quant_mode: "MIN_FIRST", name: "QuantizedMatMulWithBias")
  self.execute("QuantizedMatMulWithBias", [a, b, bias, min_a, max_a, min_b, max_b], T1: t1, T2: t2, Tbias: tbias, Toutput: toutput, transpose_a: transpose_a, transpose_b: transpose_b, input_quant_mode: input_quant_mode, name: name)
end
quantized_mat_mul_with_bias_and_relu(a, b, bias, min_a, max_a, min_b, max_b, t1: nil, t2: nil, toutput: :qint32, transpose_a: false, transpose_b: false, input_quant_mode: "MIN_FIRST", name: "QuantizedMatMulWithBiasAndRelu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2859
def self.quantized_mat_mul_with_bias_and_relu(a, b, bias, min_a, max_a, min_b, max_b, t1: nil, t2: nil, toutput: :qint32, transpose_a: false, transpose_b: false, input_quant_mode: "MIN_FIRST", name: "QuantizedMatMulWithBiasAndRelu")
  self.execute("QuantizedMatMulWithBiasAndRelu", [a, b, bias, min_a, max_a, min_b, max_b], T1: t1, T2: t2, Toutput: toutput, transpose_a: transpose_a, transpose_b: transpose_b, input_quant_mode: input_quant_mode, name: name)
end
quantized_mat_mul_with_bias_and_relu_and_requantize(a, b, bias, min_a, max_a, min_b, max_b, min_freezed_output, max_freezed_output, t1: nil, t2: nil, tbias: nil, toutput: :quint8, transpose_a: false, transpose_b: false, input_quant_mode: "MIN_FIRST", name: "QuantizedMatMulWithBiasAndReluAndRequantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2863
def self.quantized_mat_mul_with_bias_and_relu_and_requantize(a, b, bias, min_a, max_a, min_b, max_b, min_freezed_output, max_freezed_output, t1: nil, t2: nil, tbias: nil, toutput: :quint8, transpose_a: false, transpose_b: false, input_quant_mode: "MIN_FIRST", name: "QuantizedMatMulWithBiasAndReluAndRequantize")
  self.execute("QuantizedMatMulWithBiasAndReluAndRequantize", [a, b, bias, min_a, max_a, min_b, max_b, min_freezed_output, max_freezed_output], T1: t1, T2: t2, Tbias: tbias, Toutput: toutput, transpose_a: transpose_a, transpose_b: transpose_b, input_quant_mode: input_quant_mode, name: name)
end
quantized_max_pool(input, min_input, max_input, typeT: nil, ksize: nil, strides: nil, padding: nil, name: "QuantizedMaxPool") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2867
def self.quantized_max_pool(input, min_input, max_input, typeT: nil, ksize: nil, strides: nil, padding: nil, name: "QuantizedMaxPool")
  self.execute("QuantizedMaxPool", [input, min_input, max_input], T: typeT, ksize: ksize, strides: strides, padding: padding, name: name)
end
quantized_mul(x, y, min_x, max_x, min_y, max_y, t1: nil, t2: nil, toutput: :qint32, name: "QuantizedMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2871
def self.quantized_mul(x, y, min_x, max_x, min_y, max_y, t1: nil, t2: nil, toutput: :qint32, name: "QuantizedMul")
  self.execute("QuantizedMul", [x, y, min_x, max_x, min_y, max_y], T1: t1, T2: t2, Toutput: toutput, name: name)
end
quantized_relu(features, min_features, max_features, tinput: nil, out_type: :quint8, name: "QuantizedRelu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2875
def self.quantized_relu(features, min_features, max_features, tinput: nil, out_type: :quint8, name: "QuantizedRelu")
  self.execute("QuantizedRelu", [features, min_features, max_features], Tinput: tinput, out_type: out_type, name: name)
end
quantized_relu6(features, min_features, max_features, tinput: nil, out_type: :quint8, name: "QuantizedRelu6") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2879
def self.quantized_relu6(features, min_features, max_features, tinput: nil, out_type: :quint8, name: "QuantizedRelu6")
  self.execute("QuantizedRelu6", [features, min_features, max_features], Tinput: tinput, out_type: out_type, name: name)
end
quantized_relu_x(features, max_value, min_features, max_features, tinput: nil, out_type: :quint8, name: "QuantizedReluX") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2883
def self.quantized_relu_x(features, max_value, min_features, max_features, tinput: nil, out_type: :quint8, name: "QuantizedReluX")
  self.execute("QuantizedReluX", [features, max_value, min_features, max_features], Tinput: tinput, out_type: out_type, name: name)
end
quantized_reshape(tensor, shape, input_min, input_max, typeT: nil, tshape: :int32, name: "QuantizedReshape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2887
def self.quantized_reshape(tensor, shape, input_min, input_max, typeT: nil, tshape: :int32, name: "QuantizedReshape")
  self.execute("QuantizedReshape", [tensor, shape, input_min, input_max], T: typeT, Tshape: tshape, name: name)
end
quantized_resize_bilinear(images, size, min, max, typeT: nil, align_corners: false, half_pixel_centers: false, name: "QuantizedResizeBilinear") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2891
def self.quantized_resize_bilinear(images, size, min, max, typeT: nil, align_corners: false, half_pixel_centers: false, name: "QuantizedResizeBilinear")
  self.execute("QuantizedResizeBilinear", [images, size, min, max], T: typeT, align_corners: align_corners, half_pixel_centers: half_pixel_centers, name: name)
end
queue_close(handle, cancel_pending_enqueues: false, name: "QueueClose") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2895
def self.queue_close(handle, cancel_pending_enqueues: false, name: "QueueClose")
  self.execute("QueueClose", [handle], cancel_pending_enqueues: cancel_pending_enqueues, name: name)
end
queue_close_v2(handle, cancel_pending_enqueues: false, name: "QueueCloseV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2899
def self.queue_close_v2(handle, cancel_pending_enqueues: false, name: "QueueCloseV2")
  self.execute("QueueCloseV2", [handle], cancel_pending_enqueues: cancel_pending_enqueues, name: name)
end
queue_dequeue(handle, component_types: nil, timeout_ms: -1, name: "QueueDequeue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2903
def self.queue_dequeue(handle, component_types: nil, timeout_ms: -1, name: "QueueDequeue")
  self.execute("QueueDequeue", [handle], component_types: component_types, timeout_ms: timeout_ms, name: name)
end
queue_dequeue_many(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueMany") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2907
def self.queue_dequeue_many(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueMany")
  self.execute("QueueDequeueMany", [handle, n], component_types: component_types, timeout_ms: timeout_ms, name: name)
end
queue_dequeue_many_v2(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueManyV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2911
def self.queue_dequeue_many_v2(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueManyV2")
  self.execute("QueueDequeueManyV2", [handle, n], component_types: component_types, timeout_ms: timeout_ms, name: name)
end
queue_dequeue_up_to(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueUpTo") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2915
def self.queue_dequeue_up_to(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueUpTo")
  self.execute("QueueDequeueUpTo", [handle, n], component_types: component_types, timeout_ms: timeout_ms, name: name)
end
queue_dequeue_up_to_v2(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueUpToV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2919
def self.queue_dequeue_up_to_v2(handle, n, component_types: nil, timeout_ms: -1, name: "QueueDequeueUpToV2")
  self.execute("QueueDequeueUpToV2", [handle, n], component_types: component_types, timeout_ms: timeout_ms, name: name)
end
queue_dequeue_v2(handle, component_types: nil, timeout_ms: -1, name: "QueueDequeueV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2923
def self.queue_dequeue_v2(handle, component_types: nil, timeout_ms: -1, name: "QueueDequeueV2")
  self.execute("QueueDequeueV2", [handle], component_types: component_types, timeout_ms: timeout_ms, name: name)
end
queue_enqueue(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2927
def self.queue_enqueue(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueue")
  self.execute("QueueEnqueue", [handle, components], Tcomponents: tcomponents, timeout_ms: timeout_ms, name: name)
end
queue_enqueue_many(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueueMany") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2931
def self.queue_enqueue_many(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueueMany")
  self.execute("QueueEnqueueMany", [handle, components], Tcomponents: tcomponents, timeout_ms: timeout_ms, name: name)
end
queue_enqueue_many_v2(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueueManyV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2935
def self.queue_enqueue_many_v2(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueueManyV2")
  self.execute("QueueEnqueueManyV2", [handle, components], Tcomponents: tcomponents, timeout_ms: timeout_ms, name: name)
end
queue_enqueue_v2(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueueV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2939
def self.queue_enqueue_v2(handle, components, tcomponents: nil, timeout_ms: -1, name: "QueueEnqueueV2")
  self.execute("QueueEnqueueV2", [handle, components], Tcomponents: tcomponents, timeout_ms: timeout_ms, name: name)
end
queue_is_closed(handle, name: "QueueIsClosed") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2943
def self.queue_is_closed(handle, name: "QueueIsClosed")
  self.execute("QueueIsClosed", [handle], name: name)
end
queue_is_closed_v2(handle, name: "QueueIsClosedV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2947
def self.queue_is_closed_v2(handle, name: "QueueIsClosedV2")
  self.execute("QueueIsClosedV2", [handle], name: name)
end
queue_size(handle, name: "QueueSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2951
def self.queue_size(handle, name: "QueueSize")
  self.execute("QueueSize", [handle], name: name)
end
queue_size_v2(handle, name: "QueueSizeV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2955
def self.queue_size_v2(handle, name: "QueueSizeV2")
  self.execute("QueueSizeV2", [handle], name: name)
end
ragged_gather(params_nested_splits, params_dense_values, indices, tvalues: nil, tindices: nil, tsplits: :int64, params_ragged_rank: nil, output_ragged_rank: nil, name: "RaggedGather") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2975
def self.ragged_gather(params_nested_splits, params_dense_values, indices, tvalues: nil, tindices: nil, tsplits: :int64, params_ragged_rank: nil, output_ragged_rank: nil, name: "RaggedGather")
  self.execute("RaggedGather", [params_nested_splits, params_dense_values, indices], Tvalues: tvalues, Tindices: tindices, Tsplits: tsplits, PARAMS_RAGGED_RANK: params_ragged_rank, OUTPUT_RAGGED_RANK: output_ragged_rank, name: name)
end
ragged_range(starts, limits, deltas, typeT: :int32, tsplits: :int64, name: "RaggedRange") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2979
def self.ragged_range(starts, limits, deltas, typeT: :int32, tsplits: :int64, name: "RaggedRange")
  self.execute("RaggedRange", [starts, limits, deltas], T: typeT, Tsplits: tsplits, name: name)
end
ragged_tensor_from_variant(encoded_ragged, input_ragged_rank: nil, output_ragged_rank: nil, tvalues: nil, tsplits: :int64, name: "RaggedTensorFromVariant") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2983
def self.ragged_tensor_from_variant(encoded_ragged, input_ragged_rank: nil, output_ragged_rank: nil, tvalues: nil, tsplits: :int64, name: "RaggedTensorFromVariant")
  self.execute("RaggedTensorFromVariant", [encoded_ragged], input_ragged_rank: input_ragged_rank, output_ragged_rank: output_ragged_rank, Tvalues: tvalues, Tsplits: tsplits, name: name)
end
ragged_tensor_to_sparse(rt_nested_splits, rt_dense_values, ragged_rank: nil, typeT: nil, tsplits: :int64, name: "RaggedTensorToSparse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2987
def self.ragged_tensor_to_sparse(rt_nested_splits, rt_dense_values, ragged_rank: nil, typeT: nil, tsplits: :int64, name: "RaggedTensorToSparse")
  self.execute("RaggedTensorToSparse", [rt_nested_splits, rt_dense_values], RAGGED_RANK: ragged_rank, T: typeT, Tsplits: tsplits, name: name)
end
ragged_tensor_to_tensor(shape, values, default_value, row_partition_tensors, typeT: nil, tindex: nil, tshape: nil, num_row_partition_tensors: nil, row_partition_types: nil, name: "RaggedTensorToTensor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2991
def self.ragged_tensor_to_tensor(shape, values, default_value, row_partition_tensors, typeT: nil, tindex: nil, tshape: nil, num_row_partition_tensors: nil, row_partition_types: nil, name: "RaggedTensorToTensor")
  self.execute("RaggedTensorToTensor", [shape, values, default_value, row_partition_tensors], T: typeT, Tindex: tindex, Tshape: tshape, num_row_partition_tensors: num_row_partition_tensors, row_partition_types: row_partition_types, name: name)
end
ragged_tensor_to_variant(rt_nested_splits, rt_dense_values, ragged_rank: nil, tvalues: nil, tsplits: :int64, batched_input: nil, name: "RaggedTensorToVariant") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2995
def self.ragged_tensor_to_variant(rt_nested_splits, rt_dense_values, ragged_rank: nil, tvalues: nil, tsplits: :int64, batched_input: nil, name: "RaggedTensorToVariant")
  self.execute("RaggedTensorToVariant", [rt_nested_splits, rt_dense_values], RAGGED_RANK: ragged_rank, Tvalues: tvalues, Tsplits: tsplits, batched_input: batched_input, name: name)
end
random_crop(image, size, typeT: nil, seed: 0, seed2: 0, name: "RandomCrop") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2999
def self.random_crop(image, size, typeT: nil, seed: 0, seed2: 0, name: "RandomCrop")
  self.execute("RandomCrop", [image, size], T: typeT, seed: seed, seed2: seed2, name: name)
end
random_dataset(seed, seed2, output_types: nil, output_shapes: nil, name: "RandomDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3003
def self.random_dataset(seed, seed2, output_types: nil, output_shapes: nil, name: "RandomDataset")
  self.execute("RandomDataset", [seed, seed2], output_types: output_types, output_shapes: output_shapes, name: name)
end
random_gamma(shape, alpha, seed: 0, seed2: 0, s: nil, typeT: nil, name: "RandomGamma") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3007
def self.random_gamma(shape, alpha, seed: 0, seed2: 0, s: nil, typeT: nil, name: "RandomGamma")
  self.execute("RandomGamma", [shape, alpha], seed: seed, seed2: seed2, S: s, T: typeT, name: name)
end
random_gamma_grad(alpha, sample, typeT: nil, name: "RandomGammaGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3011
def self.random_gamma_grad(alpha, sample, typeT: nil, name: "RandomGammaGrad")
  self.execute("RandomGammaGrad", [alpha, sample], T: typeT, name: name)
end
random_poisson(shape, rate, seed: 0, seed2: 0, s: nil, dtype: nil, name: "RandomPoisson") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3015
def self.random_poisson(shape, rate, seed: 0, seed2: 0, s: nil, dtype: nil, name: "RandomPoisson")
  self.execute("RandomPoisson", [shape, rate], seed: seed, seed2: seed2, S: s, dtype: dtype, name: name)
end
random_poisson_v2(shape, rate, seed: 0, seed2: 0, s: nil, r: :double, dtype: :int64, name: "RandomPoissonV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3019
def self.random_poisson_v2(shape, rate, seed: 0, seed2: 0, s: nil, r: :double, dtype: :int64, name: "RandomPoissonV2")
  self.execute("RandomPoissonV2", [shape, rate], seed: seed, seed2: seed2, S: s, R: r, dtype: dtype, name: name)
end
random_shuffle(value, seed: 0, seed2: 0, typeT: nil, name: "RandomShuffle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3023
def self.random_shuffle(value, seed: 0, seed2: 0, typeT: nil, name: "RandomShuffle")
  self.execute("RandomShuffle", [value], seed: seed, seed2: seed2, T: typeT, name: name)
end
random_shuffle_queue(component_types: nil, shapes: [], capacity: -1, min_after_dequeue: 0, seed: 0, seed2: 0, container: "", shared_name: "", name: "RandomShuffleQueue") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3027
def self.random_shuffle_queue(component_types: nil, shapes: [], capacity: -1, min_after_dequeue: 0, seed: 0, seed2: 0, container: "", shared_name: "", name: "RandomShuffleQueue")
  self.execute("RandomShuffleQueue", [], component_types: component_types, shapes: shapes, capacity: capacity, min_after_dequeue: min_after_dequeue, seed: seed, seed2: seed2, container: container, shared_name: shared_name, name: name)
end
random_shuffle_queue_v2(component_types: nil, shapes: [], capacity: -1, min_after_dequeue: 0, seed: 0, seed2: 0, container: "", shared_name: "", name: "RandomShuffleQueueV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3031
def self.random_shuffle_queue_v2(component_types: nil, shapes: [], capacity: -1, min_after_dequeue: 0, seed: 0, seed2: 0, container: "", shared_name: "", name: "RandomShuffleQueueV2")
  self.execute("RandomShuffleQueueV2", [], component_types: component_types, shapes: shapes, capacity: capacity, min_after_dequeue: min_after_dequeue, seed: seed, seed2: seed2, container: container, shared_name: shared_name, name: name)
end
random_standard_normal(shape, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "RandomStandardNormal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3035
def self.random_standard_normal(shape, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "RandomStandardNormal")
  self.execute("RandomStandardNormal", [shape], seed: seed, seed2: seed2, dtype: dtype, T: typeT, name: name)
end
random_uniform(shape, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "RandomUniform") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3039
def self.random_uniform(shape, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "RandomUniform")
  self.execute("RandomUniform", [shape], seed: seed, seed2: seed2, dtype: dtype, T: typeT, name: name)
end
random_uniform_int(shape, minval, maxval, seed: 0, seed2: 0, tout: nil, typeT: nil, name: "RandomUniformInt") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3043
def self.random_uniform_int(shape, minval, maxval, seed: 0, seed2: 0, tout: nil, typeT: nil, name: "RandomUniformInt")
  self.execute("RandomUniformInt", [shape, minval, maxval], seed: seed, seed2: seed2, Tout: tout, T: typeT, name: name)
end
range(start, limit, delta, tidx: :int32, name: "Range") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3047
def self.range(start, limit, delta, tidx: :int32, name: "Range")
  self.execute("Range", [start, limit, delta], Tidx: tidx, name: name)
end
range_dataset(start, stop, step, output_types: nil, output_shapes: nil, name: "RangeDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3051
def self.range_dataset(start, stop, step, output_types: nil, output_shapes: nil, name: "RangeDataset")
  self.execute("RangeDataset", [start, stop, step], output_types: output_types, output_shapes: output_shapes, name: name)
end
rank(input, typeT: nil, name: "Rank") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3055
def self.rank(input, typeT: nil, name: "Rank")
  self.execute("Rank", [input], T: typeT, name: name)
end
read_file(filename, name: "ReadFile") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3059
def self.read_file(filename, name: "ReadFile")
  self.execute("ReadFile", [filename], name: name)
end
read_variable_op(resource, dtype: nil, name: "ReadVariableOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3063
def self.read_variable_op(resource, dtype: nil, name: "ReadVariableOp")
  self.execute("ReadVariableOp", [resource], dtype: dtype, name: name)
end
reader_num_records_produced(reader_handle, name: "ReaderNumRecordsProduced") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3067
def self.reader_num_records_produced(reader_handle, name: "ReaderNumRecordsProduced")
  self.execute("ReaderNumRecordsProduced", [reader_handle], name: name)
end
reader_num_records_produced_v2(reader_handle, name: "ReaderNumRecordsProducedV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3071
def self.reader_num_records_produced_v2(reader_handle, name: "ReaderNumRecordsProducedV2")
  self.execute("ReaderNumRecordsProducedV2", [reader_handle], name: name)
end
reader_num_work_units_completed(reader_handle, name: "ReaderNumWorkUnitsCompleted") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3075
def self.reader_num_work_units_completed(reader_handle, name: "ReaderNumWorkUnitsCompleted")
  self.execute("ReaderNumWorkUnitsCompleted", [reader_handle], name: name)
end
reader_num_work_units_completed_v2(reader_handle, name: "ReaderNumWorkUnitsCompletedV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3079
def self.reader_num_work_units_completed_v2(reader_handle, name: "ReaderNumWorkUnitsCompletedV2")
  self.execute("ReaderNumWorkUnitsCompletedV2", [reader_handle], name: name)
end
reader_read(reader_handle, queue_handle, name: "ReaderRead") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3083
def self.reader_read(reader_handle, queue_handle, name: "ReaderRead")
  self.execute("ReaderRead", [reader_handle, queue_handle], name: name)
end
reader_read_up_to(reader_handle, queue_handle, num_records, name: "ReaderReadUpTo") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3087
def self.reader_read_up_to(reader_handle, queue_handle, num_records, name: "ReaderReadUpTo")
  self.execute("ReaderReadUpTo", [reader_handle, queue_handle, num_records], name: name)
end
reader_read_up_to_v2(reader_handle, queue_handle, num_records, name: "ReaderReadUpToV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3091
def self.reader_read_up_to_v2(reader_handle, queue_handle, num_records, name: "ReaderReadUpToV2")
  self.execute("ReaderReadUpToV2", [reader_handle, queue_handle, num_records], name: name)
end
reader_read_v2(reader_handle, queue_handle, name: "ReaderReadV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3095
def self.reader_read_v2(reader_handle, queue_handle, name: "ReaderReadV2")
  self.execute("ReaderReadV2", [reader_handle, queue_handle], name: name)
end
reader_reset(reader_handle, name: "ReaderReset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3099
def self.reader_reset(reader_handle, name: "ReaderReset")
  self.execute("ReaderReset", [reader_handle], name: name)
end
reader_reset_v2(reader_handle, name: "ReaderResetV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3103
def self.reader_reset_v2(reader_handle, name: "ReaderResetV2")
  self.execute("ReaderResetV2", [reader_handle], name: name)
end
reader_restore_state(reader_handle, state, name: "ReaderRestoreState") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3107
def self.reader_restore_state(reader_handle, state, name: "ReaderRestoreState")
  self.execute("ReaderRestoreState", [reader_handle, state], name: name)
end
reader_restore_state_v2(reader_handle, state, name: "ReaderRestoreStateV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3111
def self.reader_restore_state_v2(reader_handle, state, name: "ReaderRestoreStateV2")
  self.execute("ReaderRestoreStateV2", [reader_handle, state], name: name)
end
reader_serialize_state(reader_handle, name: "ReaderSerializeState") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3115
def self.reader_serialize_state(reader_handle, name: "ReaderSerializeState")
  self.execute("ReaderSerializeState", [reader_handle], name: name)
end
reader_serialize_state_v2(reader_handle, name: "ReaderSerializeStateV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3119
def self.reader_serialize_state_v2(reader_handle, name: "ReaderSerializeStateV2")
  self.execute("ReaderSerializeStateV2", [reader_handle], name: name)
end
real(input, typeT: :complex64, tout: :float, name: "Real") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3123
def self.real(input, typeT: :complex64, tout: :float, name: "Real")
  self.execute("Real", [input], T: typeT, Tout: tout, name: name)
end
real_div(x, y, typeT: nil, name: "RealDiv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3127
def self.real_div(x, y, typeT: nil, name: "RealDiv")
  self.execute("RealDiv", [x, y], T: typeT, name: name)
end
rebatch_dataset(input_dataset, num_replicas, output_types: nil, output_shapes: nil, use_fallback: true, name: "RebatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3131
def self.rebatch_dataset(input_dataset, num_replicas, output_types: nil, output_shapes: nil, use_fallback: true, name: "RebatchDataset")
  self.execute("RebatchDataset", [input_dataset, num_replicas], output_types: output_types, output_shapes: output_shapes, use_fallback: use_fallback, name: name)
end
reciprocal(x, typeT: nil, name: "Reciprocal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3135
def self.reciprocal(x, typeT: nil, name: "Reciprocal")
  self.execute("Reciprocal", [x], T: typeT, name: name)
end
reciprocal_grad(y, dy, typeT: nil, name: "ReciprocalGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3139
def self.reciprocal_grad(y, dy, typeT: nil, name: "ReciprocalGrad")
  self.execute("ReciprocalGrad", [y, dy], T: typeT, name: name)
end
record_input(file_pattern: "", file_random_seed: 301, file_shuffle_shift_ratio: 0.0, file_buffer_size: 10000, file_parallelism: 16, batch_size: 32, compression_type: "", name: "RecordInput") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3143
def self.record_input(file_pattern: "", file_random_seed: 301, file_shuffle_shift_ratio: 0.0, file_buffer_size: 10000, file_parallelism: 16, batch_size: 32, compression_type: "", name: "RecordInput")
  self.execute("RecordInput", [], file_pattern: file_pattern, file_random_seed: file_random_seed, file_shuffle_shift_ratio: file_shuffle_shift_ratio, file_buffer_size: file_buffer_size, file_parallelism: file_parallelism, batch_size: batch_size, compression_type: compression_type, name: name)
end
recv(tensor_type: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "Recv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3147
def self.recv(tensor_type: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "Recv")
  self.execute("Recv", [], tensor_type: tensor_type, tensor_name: tensor_name, send_device: send_device, send_device_incarnation: send_device_incarnation, recv_device: recv_device, client_terminated: client_terminated, name: name)
end
recv_tpu_embedding_activations(num_outputs: nil, config: "", name: "RecvTPUEmbeddingActivations") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3151
def self.recv_tpu_embedding_activations(num_outputs: nil, config: "", name: "RecvTPUEmbeddingActivations")
  self.execute("RecvTPUEmbeddingActivations", [], num_outputs: num_outputs, config: config, name: name)
end
reduce_dataset(input_dataset, initial_state, other_arguments, f: nil, tstate: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, name: "ReduceDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3155
def self.reduce_dataset(input_dataset, initial_state, other_arguments, f: nil, tstate: nil, targuments: nil, output_types: nil, output_shapes: nil, use_inter_op_parallelism: true, name: "ReduceDataset")
  self.execute("ReduceDataset", [input_dataset, initial_state, other_arguments], f: f, Tstate: tstate, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, use_inter_op_parallelism: use_inter_op_parallelism, name: name)
end
reduce_join(inputs, reduction_indices, keep_dims: false, separator: "", name: "ReduceJoin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3159
def self.reduce_join(inputs, reduction_indices, keep_dims: false, separator: "", name: "ReduceJoin")
  self.execute("ReduceJoin", [inputs, reduction_indices], keep_dims: keep_dims, separator: separator, name: name)
end
ref_enter(data, typeT: nil, frame_name: "", is_constant: false, parallel_iterations: 10, name: "RefEnter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3163
def self.ref_enter(data, typeT: nil, frame_name: "", is_constant: false, parallel_iterations: 10, name: "RefEnter")
  self.execute("RefEnter", [data], T: typeT, frame_name: frame_name, is_constant: is_constant, parallel_iterations: parallel_iterations, name: name)
end
ref_exit(data, typeT: nil, name: "RefExit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3167
def self.ref_exit(data, typeT: nil, name: "RefExit")
  self.execute("RefExit", [data], T: typeT, name: name)
end
ref_identity(input, typeT: nil, name: "RefIdentity") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3171
def self.ref_identity(input, typeT: nil, name: "RefIdentity")
  self.execute("RefIdentity", [input], T: typeT, name: name)
end
ref_merge(inputs, typeT: nil, n: nil, name: "RefMerge") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3175
def self.ref_merge(inputs, typeT: nil, n: nil, name: "RefMerge")
  self.execute("RefMerge", [inputs], T: typeT, N: n, name: name)
end
ref_next_iteration(data, typeT: nil, name: "RefNextIteration") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3179
def self.ref_next_iteration(data, typeT: nil, name: "RefNextIteration")
  self.execute("RefNextIteration", [data], T: typeT, name: name)
end
ref_select(index, inputs, typeT: nil, n: nil, name: "RefSelect") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3183
def self.ref_select(index, inputs, typeT: nil, n: nil, name: "RefSelect")
  self.execute("RefSelect", [index, inputs], T: typeT, N: n, name: name)
end
ref_switch(data, pred, typeT: nil, name: "RefSwitch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3187
def self.ref_switch(data, pred, typeT: nil, name: "RefSwitch")
  self.execute("RefSwitch", [data, pred], T: typeT, name: name)
end
regex_full_match(input, pattern, name: "RegexFullMatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3191
def self.regex_full_match(input, pattern, name: "RegexFullMatch")
  self.execute("RegexFullMatch", [input, pattern], name: name)
end
regex_replace(input, pattern, rewrite, replace_global: true, name: "RegexReplace") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3195
def self.regex_replace(input, pattern, rewrite, replace_global: true, name: "RegexReplace")
  self.execute("RegexReplace", [input, pattern, rewrite], replace_global: replace_global, name: name)
end
relu(features, typeT: nil, name: "Relu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3199
def self.relu(features, typeT: nil, name: "Relu")
  self.execute("Relu", [features], T: typeT, name: name)
end
relu6(features, typeT: nil, name: "Relu6") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3203
def self.relu6(features, typeT: nil, name: "Relu6")
  self.execute("Relu6", [features], T: typeT, name: name)
end
relu6_grad(gradients, features, typeT: nil, name: "Relu6Grad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3207
def self.relu6_grad(gradients, features, typeT: nil, name: "Relu6Grad")
  self.execute("Relu6Grad", [gradients, features], T: typeT, name: name)
end
relu_grad(gradients, features, typeT: nil, name: "ReluGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3211
def self.relu_grad(gradients, features, typeT: nil, name: "ReluGrad")
  self.execute("ReluGrad", [gradients, features], T: typeT, name: name)
end
remote_call(target, args, tin: nil, tout: nil, f: nil, name: "RemoteCall") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3215
def self.remote_call(target, args, tin: nil, tout: nil, f: nil, name: "RemoteCall")
  self.execute("RemoteCall", [target, args], Tin: tin, Tout: tout, f: f, name: name)
end
remote_fused_graph_execute(inputs, tinputs: nil, toutputs: nil, serialized_remote_fused_graph_execute_info: "", name: "RemoteFusedGraphExecute") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3219
def self.remote_fused_graph_execute(inputs, tinputs: nil, toutputs: nil, serialized_remote_fused_graph_execute_info: "", name: "RemoteFusedGraphExecute")
  self.execute("RemoteFusedGraphExecute", [inputs], Tinputs: tinputs, Toutputs: toutputs, serialized_remote_fused_graph_execute_info: serialized_remote_fused_graph_execute_info, name: name)
end
repeat_dataset(input_dataset, count, output_types: nil, output_shapes: nil, name: "RepeatDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3223
def self.repeat_dataset(input_dataset, count, output_types: nil, output_shapes: nil, name: "RepeatDataset")
  self.execute("RepeatDataset", [input_dataset, count], output_types: output_types, output_shapes: output_shapes, name: name)
end
requantization_range(input, input_min, input_max, tinput: nil, name: "RequantizationRange") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3227
def self.requantization_range(input, input_min, input_max, tinput: nil, name: "RequantizationRange")
  self.execute("RequantizationRange", [input, input_min, input_max], Tinput: tinput, name: name)
end
requantization_range_per_channel(input, input_min, input_max, typeT: :qint32, clip_value_max: nil, name: "RequantizationRangePerChannel") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3231
def self.requantization_range_per_channel(input, input_min, input_max, typeT: :qint32, clip_value_max: nil, name: "RequantizationRangePerChannel")
  self.execute("RequantizationRangePerChannel", [input, input_min, input_max], T: typeT, clip_value_max: clip_value_max, name: name)
end
requantize(input, input_min, input_max, requested_output_min, requested_output_max, tinput: nil, out_type: nil, name: "Requantize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3235
def self.requantize(input, input_min, input_max, requested_output_min, requested_output_max, tinput: nil, out_type: nil, name: "Requantize")
  self.execute("Requantize", [input, input_min, input_max, requested_output_min, requested_output_max], Tinput: tinput, out_type: out_type, name: name)
end
requantize_per_channel(input, input_min, input_max, requested_output_min, requested_output_max, typeT: :qint32, out_type: :quint8, name: "RequantizePerChannel") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3239
def self.requantize_per_channel(input, input_min, input_max, requested_output_min, requested_output_max, typeT: :qint32, out_type: :quint8, name: "RequantizePerChannel")
  self.execute("RequantizePerChannel", [input, input_min, input_max, requested_output_min, requested_output_max], T: typeT, out_type: out_type, name: name)
end
reshape(tensor, shape, typeT: nil, tshape: :int32, name: "Reshape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3243
def self.reshape(tensor, shape, typeT: nil, tshape: :int32, name: "Reshape")
  self.execute("Reshape", [tensor, shape], T: typeT, Tshape: tshape, name: name)
end
resize_area(images, size, typeT: nil, align_corners: false, name: "ResizeArea") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3247
def self.resize_area(images, size, typeT: nil, align_corners: false, name: "ResizeArea")
  self.execute("ResizeArea", [images, size], T: typeT, align_corners: align_corners, name: name)
end
resize_bicubic(images, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBicubic") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3251
def self.resize_bicubic(images, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBicubic")
  self.execute("ResizeBicubic", [images, size], T: typeT, align_corners: align_corners, half_pixel_centers: half_pixel_centers, name: name)
end
resize_bicubic_grad(grads, original_image, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBicubicGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3255
def self.resize_bicubic_grad(grads, original_image, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBicubicGrad")
  self.execute("ResizeBicubicGrad", [grads, original_image], T: typeT, align_corners: align_corners, half_pixel_centers: half_pixel_centers, name: name)
end
resize_bilinear(images, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBilinear") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3259
def self.resize_bilinear(images, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBilinear")
  self.execute("ResizeBilinear", [images, size], T: typeT, align_corners: align_corners, half_pixel_centers: half_pixel_centers, name: name)
end
resize_bilinear_grad(grads, original_image, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBilinearGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3263
def self.resize_bilinear_grad(grads, original_image, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeBilinearGrad")
  self.execute("ResizeBilinearGrad", [grads, original_image], T: typeT, align_corners: align_corners, half_pixel_centers: half_pixel_centers, name: name)
end
resize_nearest_neighbor(images, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeNearestNeighbor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3267
def self.resize_nearest_neighbor(images, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeNearestNeighbor")
  self.execute("ResizeNearestNeighbor", [images, size], T: typeT, align_corners: align_corners, half_pixel_centers: half_pixel_centers, name: name)
end
resize_nearest_neighbor_grad(grads, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeNearestNeighborGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3271
def self.resize_nearest_neighbor_grad(grads, size, typeT: nil, align_corners: false, half_pixel_centers: false, name: "ResizeNearestNeighborGrad")
  self.execute("ResizeNearestNeighborGrad", [grads, size], T: typeT, align_corners: align_corners, half_pixel_centers: half_pixel_centers, name: name)
end
resource_accumulator_apply_gradient(handle, local_step, gradient, dtype: nil, name: "ResourceAccumulatorApplyGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3275
def self.resource_accumulator_apply_gradient(handle, local_step, gradient, dtype: nil, name: "ResourceAccumulatorApplyGradient")
  self.execute("ResourceAccumulatorApplyGradient", [handle, local_step, gradient], dtype: dtype, name: name)
end
resource_accumulator_num_accumulated(handle, name: "ResourceAccumulatorNumAccumulated") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3279
def self.resource_accumulator_num_accumulated(handle, name: "ResourceAccumulatorNumAccumulated")
  self.execute("ResourceAccumulatorNumAccumulated", [handle], name: name)
end
resource_accumulator_set_global_step(handle, new_global_step, name: "ResourceAccumulatorSetGlobalStep") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3283
def self.resource_accumulator_set_global_step(handle, new_global_step, name: "ResourceAccumulatorSetGlobalStep")
  self.execute("ResourceAccumulatorSetGlobalStep", [handle, new_global_step], name: name)
end
resource_accumulator_take_gradient(handle, num_required, dtype: nil, name: "ResourceAccumulatorTakeGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3287
def self.resource_accumulator_take_gradient(handle, num_required, dtype: nil, name: "ResourceAccumulatorTakeGradient")
  self.execute("ResourceAccumulatorTakeGradient", [handle, num_required], dtype: dtype, name: name)
end
resource_apply_ada_max(var, m, v, beta1_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyAdaMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3291
def self.resource_apply_ada_max(var, m, v, beta1_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyAdaMax")
  self.execute("ResourceApplyAdaMax", [var, m, v, beta1_power, lr, beta1, beta2, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyAdadelta") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3295
def self.resource_apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyAdadelta")
  self.execute("ResourceApplyAdadelta", [var, accum, accum_update, lr, rho, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_adagrad(var, accum, lr, grad, typeT: nil, use_locking: false, update_slots: true, name: "ResourceApplyAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3299
def self.resource_apply_adagrad(var, accum, lr, grad, typeT: nil, use_locking: false, update_slots: true, name: "ResourceApplyAdagrad")
  self.execute("ResourceApplyAdagrad", [var, accum, lr, grad], T: typeT, use_locking: use_locking, update_slots: update_slots, name: name)
end
resource_apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, lr, l1, l2, global_step, typeT: nil, use_locking: false, name: "ResourceApplyAdagradDA") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3303
def self.resource_apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, lr, l1, l2, global_step, typeT: nil, use_locking: false, name: "ResourceApplyAdagradDA")
  self.execute("ResourceApplyAdagradDA", [var, gradient_accumulator, gradient_squared_accumulator, grad, lr, l1, l2, global_step], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_adagrad_v2(var, accum, lr, epsilon, grad, typeT: nil, use_locking: false, update_slots: true, name: "ResourceApplyAdagradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3307
def self.resource_apply_adagrad_v2(var, accum, lr, epsilon, grad, typeT: nil, use_locking: false, update_slots: true, name: "ResourceApplyAdagradV2")
  self.execute("ResourceApplyAdagradV2", [var, accum, lr, epsilon, grad], T: typeT, use_locking: use_locking, update_slots: update_slots, name: name)
end
resource_apply_adam(var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, use_nesterov: false, name: "ResourceApplyAdam") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3311
def self.resource_apply_adam(var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, use_nesterov: false, name: "ResourceApplyAdam")
  self.execute("ResourceApplyAdam", [var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad], T: typeT, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
resource_apply_adam_with_amsgrad(var, m, v, vhat, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyAdamWithAmsgrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3315
def self.resource_apply_adam_with_amsgrad(var, m, v, vhat, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyAdamWithAmsgrad")
  self.execute("ResourceApplyAdamWithAmsgrad", [var, m, v, vhat, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_add_sign(var, m, lr, alpha, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ResourceApplyAddSign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3319
def self.resource_apply_add_sign(var, m, lr, alpha, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ResourceApplyAddSign")
  self.execute("ResourceApplyAddSign", [var, m, lr, alpha, sign_decay, beta, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyCenteredRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3323
def self.resource_apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyCenteredRMSProp")
  self.execute("ResourceApplyCenteredRMSProp", [var, mg, ms, mom, lr, rho, momentum, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_ftrl(var, accum, linear, grad, lr, l1, l2, lr_power, typeT: nil, use_locking: false, name: "ResourceApplyFtrl") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3327
def self.resource_apply_ftrl(var, accum, linear, grad, lr, l1, l2, lr_power, typeT: nil, use_locking: false, name: "ResourceApplyFtrl")
  self.execute("ResourceApplyFtrl", [var, accum, linear, grad, lr, l1, l2, lr_power], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_ftrl_v2(var, accum, linear, grad, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, use_locking: false, name: "ResourceApplyFtrlV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3331
def self.resource_apply_ftrl_v2(var, accum, linear, grad, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, use_locking: false, name: "ResourceApplyFtrlV2")
  self.execute("ResourceApplyFtrlV2", [var, accum, linear, grad, lr, l1, l2, l2_shrinkage, lr_power], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_gradient_descent(var, alpha, delta, typeT: nil, use_locking: false, name: "ResourceApplyGradientDescent") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3335
def self.resource_apply_gradient_descent(var, alpha, delta, typeT: nil, use_locking: false, name: "ResourceApplyGradientDescent")
  self.execute("ResourceApplyGradientDescent", [var, alpha, delta], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_keras_momentum(var, accum, lr, grad, momentum, typeT: nil, use_locking: false, use_nesterov: false, name: "ResourceApplyKerasMomentum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3339
def self.resource_apply_keras_momentum(var, accum, lr, grad, momentum, typeT: nil, use_locking: false, use_nesterov: false, name: "ResourceApplyKerasMomentum")
  self.execute("ResourceApplyKerasMomentum", [var, accum, lr, grad, momentum], T: typeT, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
resource_apply_momentum(var, accum, lr, grad, momentum, typeT: nil, use_locking: false, use_nesterov: false, name: "ResourceApplyMomentum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3343
def self.resource_apply_momentum(var, accum, lr, grad, momentum, typeT: nil, use_locking: false, use_nesterov: false, name: "ResourceApplyMomentum")
  self.execute("ResourceApplyMomentum", [var, accum, lr, grad, momentum], T: typeT, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
resource_apply_power_sign(var, m, lr, logbase, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ResourceApplyPowerSign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3347
def self.resource_apply_power_sign(var, m, lr, logbase, sign_decay, beta, grad, typeT: nil, use_locking: false, name: "ResourceApplyPowerSign")
  self.execute("ResourceApplyPowerSign", [var, m, lr, logbase, sign_decay, beta, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_proximal_adagrad(var, accum, lr, l1, l2, grad, typeT: nil, use_locking: false, name: "ResourceApplyProximalAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3351
def self.resource_apply_proximal_adagrad(var, accum, lr, l1, l2, grad, typeT: nil, use_locking: false, name: "ResourceApplyProximalAdagrad")
  self.execute("ResourceApplyProximalAdagrad", [var, accum, lr, l1, l2, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_proximal_gradient_descent(var, alpha, l1, l2, delta, typeT: nil, use_locking: false, name: "ResourceApplyProximalGradientDescent") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3355
def self.resource_apply_proximal_gradient_descent(var, alpha, l1, l2, delta, typeT: nil, use_locking: false, name: "ResourceApplyProximalGradientDescent")
  self.execute("ResourceApplyProximalGradientDescent", [var, alpha, l1, l2, delta], T: typeT, use_locking: use_locking, name: name)
end
resource_apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3359
def self.resource_apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, typeT: nil, use_locking: false, name: "ResourceApplyRMSProp")
  self.execute("ResourceApplyRMSProp", [var, ms, mom, lr, rho, momentum, epsilon, grad], T: typeT, use_locking: use_locking, name: name)
end
resource_conditional_accumulator(dtype: nil, shape: nil, container: "", shared_name: "", reduction_type: "MEAN", name: "ResourceConditionalAccumulator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3363
def self.resource_conditional_accumulator(dtype: nil, shape: nil, container: "", shared_name: "", reduction_type: "MEAN", name: "ResourceConditionalAccumulator")
  self.execute("ResourceConditionalAccumulator", [], dtype: dtype, shape: shape, container: container, shared_name: shared_name, reduction_type: reduction_type, name: name)
end
resource_count_up_to(resource, limit: nil, typeT: nil, name: "ResourceCountUpTo") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3367
def self.resource_count_up_to(resource, limit: nil, typeT: nil, name: "ResourceCountUpTo")
  self.execute("ResourceCountUpTo", [resource], limit: limit, T: typeT, name: name)
end
resource_gather(resource, indices, batch_dims: 0, validate_indices: true, dtype: nil, tindices: nil, name: "ResourceGather") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3371
def self.resource_gather(resource, indices, batch_dims: 0, validate_indices: true, dtype: nil, tindices: nil, name: "ResourceGather")
  self.execute("ResourceGather", [resource, indices], batch_dims: batch_dims, validate_indices: validate_indices, dtype: dtype, Tindices: tindices, name: name)
end
resource_gather_nd(resource, indices, dtype: nil, tindices: nil, name: "ResourceGatherNd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3375
def self.resource_gather_nd(resource, indices, dtype: nil, tindices: nil, name: "ResourceGatherNd")
  self.execute("ResourceGatherNd", [resource, indices], dtype: dtype, Tindices: tindices, name: name)
end
resource_scatter_add(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3379
def self.resource_scatter_add(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterAdd")
  self.execute("ResourceScatterAdd", [resource, indices, updates], dtype: dtype, Tindices: tindices, name: name)
end
resource_scatter_div(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterDiv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3383
def self.resource_scatter_div(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterDiv")
  self.execute("ResourceScatterDiv", [resource, indices, updates], dtype: dtype, Tindices: tindices, name: name)
end
resource_scatter_max(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3387
def self.resource_scatter_max(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterMax")
  self.execute("ResourceScatterMax", [resource, indices, updates], dtype: dtype, Tindices: tindices, name: name)
end
resource_scatter_min(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterMin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3391
def self.resource_scatter_min(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterMin")
  self.execute("ResourceScatterMin", [resource, indices, updates], dtype: dtype, Tindices: tindices, name: name)
end
resource_scatter_mul(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3395
def self.resource_scatter_mul(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterMul")
  self.execute("ResourceScatterMul", [resource, indices, updates], dtype: dtype, Tindices: tindices, name: name)
end
resource_scatter_nd_add(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ResourceScatterNdAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3399
def self.resource_scatter_nd_add(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ResourceScatterNdAdd")
  self.execute("ResourceScatterNdAdd", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_scatter_nd_sub(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ResourceScatterNdSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3403
def self.resource_scatter_nd_sub(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ResourceScatterNdSub")
  self.execute("ResourceScatterNdSub", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_scatter_nd_update(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ResourceScatterNdUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3407
def self.resource_scatter_nd_update(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ResourceScatterNdUpdate")
  self.execute("ResourceScatterNdUpdate", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_scatter_sub(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3411
def self.resource_scatter_sub(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterSub")
  self.execute("ResourceScatterSub", [resource, indices, updates], dtype: dtype, Tindices: tindices, name: name)
end
resource_scatter_update(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3415
def self.resource_scatter_update(resource, indices, updates, dtype: nil, tindices: nil, name: "ResourceScatterUpdate")
  self.execute("ResourceScatterUpdate", [resource, indices, updates], dtype: dtype, Tindices: tindices, name: name)
end
resource_sparse_apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyAdadelta") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3419
def self.resource_sparse_apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyAdadelta")
  self.execute("ResourceSparseApplyAdadelta", [var, accum, accum_update, lr, rho, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_sparse_apply_adagrad(var, accum, lr, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "ResourceSparseApplyAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3423
def self.resource_sparse_apply_adagrad(var, accum, lr, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "ResourceSparseApplyAdagrad")
  self.execute("ResourceSparseApplyAdagrad", [var, accum, lr, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, update_slots: update_slots, name: name)
end
resource_sparse_apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, indices, lr, l1, l2, global_step, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyAdagradDA") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3427
def self.resource_sparse_apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, indices, lr, l1, l2, global_step, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyAdagradDA")
  self.execute("ResourceSparseApplyAdagradDA", [var, gradient_accumulator, gradient_squared_accumulator, grad, indices, lr, l1, l2, global_step], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_sparse_apply_adagrad_v2(var, accum, lr, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "ResourceSparseApplyAdagradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3431
def self.resource_sparse_apply_adagrad_v2(var, accum, lr, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "ResourceSparseApplyAdagradV2")
  self.execute("ResourceSparseApplyAdagradV2", [var, accum, lr, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, update_slots: update_slots, name: name)
end
resource_sparse_apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyCenteredRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3435
def self.resource_sparse_apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyCenteredRMSProp")
  self.execute("ResourceSparseApplyCenteredRMSProp", [var, mg, ms, mom, lr, rho, momentum, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_sparse_apply_ftrl(var, accum, linear, grad, indices, lr, l1, l2, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyFtrl") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3439
def self.resource_sparse_apply_ftrl(var, accum, linear, grad, indices, lr, l1, l2, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyFtrl")
  self.execute("ResourceSparseApplyFtrl", [var, accum, linear, grad, indices, lr, l1, l2, lr_power], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_sparse_apply_ftrl_v2(var, accum, linear, grad, indices, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyFtrlV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3443
def self.resource_sparse_apply_ftrl_v2(var, accum, linear, grad, indices, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyFtrlV2")
  self.execute("ResourceSparseApplyFtrlV2", [var, accum, linear, grad, indices, lr, l1, l2, l2_shrinkage, lr_power], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_sparse_apply_keras_momentum(var, accum, lr, grad, indices, momentum, typeT: nil, tindices: nil, use_locking: false, use_nesterov: false, name: "ResourceSparseApplyKerasMomentum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3447
def self.resource_sparse_apply_keras_momentum(var, accum, lr, grad, indices, momentum, typeT: nil, tindices: nil, use_locking: false, use_nesterov: false, name: "ResourceSparseApplyKerasMomentum")
  self.execute("ResourceSparseApplyKerasMomentum", [var, accum, lr, grad, indices, momentum], T: typeT, Tindices: tindices, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
resource_sparse_apply_momentum(var, accum, lr, grad, indices, momentum, typeT: nil, tindices: nil, use_locking: false, use_nesterov: false, name: "ResourceSparseApplyMomentum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3451
def self.resource_sparse_apply_momentum(var, accum, lr, grad, indices, momentum, typeT: nil, tindices: nil, use_locking: false, use_nesterov: false, name: "ResourceSparseApplyMomentum")
  self.execute("ResourceSparseApplyMomentum", [var, accum, lr, grad, indices, momentum], T: typeT, Tindices: tindices, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
resource_sparse_apply_proximal_adagrad(var, accum, lr, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyProximalAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3455
def self.resource_sparse_apply_proximal_adagrad(var, accum, lr, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyProximalAdagrad")
  self.execute("ResourceSparseApplyProximalAdagrad", [var, accum, lr, l1, l2, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_sparse_apply_proximal_gradient_descent(var, alpha, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyProximalGradientDescent") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3459
def self.resource_sparse_apply_proximal_gradient_descent(var, alpha, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyProximalGradientDescent")
  self.execute("ResourceSparseApplyProximalGradientDescent", [var, alpha, l1, l2, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_sparse_apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3463
def self.resource_sparse_apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "ResourceSparseApplyRMSProp")
  self.execute("ResourceSparseApplyRMSProp", [var, ms, mom, lr, rho, momentum, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
resource_strided_slice_assign(ref, start, stop, strides, value, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "ResourceStridedSliceAssign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3467
def self.resource_strided_slice_assign(ref, start, stop, strides, value, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "ResourceStridedSliceAssign")
  self.execute("ResourceStridedSliceAssign", [ref, start, stop, strides, value], T: typeT, Index: index, begin_mask: begin_mask, end_mask: end_mask, ellipsis_mask: ellipsis_mask, new_axis_mask: new_axis_mask, shrink_axis_mask: shrink_axis_mask, name: name)
end
restore(file_pattern, tensor_name, dt: nil, preferred_shard: -1, name: "Restore") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3471
def self.restore(file_pattern, tensor_name, dt: nil, preferred_shard: -1, name: "Restore")
  self.execute("Restore", [file_pattern, tensor_name], dt: dt, preferred_shard: preferred_shard, name: name)
end
restore_slice(file_pattern, tensor_name, shape_and_slice, dt: nil, preferred_shard: -1, name: "RestoreSlice") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3475
def self.restore_slice(file_pattern, tensor_name, shape_and_slice, dt: nil, preferred_shard: -1, name: "RestoreSlice")
  self.execute("RestoreSlice", [file_pattern, tensor_name, shape_and_slice], dt: dt, preferred_shard: preferred_shard, name: name)
end
restore_v2(prefix, tensor_names, shape_and_slices, dtypes: nil, name: "RestoreV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3479
def self.restore_v2(prefix, tensor_names, shape_and_slices, dtypes: nil, name: "RestoreV2")
  self.execute("RestoreV2", [prefix, tensor_names, shape_and_slices], dtypes: dtypes, name: name)
end
retrieve_tpu_embedding_adadelta_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdadeltaParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3491
def self.retrieve_tpu_embedding_adadelta_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdadeltaParameters")
  self.execute("RetrieveTPUEmbeddingAdadeltaParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_adadelta_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3495
def self.retrieve_tpu_embedding_adadelta_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug")
  self.execute("RetrieveTPUEmbeddingAdadeltaParametersGradAccumDebug", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_adagrad_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdagradParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3499
def self.retrieve_tpu_embedding_adagrad_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdagradParameters")
  self.execute("RetrieveTPUEmbeddingAdagradParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_adagrad_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdagradParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3503
def self.retrieve_tpu_embedding_adagrad_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingAdagradParametersGradAccumDebug")
  self.execute("RetrieveTPUEmbeddingAdagradParametersGradAccumDebug", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_adam_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingADAMParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3483
def self.retrieve_tpu_embedding_adam_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingADAMParameters")
  self.execute("RetrieveTPUEmbeddingADAMParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_adam_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingADAMParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3487
def self.retrieve_tpu_embedding_adam_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingADAMParametersGradAccumDebug")
  self.execute("RetrieveTPUEmbeddingADAMParametersGradAccumDebug", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_centered_rms_prop_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingCenteredRMSPropParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3507
def self.retrieve_tpu_embedding_centered_rms_prop_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingCenteredRMSPropParameters")
  self.execute("RetrieveTPUEmbeddingCenteredRMSPropParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_ftrl_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingFTRLParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3511
def self.retrieve_tpu_embedding_ftrl_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingFTRLParameters")
  self.execute("RetrieveTPUEmbeddingFTRLParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_ftrl_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingFTRLParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3515
def self.retrieve_tpu_embedding_ftrl_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingFTRLParametersGradAccumDebug")
  self.execute("RetrieveTPUEmbeddingFTRLParametersGradAccumDebug", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_mdl_adagrad_light_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingMDLAdagradLightParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3519
def self.retrieve_tpu_embedding_mdl_adagrad_light_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingMDLAdagradLightParameters")
  self.execute("RetrieveTPUEmbeddingMDLAdagradLightParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_momentum_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingMomentumParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3523
def self.retrieve_tpu_embedding_momentum_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingMomentumParameters")
  self.execute("RetrieveTPUEmbeddingMomentumParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_momentum_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingMomentumParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3527
def self.retrieve_tpu_embedding_momentum_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingMomentumParametersGradAccumDebug")
  self.execute("RetrieveTPUEmbeddingMomentumParametersGradAccumDebug", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_proximal_adagrad_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingProximalAdagradParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3531
def self.retrieve_tpu_embedding_proximal_adagrad_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingProximalAdagradParameters")
  self.execute("RetrieveTPUEmbeddingProximalAdagradParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_proximal_adagrad_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3535
def self.retrieve_tpu_embedding_proximal_adagrad_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug")
  self.execute("RetrieveTPUEmbeddingProximalAdagradParametersGradAccumDebug", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_rms_prop_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingRMSPropParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3539
def self.retrieve_tpu_embedding_rms_prop_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingRMSPropParameters")
  self.execute("RetrieveTPUEmbeddingRMSPropParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_rms_prop_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3543
def self.retrieve_tpu_embedding_rms_prop_parameters_grad_accum_debug(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug")
  self.execute("RetrieveTPUEmbeddingRMSPropParametersGradAccumDebug", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
retrieve_tpu_embedding_stochastic_gradient_descent_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingStochasticGradientDescentParameters") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3547
def self.retrieve_tpu_embedding_stochastic_gradient_descent_parameters(table_id: -1, table_name: "", num_shards: nil, shard_id: nil, config: "", name: "RetrieveTPUEmbeddingStochasticGradientDescentParameters")
  self.execute("RetrieveTPUEmbeddingStochasticGradientDescentParameters", [], table_id: table_id, table_name: table_name, num_shards: num_shards, shard_id: shard_id, config: config, name: name)
end
reverse(tensor, dims, typeT: nil, name: "Reverse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3551
def self.reverse(tensor, dims, typeT: nil, name: "Reverse")
  self.execute("Reverse", [tensor, dims], T: typeT, name: name)
end
reverse_sequence(input, seq_lengths, seq_dim: nil, batch_dim: 0, typeT: nil, tlen: :int64, name: "ReverseSequence") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3555
def self.reverse_sequence(input, seq_lengths, seq_dim: nil, batch_dim: 0, typeT: nil, tlen: :int64, name: "ReverseSequence")
  self.execute("ReverseSequence", [input, seq_lengths], seq_dim: seq_dim, batch_dim: batch_dim, T: typeT, Tlen: tlen, name: name)
end
reverse_v2(tensor, axis, tidx: :int32, typeT: nil, name: "ReverseV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3559
def self.reverse_v2(tensor, axis, tidx: :int32, typeT: nil, name: "ReverseV2")
  self.execute("ReverseV2", [tensor, axis], Tidx: tidx, T: typeT, name: name)
end
rfft(input, fft_length, treal: :float, tcomplex: :complex64, name: "RFFT") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2959
def self.rfft(input, fft_length, treal: :float, tcomplex: :complex64, name: "RFFT")
  self.execute("RFFT", [input, fft_length], Treal: treal, Tcomplex: tcomplex, name: name)
end
rfft2_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "RFFT2D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2963
def self.rfft2_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "RFFT2D")
  self.execute("RFFT2D", [input, fft_length], Treal: treal, Tcomplex: tcomplex, name: name)
end
rfft3_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "RFFT3D") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2967
def self.rfft3_d(input, fft_length, treal: :float, tcomplex: :complex64, name: "RFFT3D")
  self.execute("RFFT3D", [input, fft_length], Treal: treal, Tcomplex: tcomplex, name: name)
end
rgb_to_hsv(images, typeT: :float, name: "RGBToHSV") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 2971
def self.rgb_to_hsv(images, typeT: :float, name: "RGBToHSV")
  self.execute("RGBToHSV", [images], T: typeT, name: name)
end
right_shift(x, y, typeT: nil, name: "RightShift") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3563
def self.right_shift(x, y, typeT: nil, name: "RightShift")
  self.execute("RightShift", [x, y], T: typeT, name: name)
end
rint(x, typeT: nil, name: "Rint") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3567
def self.rint(x, typeT: nil, name: "Rint")
  self.execute("Rint", [x], T: typeT, name: name)
end
rng_skip(resource, algorithm, delta, name: "RngSkip") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3571
def self.rng_skip(resource, algorithm, delta, name: "RngSkip")
  self.execute("RngSkip", [resource, algorithm, delta], name: name)
end
roll(input, shift, axis, typeT: nil, tshift: nil, taxis: nil, name: "Roll") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3575
def self.roll(input, shift, axis, typeT: nil, tshift: nil, taxis: nil, name: "Roll")
  self.execute("Roll", [input, shift, axis], T: typeT, Tshift: tshift, Taxis: taxis, name: name)
end
round(x, typeT: nil, name: "Round") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3579
def self.round(x, typeT: nil, name: "Round")
  self.execute("Round", [x], T: typeT, name: name)
end
rpc(address, method, request, protocol: "", fail_fast: true, timeout_in_ms: 0, name: "Rpc") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3583
def self.rpc(address, method, request, protocol: "", fail_fast: true, timeout_in_ms: 0, name: "Rpc")
  self.execute("Rpc", [address, method, request], protocol: protocol, fail_fast: fail_fast, timeout_in_ms: timeout_in_ms, name: name)
end
rsqrt(x, typeT: nil, name: "Rsqrt") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3587
def self.rsqrt(x, typeT: nil, name: "Rsqrt")
  self.execute("Rsqrt", [x], T: typeT, name: name)
end
rsqrt_grad(y, dy, typeT: nil, name: "RsqrtGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3591
def self.rsqrt_grad(y, dy, typeT: nil, name: "RsqrtGrad")
  self.execute("RsqrtGrad", [y, dy], T: typeT, name: name)
end
sample_distorted_bounding_box(image_size, bounding_boxes, typeT: nil, seed: 0, seed2: 0, min_object_covered: 0.10000000149011612, aspect_ratio_range: [], area_range: [], max_attempts: 100, use_image_if_no_bounding_boxes: false, name: "SampleDistortedBoundingBox") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3595
def self.sample_distorted_bounding_box(image_size, bounding_boxes, typeT: nil, seed: 0, seed2: 0, min_object_covered: 0.10000000149011612, aspect_ratio_range: [], area_range: [], max_attempts: 100, use_image_if_no_bounding_boxes: false, name: "SampleDistortedBoundingBox")
  self.execute("SampleDistortedBoundingBox", [image_size, bounding_boxes], T: typeT, seed: seed, seed2: seed2, min_object_covered: min_object_covered, aspect_ratio_range: aspect_ratio_range, area_range: area_range, max_attempts: max_attempts, use_image_if_no_bounding_boxes: use_image_if_no_bounding_boxes, name: name)
end
sample_distorted_bounding_box_v2(image_size, bounding_boxes, min_object_covered, typeT: nil, seed: 0, seed2: 0, aspect_ratio_range: [], area_range: [], max_attempts: 100, use_image_if_no_bounding_boxes: false, name: "SampleDistortedBoundingBoxV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3599
def self.sample_distorted_bounding_box_v2(image_size, bounding_boxes, min_object_covered, typeT: nil, seed: 0, seed2: 0, aspect_ratio_range: [], area_range: [], max_attempts: 100, use_image_if_no_bounding_boxes: false, name: "SampleDistortedBoundingBoxV2")
  self.execute("SampleDistortedBoundingBoxV2", [image_size, bounding_boxes, min_object_covered], T: typeT, seed: seed, seed2: seed2, aspect_ratio_range: aspect_ratio_range, area_range: area_range, max_attempts: max_attempts, use_image_if_no_bounding_boxes: use_image_if_no_bounding_boxes, name: name)
end
sampling_dataset(input_dataset, rate, seed, seed2, output_types: nil, output_shapes: nil, name: "SamplingDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3603
def self.sampling_dataset(input_dataset, rate, seed, seed2, output_types: nil, output_shapes: nil, name: "SamplingDataset")
  self.execute("SamplingDataset", [input_dataset, rate, seed, seed2], output_types: output_types, output_shapes: output_shapes, name: name)
end
save(filename, tensor_names, data, typeT: nil, name: "Save") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3607
def self.save(filename, tensor_names, data, typeT: nil, name: "Save")
  self.execute("Save", [filename, tensor_names, data], T: typeT, name: name)
end
save_slices(filename, tensor_names, shapes_and_slices, data, typeT: nil, name: "SaveSlices") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3611
def self.save_slices(filename, tensor_names, shapes_and_slices, data, typeT: nil, name: "SaveSlices")
  self.execute("SaveSlices", [filename, tensor_names, shapes_and_slices, data], T: typeT, name: name)
end
save_v2(prefix, tensor_names, shape_and_slices, tensors, dtypes: nil, name: "SaveV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3615
def self.save_v2(prefix, tensor_names, shape_and_slices, tensors, dtypes: nil, name: "SaveV2")
  self.execute("SaveV2", [prefix, tensor_names, shape_and_slices, tensors], dtypes: dtypes, name: name)
end
scalar_summary(tags, values, typeT: nil, name: "ScalarSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3619
def self.scalar_summary(tags, values, typeT: nil, name: "ScalarSummary")
  self.execute("ScalarSummary", [tags, values], T: typeT, name: name)
end
scale_and_translate(images, size, scale, translation, typeT: nil, kernel_type: "lanczos3", antialias: true, name: "ScaleAndTranslate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3623
def self.scale_and_translate(images, size, scale, translation, typeT: nil, kernel_type: "lanczos3", antialias: true, name: "ScaleAndTranslate")
  self.execute("ScaleAndTranslate", [images, size, scale, translation], T: typeT, kernel_type: kernel_type, antialias: antialias, name: name)
end
scale_and_translate_grad(grads, original_image, scale, translation, typeT: nil, kernel_type: "lanczos3", antialias: true, name: "ScaleAndTranslateGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3627
def self.scale_and_translate_grad(grads, original_image, scale, translation, typeT: nil, kernel_type: "lanczos3", antialias: true, name: "ScaleAndTranslateGrad")
  self.execute("ScaleAndTranslateGrad", [grads, original_image, scale, translation], T: typeT, kernel_type: kernel_type, antialias: antialias, name: name)
end
scan_dataset(input_dataset, initial_state, other_arguments, f: nil, tstate: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, use_default_device: true, name: "ScanDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3631
def self.scan_dataset(input_dataset, initial_state, other_arguments, f: nil, tstate: nil, targuments: nil, output_types: nil, output_shapes: nil, preserve_cardinality: false, use_default_device: true, name: "ScanDataset")
  self.execute("ScanDataset", [input_dataset, initial_state, other_arguments], f: f, Tstate: tstate, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, preserve_cardinality: preserve_cardinality, use_default_device: use_default_device, name: name)
end
scatter_add(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3635
def self.scatter_add(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterAdd")
  self.execute("ScatterAdd", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_div(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterDiv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3639
def self.scatter_div(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterDiv")
  self.execute("ScatterDiv", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_max(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3643
def self.scatter_max(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterMax")
  self.execute("ScatterMax", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_min(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterMin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3647
def self.scatter_min(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterMin")
  self.execute("ScatterMin", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_mul(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3651
def self.scatter_mul(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterMul")
  self.execute("ScatterMul", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_nd(indices, updates, shape, typeT: nil, tindices: nil, name: "ScatterNd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3655
def self.scatter_nd(indices, updates, shape, typeT: nil, tindices: nil, name: "ScatterNd")
  self.execute("ScatterNd", [indices, updates, shape], T: typeT, Tindices: tindices, name: name)
end
scatter_nd_add(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterNdAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3659
def self.scatter_nd_add(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterNdAdd")
  self.execute("ScatterNdAdd", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_nd_non_aliasing_add(input, indices, updates, typeT: nil, tindices: nil, name: "ScatterNdNonAliasingAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3663
def self.scatter_nd_non_aliasing_add(input, indices, updates, typeT: nil, tindices: nil, name: "ScatterNdNonAliasingAdd")
  self.execute("ScatterNdNonAliasingAdd", [input, indices, updates], T: typeT, Tindices: tindices, name: name)
end
scatter_nd_sub(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterNdSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3667
def self.scatter_nd_sub(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterNdSub")
  self.execute("ScatterNdSub", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_nd_update(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ScatterNdUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3671
def self.scatter_nd_update(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ScatterNdUpdate")
  self.execute("ScatterNdUpdate", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_sub(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3675
def self.scatter_sub(ref, indices, updates, typeT: nil, tindices: nil, use_locking: false, name: "ScatterSub")
  self.execute("ScatterSub", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
scatter_update(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ScatterUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3679
def self.scatter_update(ref, indices, updates, typeT: nil, tindices: nil, use_locking: true, name: "ScatterUpdate")
  self.execute("ScatterUpdate", [ref, indices, updates], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sdca_fprint(input, name: "SdcaFprint") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3683
def self.sdca_fprint(input, name: "SdcaFprint")
  self.execute("SdcaFprint", [input], name: name)
end
sdca_optimizer(sparse_example_indices, sparse_feature_indices, sparse_feature_values, dense_features, example_weights, example_labels, sparse_indices, sparse_weights, dense_weights, example_state_data, loss_type: nil, adaptative: false, num_sparse_features: nil, num_sparse_features_with_values: nil, num_dense_features: nil, l1: nil, l2: nil, num_loss_partitions: nil, num_inner_iterations: nil, name: "SdcaOptimizer") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3687
def self.sdca_optimizer(sparse_example_indices, sparse_feature_indices, sparse_feature_values, dense_features, example_weights, example_labels, sparse_indices, sparse_weights, dense_weights, example_state_data, loss_type: nil, adaptative: false, num_sparse_features: nil, num_sparse_features_with_values: nil, num_dense_features: nil, l1: nil, l2: nil, num_loss_partitions: nil, num_inner_iterations: nil, name: "SdcaOptimizer")
  self.execute("SdcaOptimizer", [sparse_example_indices, sparse_feature_indices, sparse_feature_values, dense_features, example_weights, example_labels, sparse_indices, sparse_weights, dense_weights, example_state_data], loss_type: loss_type, adaptative: adaptative, num_sparse_features: num_sparse_features, num_sparse_features_with_values: num_sparse_features_with_values, num_dense_features: num_dense_features, l1: l1, l2: l2, num_loss_partitions: num_loss_partitions, num_inner_iterations: num_inner_iterations, name: name)
end
sdca_optimizer_v2(sparse_example_indices, sparse_feature_indices, sparse_feature_values, dense_features, example_weights, example_labels, sparse_indices, sparse_weights, dense_weights, example_state_data, loss_type: nil, adaptive: false, num_sparse_features: nil, num_sparse_features_with_values: nil, num_dense_features: nil, l1: nil, l2: nil, num_loss_partitions: nil, num_inner_iterations: nil, name: "SdcaOptimizerV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3691
def self.sdca_optimizer_v2(sparse_example_indices, sparse_feature_indices, sparse_feature_values, dense_features, example_weights, example_labels, sparse_indices, sparse_weights, dense_weights, example_state_data, loss_type: nil, adaptive: false, num_sparse_features: nil, num_sparse_features_with_values: nil, num_dense_features: nil, l1: nil, l2: nil, num_loss_partitions: nil, num_inner_iterations: nil, name: "SdcaOptimizerV2")
  self.execute("SdcaOptimizerV2", [sparse_example_indices, sparse_feature_indices, sparse_feature_values, dense_features, example_weights, example_labels, sparse_indices, sparse_weights, dense_weights, example_state_data], loss_type: loss_type, adaptive: adaptive, num_sparse_features: num_sparse_features, num_sparse_features_with_values: num_sparse_features_with_values, num_dense_features: num_dense_features, l1: l1, l2: l2, num_loss_partitions: num_loss_partitions, num_inner_iterations: num_inner_iterations, name: name)
end
sdca_shrink_l1(weights, num_features: nil, l1: nil, l2: nil, name: "SdcaShrinkL1") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3695
def self.sdca_shrink_l1(weights, num_features: nil, l1: nil, l2: nil, name: "SdcaShrinkL1")
  self.execute("SdcaShrinkL1", [weights], num_features: num_features, l1: l1, l2: l2, name: name)
end
segment_max(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3699
def self.segment_max(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentMax")
  self.execute("SegmentMax", [data, segment_ids], T: typeT, Tindices: tindices, name: name)
end
segment_mean(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentMean") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3703
def self.segment_mean(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentMean")
  self.execute("SegmentMean", [data, segment_ids], T: typeT, Tindices: tindices, name: name)
end
segment_min(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentMin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3707
def self.segment_min(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentMin")
  self.execute("SegmentMin", [data, segment_ids], T: typeT, Tindices: tindices, name: name)
end
segment_prod(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentProd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3711
def self.segment_prod(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentProd")
  self.execute("SegmentProd", [data, segment_ids], T: typeT, Tindices: tindices, name: name)
end
segment_sum(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentSum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3715
def self.segment_sum(data, segment_ids, typeT: nil, tindices: nil, name: "SegmentSum")
  self.execute("SegmentSum", [data, segment_ids], T: typeT, Tindices: tindices, name: name)
end
select(condition, t, e, typeT: nil, name: "Select") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3719
def self.select(condition, t, e, typeT: nil, name: "Select")
  self.execute("Select", [condition, t, e], T: typeT, name: name)
end
select_v2(condition, t, e, typeT: nil, name: "SelectV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3723
def self.select_v2(condition, t, e, typeT: nil, name: "SelectV2")
  self.execute("SelectV2", [condition, t, e], T: typeT, name: name)
end
self_adjoint_eig(input, typeT: nil, name: "SelfAdjointEig") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3727
def self.self_adjoint_eig(input, typeT: nil, name: "SelfAdjointEig")
  self.execute("SelfAdjointEig", [input], T: typeT, name: name)
end
self_adjoint_eig_v2(input, compute_v: true, typeT: nil, name: "SelfAdjointEigV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3731
def self.self_adjoint_eig_v2(input, compute_v: true, typeT: nil, name: "SelfAdjointEigV2")
  self.execute("SelfAdjointEigV2", [input], compute_v: compute_v, T: typeT, name: name)
end
selu(features, typeT: nil, name: "Selu") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3735
def self.selu(features, typeT: nil, name: "Selu")
  self.execute("Selu", [features], T: typeT, name: name)
end
selu_grad(gradients, outputs, typeT: nil, name: "SeluGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3739
def self.selu_grad(gradients, outputs, typeT: nil, name: "SeluGrad")
  self.execute("SeluGrad", [gradients, outputs], T: typeT, name: name)
end
send(tensor, typeT: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "Send") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3743
def self.send(tensor, typeT: nil, tensor_name: "", send_device: "", send_device_incarnation: nil, recv_device: "", client_terminated: false, name: "Send")
  self.execute("Send", [tensor], T: typeT, tensor_name: tensor_name, send_device: send_device, send_device_incarnation: send_device_incarnation, recv_device: recv_device, client_terminated: client_terminated, name: name)
end
send_tpu_embedding_gradients(inputs, learning_rates, n: nil, nn: 0, config: "", name: "SendTPUEmbeddingGradients") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3747
def self.send_tpu_embedding_gradients(inputs, learning_rates, n: nil, nn: 0, config: "", name: "SendTPUEmbeddingGradients")
  self.execute("SendTPUEmbeddingGradients", [inputs, learning_rates], N: n, NN: nn, config: config, name: name)
end
serialize_iterator(resource_handle, name: "SerializeIterator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3751
def self.serialize_iterator(resource_handle, name: "SerializeIterator")
  self.execute("SerializeIterator", [resource_handle], name: name)
end
serialize_many_sparse(sparse_indices, sparse_values, sparse_shape, typeT: nil, out_type: :string, name: "SerializeManySparse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3755
def self.serialize_many_sparse(sparse_indices, sparse_values, sparse_shape, typeT: nil, out_type: :string, name: "SerializeManySparse")
  self.execute("SerializeManySparse", [sparse_indices, sparse_values, sparse_shape], T: typeT, out_type: out_type, name: name)
end
serialize_sparse(sparse_indices, sparse_values, sparse_shape, typeT: nil, out_type: :string, name: "SerializeSparse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3759
def self.serialize_sparse(sparse_indices, sparse_values, sparse_shape, typeT: nil, out_type: :string, name: "SerializeSparse")
  self.execute("SerializeSparse", [sparse_indices, sparse_values, sparse_shape], T: typeT, out_type: out_type, name: name)
end
serialize_tensor(tensor, typeT: nil, name: "SerializeTensor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3763
def self.serialize_tensor(tensor, typeT: nil, name: "SerializeTensor")
  self.execute("SerializeTensor", [tensor], T: typeT, name: name)
end
set_size(set_indices, set_values, set_shape, validate_indices: true, typeT: nil, name: "SetSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3767
def self.set_size(set_indices, set_values, set_shape, validate_indices: true, typeT: nil, name: "SetSize")
  self.execute("SetSize", [set_indices, set_values, set_shape], validate_indices: validate_indices, T: typeT, name: name)
end
set_stats_aggregator_dataset(input_dataset, stats_aggregator, tag, counter_prefix, output_types: nil, output_shapes: nil, name: "SetStatsAggregatorDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3771
def self.set_stats_aggregator_dataset(input_dataset, stats_aggregator, tag, counter_prefix, output_types: nil, output_shapes: nil, name: "SetStatsAggregatorDataset")
  self.execute("SetStatsAggregatorDataset", [input_dataset, stats_aggregator, tag, counter_prefix], output_types: output_types, output_shapes: output_shapes, name: name)
end
shape(input, typeT: nil, out_type: :int32, name: "Shape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3775
def self.shape(input, typeT: nil, out_type: :int32, name: "Shape")
  self.execute("Shape", [input], T: typeT, out_type: out_type, name: name)
end
shape_n(input, n: nil, typeT: nil, out_type: :int32, name: "ShapeN") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3779
def self.shape_n(input, n: nil, typeT: nil, out_type: :int32, name: "ShapeN")
  self.execute("ShapeN", [input], N: n, T: typeT, out_type: out_type, name: name)
end
shard_dataset(input_dataset, num_shards, index, require_non_empty: false, output_types: nil, output_shapes: nil, name: "ShardDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3783
def self.shard_dataset(input_dataset, num_shards, index, require_non_empty: false, output_types: nil, output_shapes: nil, name: "ShardDataset")
  self.execute("ShardDataset", [input_dataset, num_shards, index], require_non_empty: require_non_empty, output_types: output_types, output_shapes: output_shapes, name: name)
end
sharded_filename(basename, shard, num_shards, name: "ShardedFilename") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3787
def self.sharded_filename(basename, shard, num_shards, name: "ShardedFilename")
  self.execute("ShardedFilename", [basename, shard, num_shards], name: name)
end
sharded_filespec(basename, num_shards, name: "ShardedFilespec") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3791
def self.sharded_filespec(basename, num_shards, name: "ShardedFilespec")
  self.execute("ShardedFilespec", [basename, num_shards], name: name)
end
shuffle_and_repeat_dataset(input_dataset, buffer_size, seed, seed2, count, output_types: nil, output_shapes: nil, name: "ShuffleAndRepeatDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3795
def self.shuffle_and_repeat_dataset(input_dataset, buffer_size, seed, seed2, count, output_types: nil, output_shapes: nil, name: "ShuffleAndRepeatDataset")
  self.execute("ShuffleAndRepeatDataset", [input_dataset, buffer_size, seed, seed2, count], output_types: output_types, output_shapes: output_shapes, name: name)
end
shuffle_dataset(input_dataset, buffer_size, seed, seed2, reshuffle_each_iteration: true, output_types: nil, output_shapes: nil, name: "ShuffleDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3799
def self.shuffle_dataset(input_dataset, buffer_size, seed, seed2, reshuffle_each_iteration: true, output_types: nil, output_shapes: nil, name: "ShuffleDataset")
  self.execute("ShuffleDataset", [input_dataset, buffer_size, seed, seed2], reshuffle_each_iteration: reshuffle_each_iteration, output_types: output_types, output_shapes: output_shapes, name: name)
end
shuffle_dataset_v2(input_dataset, buffer_size, seed_generator, output_types: nil, output_shapes: nil, name: "ShuffleDatasetV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3803
def self.shuffle_dataset_v2(input_dataset, buffer_size, seed_generator, output_types: nil, output_shapes: nil, name: "ShuffleDatasetV2")
  self.execute("ShuffleDatasetV2", [input_dataset, buffer_size, seed_generator], output_types: output_types, output_shapes: output_shapes, name: name)
end
shutdown_distributed_tpu(name: "ShutdownDistributedTPU") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3807
def self.shutdown_distributed_tpu(name: "ShutdownDistributedTPU")
  self.execute("ShutdownDistributedTPU", [], name: name)
end
sigmoid(x, typeT: nil, name: "Sigmoid") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3811
def self.sigmoid(x, typeT: nil, name: "Sigmoid")
  self.execute("Sigmoid", [x], T: typeT, name: name)
end
sigmoid_grad(y, dy, typeT: nil, name: "SigmoidGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3815
def self.sigmoid_grad(y, dy, typeT: nil, name: "SigmoidGrad")
  self.execute("SigmoidGrad", [y, dy], T: typeT, name: name)
end
sign(x, typeT: nil, name: "Sign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3819
def self.sign(x, typeT: nil, name: "Sign")
  self.execute("Sign", [x], T: typeT, name: name)
end
sin(x, typeT: nil, name: "Sin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3823
def self.sin(x, typeT: nil, name: "Sin")
  self.execute("Sin", [x], T: typeT, name: name)
end
sinh(x, typeT: nil, name: "Sinh") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3827
def self.sinh(x, typeT: nil, name: "Sinh")
  self.execute("Sinh", [x], T: typeT, name: name)
end
size(input, typeT: nil, out_type: :int32, name: "Size") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3831
def self.size(input, typeT: nil, out_type: :int32, name: "Size")
  self.execute("Size", [input], T: typeT, out_type: out_type, name: name)
end
skip_dataset(input_dataset, count, output_types: nil, output_shapes: nil, name: "SkipDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3835
def self.skip_dataset(input_dataset, count, output_types: nil, output_shapes: nil, name: "SkipDataset")
  self.execute("SkipDataset", [input_dataset, count], output_types: output_types, output_shapes: output_shapes, name: name)
end
skipgram(filename: "", batch_size: nil, window_size: 5, min_count: 5, subsample: 0.0010000000474974513, name: "Skipgram") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3839
def self.skipgram(filename: "", batch_size: nil, window_size: 5, min_count: 5, subsample: 0.0010000000474974513, name: "Skipgram")
  self.execute("Skipgram", [], filename: filename, batch_size: batch_size, window_size: window_size, min_count: min_count, subsample: subsample, name: name)
end
sleep_dataset(input_dataset, sleep_microseconds, output_types: nil, output_shapes: nil, name: "SleepDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3843
def self.sleep_dataset(input_dataset, sleep_microseconds, output_types: nil, output_shapes: nil, name: "SleepDataset")
  self.execute("SleepDataset", [input_dataset, sleep_microseconds], output_types: output_types, output_shapes: output_shapes, name: name)
end
slice(input, start, size, typeT: nil, index: nil, name: "Slice") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3847
def self.slice(input, start, size, typeT: nil, index: nil, name: "Slice")
  self.execute("Slice", [input, start, size], T: typeT, Index: index, name: name)
end
sliding_window_dataset(input_dataset, window_size, window_shift, window_stride, output_types: nil, output_shapes: nil, name: "SlidingWindowDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3851
def self.sliding_window_dataset(input_dataset, window_size, window_shift, window_stride, output_types: nil, output_shapes: nil, name: "SlidingWindowDataset")
  self.execute("SlidingWindowDataset", [input_dataset, window_size, window_shift, window_stride], output_types: output_types, output_shapes: output_shapes, name: name)
end
snapshot(input, typeT: nil, name: "Snapshot") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3855
def self.snapshot(input, typeT: nil, name: "Snapshot")
  self.execute("Snapshot", [input], T: typeT, name: name)
end
snapshot_dataset(input_dataset, path, output_types: nil, output_shapes: nil, compression: "", reader_path_prefix: "", writer_path_prefix: "", shard_size_bytes: 10737418240, pending_snapshot_expiry_seconds: 86400, num_reader_threads: 1, reader_buffer_size: 1, num_writer_threads: 1, writer_buffer_size: 1, shuffle_on_read: false, seed: 0, seed2: 0, name: "SnapshotDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3859
def self.snapshot_dataset(input_dataset, path, output_types: nil, output_shapes: nil, compression: "", reader_path_prefix: "", writer_path_prefix: "", shard_size_bytes: 10737418240, pending_snapshot_expiry_seconds: 86400, num_reader_threads: 1, reader_buffer_size: 1, num_writer_threads: 1, writer_buffer_size: 1, shuffle_on_read: false, seed: 0, seed2: 0, name: "SnapshotDataset")
  self.execute("SnapshotDataset", [input_dataset, path], output_types: output_types, output_shapes: output_shapes, compression: compression, reader_path_prefix: reader_path_prefix, writer_path_prefix: writer_path_prefix, shard_size_bytes: shard_size_bytes, pending_snapshot_expiry_seconds: pending_snapshot_expiry_seconds, num_reader_threads: num_reader_threads, reader_buffer_size: reader_buffer_size, num_writer_threads: num_writer_threads, writer_buffer_size: writer_buffer_size, shuffle_on_read: shuffle_on_read, seed: seed, seed2: seed2, name: name)
end
softmax(logits, typeT: nil, name: "Softmax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3863
def self.softmax(logits, typeT: nil, name: "Softmax")
  self.execute("Softmax", [logits], T: typeT, name: name)
end
softmax_cross_entropy_with_logits(features, labels, typeT: nil, name: "SoftmaxCrossEntropyWithLogits") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3867
def self.softmax_cross_entropy_with_logits(features, labels, typeT: nil, name: "SoftmaxCrossEntropyWithLogits")
  self.execute("SoftmaxCrossEntropyWithLogits", [features, labels], T: typeT, name: name)
end
softplus(features, typeT: nil, name: "Softplus") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3871
def self.softplus(features, typeT: nil, name: "Softplus")
  self.execute("Softplus", [features], T: typeT, name: name)
end
softplus_grad(gradients, features, typeT: nil, name: "SoftplusGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3875
def self.softplus_grad(gradients, features, typeT: nil, name: "SoftplusGrad")
  self.execute("SoftplusGrad", [gradients, features], T: typeT, name: name)
end
softsign(features, typeT: nil, name: "Softsign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3879
def self.softsign(features, typeT: nil, name: "Softsign")
  self.execute("Softsign", [features], T: typeT, name: name)
end
softsign_grad(gradients, features, typeT: nil, name: "SoftsignGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3883
def self.softsign_grad(gradients, features, typeT: nil, name: "SoftsignGrad")
  self.execute("SoftsignGrad", [gradients, features], T: typeT, name: name)
end
space_to_batch(input, paddings, typeT: nil, tpaddings: :int32, block_size: nil, name: "SpaceToBatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3887
def self.space_to_batch(input, paddings, typeT: nil, tpaddings: :int32, block_size: nil, name: "SpaceToBatch")
  self.execute("SpaceToBatch", [input, paddings], T: typeT, Tpaddings: tpaddings, block_size: block_size, name: name)
end
space_to_batch_nd(input, block_shape, paddings, typeT: nil, tblock_shape: :int32, tpaddings: :int32, name: "SpaceToBatchND") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3891
def self.space_to_batch_nd(input, block_shape, paddings, typeT: nil, tblock_shape: :int32, tpaddings: :int32, name: "SpaceToBatchND")
  self.execute("SpaceToBatchND", [input, block_shape, paddings], T: typeT, Tblock_shape: tblock_shape, Tpaddings: tpaddings, name: name)
end
space_to_depth(input, typeT: nil, block_size: nil, data_format: "NHWC", name: "SpaceToDepth") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3895
def self.space_to_depth(input, typeT: nil, block_size: nil, data_format: "NHWC", name: "SpaceToDepth")
  self.execute("SpaceToDepth", [input], T: typeT, block_size: block_size, data_format: data_format, name: name)
end
sparse_accumulator_apply_gradient(handle, local_step, gradient_indices, gradient_values, gradient_shape, dtype: nil, has_known_shape: nil, name: "SparseAccumulatorApplyGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3899
def self.sparse_accumulator_apply_gradient(handle, local_step, gradient_indices, gradient_values, gradient_shape, dtype: nil, has_known_shape: nil, name: "SparseAccumulatorApplyGradient")
  self.execute("SparseAccumulatorApplyGradient", [handle, local_step, gradient_indices, gradient_values, gradient_shape], dtype: dtype, has_known_shape: has_known_shape, name: name)
end
sparse_accumulator_take_gradient(handle, num_required, dtype: nil, name: "SparseAccumulatorTakeGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3903
def self.sparse_accumulator_take_gradient(handle, num_required, dtype: nil, name: "SparseAccumulatorTakeGradient")
  self.execute("SparseAccumulatorTakeGradient", [handle, num_required], dtype: dtype, name: name)
end
sparse_add(a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh, typeT: nil, treal: nil, name: "SparseAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3907
def self.sparse_add(a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh, typeT: nil, treal: nil, name: "SparseAdd")
  self.execute("SparseAdd", [a_indices, a_values, a_shape, b_indices, b_values, b_shape, thresh], T: typeT, Treal: treal, name: name)
end
sparse_add_grad(backprop_val_grad, a_indices, b_indices, sum_indices, typeT: nil, name: "SparseAddGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3911
def self.sparse_add_grad(backprop_val_grad, a_indices, b_indices, sum_indices, typeT: nil, name: "SparseAddGrad")
  self.execute("SparseAddGrad", [backprop_val_grad, a_indices, b_indices, sum_indices], T: typeT, name: name)
end
sparse_apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyAdadelta") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3915
def self.sparse_apply_adadelta(var, accum, accum_update, lr, rho, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyAdadelta")
  self.execute("SparseApplyAdadelta", [var, accum, accum_update, lr, rho, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_apply_adagrad(var, accum, lr, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "SparseApplyAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3919
def self.sparse_apply_adagrad(var, accum, lr, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "SparseApplyAdagrad")
  self.execute("SparseApplyAdagrad", [var, accum, lr, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, update_slots: update_slots, name: name)
end
sparse_apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, indices, lr, l1, l2, global_step, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyAdagradDA") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3923
def self.sparse_apply_adagrad_da(var, gradient_accumulator, gradient_squared_accumulator, grad, indices, lr, l1, l2, global_step, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyAdagradDA")
  self.execute("SparseApplyAdagradDA", [var, gradient_accumulator, gradient_squared_accumulator, grad, indices, lr, l1, l2, global_step], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_apply_adagrad_v2(var, accum, lr, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "SparseApplyAdagradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3927
def self.sparse_apply_adagrad_v2(var, accum, lr, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, update_slots: true, name: "SparseApplyAdagradV2")
  self.execute("SparseApplyAdagradV2", [var, accum, lr, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, update_slots: update_slots, name: name)
end
sparse_apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyCenteredRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3931
def self.sparse_apply_centered_rms_prop(var, mg, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyCenteredRMSProp")
  self.execute("SparseApplyCenteredRMSProp", [var, mg, ms, mom, lr, rho, momentum, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_apply_ftrl(var, accum, linear, grad, indices, lr, l1, l2, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyFtrl") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3935
def self.sparse_apply_ftrl(var, accum, linear, grad, indices, lr, l1, l2, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyFtrl")
  self.execute("SparseApplyFtrl", [var, accum, linear, grad, indices, lr, l1, l2, lr_power], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_apply_ftrl_v2(var, accum, linear, grad, indices, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyFtrlV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3939
def self.sparse_apply_ftrl_v2(var, accum, linear, grad, indices, lr, l1, l2, l2_shrinkage, lr_power, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyFtrlV2")
  self.execute("SparseApplyFtrlV2", [var, accum, linear, grad, indices, lr, l1, l2, l2_shrinkage, lr_power], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_apply_momentum(var, accum, lr, grad, indices, momentum, typeT: nil, tindices: nil, use_locking: false, use_nesterov: false, name: "SparseApplyMomentum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3943
def self.sparse_apply_momentum(var, accum, lr, grad, indices, momentum, typeT: nil, tindices: nil, use_locking: false, use_nesterov: false, name: "SparseApplyMomentum")
  self.execute("SparseApplyMomentum", [var, accum, lr, grad, indices, momentum], T: typeT, Tindices: tindices, use_locking: use_locking, use_nesterov: use_nesterov, name: name)
end
sparse_apply_proximal_adagrad(var, accum, lr, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyProximalAdagrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3947
def self.sparse_apply_proximal_adagrad(var, accum, lr, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyProximalAdagrad")
  self.execute("SparseApplyProximalAdagrad", [var, accum, lr, l1, l2, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_apply_proximal_gradient_descent(var, alpha, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyProximalGradientDescent") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3951
def self.sparse_apply_proximal_gradient_descent(var, alpha, l1, l2, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyProximalGradientDescent")
  self.execute("SparseApplyProximalGradientDescent", [var, alpha, l1, l2, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyRMSProp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3955
def self.sparse_apply_rms_prop(var, ms, mom, lr, rho, momentum, epsilon, grad, indices, typeT: nil, tindices: nil, use_locking: false, name: "SparseApplyRMSProp")
  self.execute("SparseApplyRMSProp", [var, ms, mom, lr, rho, momentum, epsilon, grad, indices], T: typeT, Tindices: tindices, use_locking: use_locking, name: name)
end
sparse_concat(indices, values, shapes, concat_dim: nil, n: nil, typeT: nil, name: "SparseConcat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3959
def self.sparse_concat(indices, values, shapes, concat_dim: nil, n: nil, typeT: nil, name: "SparseConcat")
  self.execute("SparseConcat", [indices, values, shapes], concat_dim: concat_dim, N: n, T: typeT, name: name)
end
sparse_conditional_accumulator(dtype: nil, shape: nil, container: "", shared_name: "", reduction_type: "MEAN", name: "SparseConditionalAccumulator") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3963
def self.sparse_conditional_accumulator(dtype: nil, shape: nil, container: "", shared_name: "", reduction_type: "MEAN", name: "SparseConditionalAccumulator")
  self.execute("SparseConditionalAccumulator", [], dtype: dtype, shape: shape, container: container, shared_name: shared_name, reduction_type: reduction_type, name: name)
end
sparse_cross(indices, values, shapes, dense_inputs, n: nil, hashed_output: nil, num_buckets: nil, hash_key: nil, sparse_types: nil, dense_types: nil, out_type: nil, internal_type: nil, name: "SparseCross") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3967
def self.sparse_cross(indices, values, shapes, dense_inputs, n: nil, hashed_output: nil, num_buckets: nil, hash_key: nil, sparse_types: nil, dense_types: nil, out_type: nil, internal_type: nil, name: "SparseCross")
  self.execute("SparseCross", [indices, values, shapes, dense_inputs], N: n, hashed_output: hashed_output, num_buckets: num_buckets, hash_key: hash_key, sparse_types: sparse_types, dense_types: dense_types, out_type: out_type, internal_type: internal_type, name: name)
end
sparse_dense_cwise_add(sp_indices, sp_values, sp_shape, dense, typeT: nil, name: "SparseDenseCwiseAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3971
def self.sparse_dense_cwise_add(sp_indices, sp_values, sp_shape, dense, typeT: nil, name: "SparseDenseCwiseAdd")
  self.execute("SparseDenseCwiseAdd", [sp_indices, sp_values, sp_shape, dense], T: typeT, name: name)
end
sparse_dense_cwise_div(sp_indices, sp_values, sp_shape, dense, typeT: nil, name: "SparseDenseCwiseDiv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3975
def self.sparse_dense_cwise_div(sp_indices, sp_values, sp_shape, dense, typeT: nil, name: "SparseDenseCwiseDiv")
  self.execute("SparseDenseCwiseDiv", [sp_indices, sp_values, sp_shape, dense], T: typeT, name: name)
end
sparse_dense_cwise_mul(sp_indices, sp_values, sp_shape, dense, typeT: nil, name: "SparseDenseCwiseMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3979
def self.sparse_dense_cwise_mul(sp_indices, sp_values, sp_shape, dense, typeT: nil, name: "SparseDenseCwiseMul")
  self.execute("SparseDenseCwiseMul", [sp_indices, sp_values, sp_shape, dense], T: typeT, name: name)
end
sparse_fill_empty_rows(indices, values, dense_shape, default_value, typeT: nil, name: "SparseFillEmptyRows") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3983
def self.sparse_fill_empty_rows(indices, values, dense_shape, default_value, typeT: nil, name: "SparseFillEmptyRows")
  self.execute("SparseFillEmptyRows", [indices, values, dense_shape, default_value], T: typeT, name: name)
end
sparse_fill_empty_rows_grad(reverse_index_map, grad_values, typeT: nil, name: "SparseFillEmptyRowsGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3987
def self.sparse_fill_empty_rows_grad(reverse_index_map, grad_values, typeT: nil, name: "SparseFillEmptyRowsGrad")
  self.execute("SparseFillEmptyRowsGrad", [reverse_index_map, grad_values], T: typeT, name: name)
end
sparse_mat_mul(a, b, transpose_a: false, transpose_b: false, a_is_sparse: false, b_is_sparse: false, ta: :float, tb: :float, name: "SparseMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3991
def self.sparse_mat_mul(a, b, transpose_a: false, transpose_b: false, a_is_sparse: false, b_is_sparse: false, ta: :float, tb: :float, name: "SparseMatMul")
  self.execute("SparseMatMul", [a, b], transpose_a: transpose_a, transpose_b: transpose_b, a_is_sparse: a_is_sparse, b_is_sparse: b_is_sparse, Ta: ta, Tb: tb, name: name)
end
sparse_matrix_add(a, b, alpha, beta, typeT: nil, name: "SparseMatrixAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3995
def self.sparse_matrix_add(a, b, alpha, beta, typeT: nil, name: "SparseMatrixAdd")
  self.execute("SparseMatrixAdd", [a, b, alpha, beta], T: typeT, name: name)
end
sparse_matrix_mat_mul(a, b, typeT: nil, transpose_a: false, transpose_b: false, adjoint_a: false, adjoint_b: false, transpose_output: false, conjugate_output: false, name: "SparseMatrixMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 3999
def self.sparse_matrix_mat_mul(a, b, typeT: nil, transpose_a: false, transpose_b: false, adjoint_a: false, adjoint_b: false, transpose_output: false, conjugate_output: false, name: "SparseMatrixMatMul")
  self.execute("SparseMatrixMatMul", [a, b], T: typeT, transpose_a: transpose_a, transpose_b: transpose_b, adjoint_a: adjoint_a, adjoint_b: adjoint_b, transpose_output: transpose_output, conjugate_output: conjugate_output, name: name)
end
sparse_matrix_mul(a, b, typeT: nil, name: "SparseMatrixMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4003
def self.sparse_matrix_mul(a, b, typeT: nil, name: "SparseMatrixMul")
  self.execute("SparseMatrixMul", [a, b], T: typeT, name: name)
end
sparse_matrix_nnz(sparse_matrix, name: "SparseMatrixNNZ") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4007
def self.sparse_matrix_nnz(sparse_matrix, name: "SparseMatrixNNZ")
  self.execute("SparseMatrixNNZ", [sparse_matrix], name: name)
end
sparse_matrix_ordering_amd(input, name: "SparseMatrixOrderingAMD") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4011
def self.sparse_matrix_ordering_amd(input, name: "SparseMatrixOrderingAMD")
  self.execute("SparseMatrixOrderingAMD", [input], name: name)
end
sparse_matrix_softmax(logits, type: nil, name: "SparseMatrixSoftmax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4015
def self.sparse_matrix_softmax(logits, type: nil, name: "SparseMatrixSoftmax")
  self.execute("SparseMatrixSoftmax", [logits], type: type, name: name)
end
sparse_matrix_softmax_grad(softmax, grad_softmax, type: nil, name: "SparseMatrixSoftmaxGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4019
def self.sparse_matrix_softmax_grad(softmax, grad_softmax, type: nil, name: "SparseMatrixSoftmaxGrad")
  self.execute("SparseMatrixSoftmaxGrad", [softmax, grad_softmax], type: type, name: name)
end
sparse_matrix_sparse_cholesky(input, permutation, type: nil, name: "SparseMatrixSparseCholesky") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4023
def self.sparse_matrix_sparse_cholesky(input, permutation, type: nil, name: "SparseMatrixSparseCholesky")
  self.execute("SparseMatrixSparseCholesky", [input, permutation], type: type, name: name)
end
sparse_matrix_sparse_mat_mul(a, b, type: nil, transpose_a: false, transpose_b: false, adjoint_a: false, adjoint_b: false, name: "SparseMatrixSparseMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4027
def self.sparse_matrix_sparse_mat_mul(a, b, type: nil, transpose_a: false, transpose_b: false, adjoint_a: false, adjoint_b: false, name: "SparseMatrixSparseMatMul")
  self.execute("SparseMatrixSparseMatMul", [a, b], type: type, transpose_a: transpose_a, transpose_b: transpose_b, adjoint_a: adjoint_a, adjoint_b: adjoint_b, name: name)
end
sparse_matrix_transpose(input, conjugate: false, type: nil, name: "SparseMatrixTranspose") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4031
def self.sparse_matrix_transpose(input, conjugate: false, type: nil, name: "SparseMatrixTranspose")
  self.execute("SparseMatrixTranspose", [input], conjugate: conjugate, type: type, name: name)
end
sparse_matrix_zeros(dense_shape, type: nil, name: "SparseMatrixZeros") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4035
def self.sparse_matrix_zeros(dense_shape, type: nil, name: "SparseMatrixZeros")
  self.execute("SparseMatrixZeros", [dense_shape], type: type, name: name)
end
sparse_reduce_max(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4039
def self.sparse_reduce_max(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceMax")
  self.execute("SparseReduceMax", [input_indices, input_values, input_shape, reduction_axes], keep_dims: keep_dims, T: typeT, name: name)
end
sparse_reduce_max_sparse(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceMaxSparse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4043
def self.sparse_reduce_max_sparse(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceMaxSparse")
  self.execute("SparseReduceMaxSparse", [input_indices, input_values, input_shape, reduction_axes], keep_dims: keep_dims, T: typeT, name: name)
end
sparse_reduce_sum(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceSum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4047
def self.sparse_reduce_sum(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceSum")
  self.execute("SparseReduceSum", [input_indices, input_values, input_shape, reduction_axes], keep_dims: keep_dims, T: typeT, name: name)
end
sparse_reduce_sum_sparse(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceSumSparse") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4051
def self.sparse_reduce_sum_sparse(input_indices, input_values, input_shape, reduction_axes, keep_dims: false, typeT: nil, name: "SparseReduceSumSparse")
  self.execute("SparseReduceSumSparse", [input_indices, input_values, input_shape, reduction_axes], keep_dims: keep_dims, T: typeT, name: name)
end
sparse_reorder(input_indices, input_values, input_shape, typeT: nil, name: "SparseReorder") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4055
def self.sparse_reorder(input_indices, input_values, input_shape, typeT: nil, name: "SparseReorder")
  self.execute("SparseReorder", [input_indices, input_values, input_shape], T: typeT, name: name)
end
sparse_reshape(input_indices, input_shape, new_shape, name: "SparseReshape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4059
def self.sparse_reshape(input_indices, input_shape, new_shape, name: "SparseReshape")
  self.execute("SparseReshape", [input_indices, input_shape, new_shape], name: name)
end
sparse_segment_mean(data, indices, segment_ids, typeT: nil, tidx: :int32, name: "SparseSegmentMean") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4063
def self.sparse_segment_mean(data, indices, segment_ids, typeT: nil, tidx: :int32, name: "SparseSegmentMean")
  self.execute("SparseSegmentMean", [data, indices, segment_ids], T: typeT, Tidx: tidx, name: name)
end
sparse_segment_mean_grad(grad, indices, segment_ids, output_dim0, typeT: nil, tidx: :int32, name: "SparseSegmentMeanGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4067
def self.sparse_segment_mean_grad(grad, indices, segment_ids, output_dim0, typeT: nil, tidx: :int32, name: "SparseSegmentMeanGrad")
  self.execute("SparseSegmentMeanGrad", [grad, indices, segment_ids, output_dim0], T: typeT, Tidx: tidx, name: name)
end
sparse_segment_mean_with_num_segments(data, indices, segment_ids, num_segments, typeT: nil, tidx: :int32, tnumsegments: :int32, name: "SparseSegmentMeanWithNumSegments") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4071
def self.sparse_segment_mean_with_num_segments(data, indices, segment_ids, num_segments, typeT: nil, tidx: :int32, tnumsegments: :int32, name: "SparseSegmentMeanWithNumSegments")
  self.execute("SparseSegmentMeanWithNumSegments", [data, indices, segment_ids, num_segments], T: typeT, Tidx: tidx, Tnumsegments: tnumsegments, name: name)
end
sparse_segment_sqrt_n(data, indices, segment_ids, typeT: nil, tidx: :int32, name: "SparseSegmentSqrtN") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4075
def self.sparse_segment_sqrt_n(data, indices, segment_ids, typeT: nil, tidx: :int32, name: "SparseSegmentSqrtN")
  self.execute("SparseSegmentSqrtN", [data, indices, segment_ids], T: typeT, Tidx: tidx, name: name)
end
sparse_segment_sqrt_n_grad(grad, indices, segment_ids, output_dim0, typeT: nil, tidx: :int32, name: "SparseSegmentSqrtNGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4079
def self.sparse_segment_sqrt_n_grad(grad, indices, segment_ids, output_dim0, typeT: nil, tidx: :int32, name: "SparseSegmentSqrtNGrad")
  self.execute("SparseSegmentSqrtNGrad", [grad, indices, segment_ids, output_dim0], T: typeT, Tidx: tidx, name: name)
end
sparse_segment_sqrt_n_with_num_segments(data, indices, segment_ids, num_segments, typeT: nil, tidx: :int32, tnumsegments: :int32, name: "SparseSegmentSqrtNWithNumSegments") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4083
def self.sparse_segment_sqrt_n_with_num_segments(data, indices, segment_ids, num_segments, typeT: nil, tidx: :int32, tnumsegments: :int32, name: "SparseSegmentSqrtNWithNumSegments")
  self.execute("SparseSegmentSqrtNWithNumSegments", [data, indices, segment_ids, num_segments], T: typeT, Tidx: tidx, Tnumsegments: tnumsegments, name: name)
end
sparse_segment_sum(data, indices, segment_ids, typeT: nil, tidx: :int32, name: "SparseSegmentSum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4087
def self.sparse_segment_sum(data, indices, segment_ids, typeT: nil, tidx: :int32, name: "SparseSegmentSum")
  self.execute("SparseSegmentSum", [data, indices, segment_ids], T: typeT, Tidx: tidx, name: name)
end
sparse_segment_sum_with_num_segments(data, indices, segment_ids, num_segments, typeT: nil, tidx: :int32, tnumsegments: :int32, name: "SparseSegmentSumWithNumSegments") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4091
def self.sparse_segment_sum_with_num_segments(data, indices, segment_ids, num_segments, typeT: nil, tidx: :int32, tnumsegments: :int32, name: "SparseSegmentSumWithNumSegments")
  self.execute("SparseSegmentSumWithNumSegments", [data, indices, segment_ids, num_segments], T: typeT, Tidx: tidx, Tnumsegments: tnumsegments, name: name)
end
sparse_slice(indices, values, shape, start, size, typeT: nil, name: "SparseSlice") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4095
def self.sparse_slice(indices, values, shape, start, size, typeT: nil, name: "SparseSlice")
  self.execute("SparseSlice", [indices, values, shape, start, size], T: typeT, name: name)
end
sparse_slice_grad(backprop_val_grad, input_indices, input_start, output_indices, typeT: nil, name: "SparseSliceGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4099
def self.sparse_slice_grad(backprop_val_grad, input_indices, input_start, output_indices, typeT: nil, name: "SparseSliceGrad")
  self.execute("SparseSliceGrad", [backprop_val_grad, input_indices, input_start, output_indices], T: typeT, name: name)
end
sparse_softmax(sp_indices, sp_values, sp_shape, typeT: nil, name: "SparseSoftmax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4103
def self.sparse_softmax(sp_indices, sp_values, sp_shape, typeT: nil, name: "SparseSoftmax")
  self.execute("SparseSoftmax", [sp_indices, sp_values, sp_shape], T: typeT, name: name)
end
sparse_softmax_cross_entropy_with_logits(features, labels, typeT: nil, tlabels: :int64, name: "SparseSoftmaxCrossEntropyWithLogits") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4107
def self.sparse_softmax_cross_entropy_with_logits(features, labels, typeT: nil, tlabels: :int64, name: "SparseSoftmaxCrossEntropyWithLogits")
  self.execute("SparseSoftmaxCrossEntropyWithLogits", [features, labels], T: typeT, Tlabels: tlabels, name: name)
end
sparse_sparse_maximum(a_indices, a_values, a_shape, b_indices, b_values, b_shape, typeT: nil, name: "SparseSparseMaximum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4111
def self.sparse_sparse_maximum(a_indices, a_values, a_shape, b_indices, b_values, b_shape, typeT: nil, name: "SparseSparseMaximum")
  self.execute("SparseSparseMaximum", [a_indices, a_values, a_shape, b_indices, b_values, b_shape], T: typeT, name: name)
end
sparse_sparse_minimum(a_indices, a_values, a_shape, b_indices, b_values, b_shape, typeT: nil, name: "SparseSparseMinimum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4115
def self.sparse_sparse_minimum(a_indices, a_values, a_shape, b_indices, b_values, b_shape, typeT: nil, name: "SparseSparseMinimum")
  self.execute("SparseSparseMinimum", [a_indices, a_values, a_shape, b_indices, b_values, b_shape], T: typeT, name: name)
end
sparse_split(split_dim, indices, values, shape, num_split: nil, typeT: nil, name: "SparseSplit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4119
def self.sparse_split(split_dim, indices, values, shape, num_split: nil, typeT: nil, name: "SparseSplit")
  self.execute("SparseSplit", [split_dim, indices, values, shape], num_split: num_split, T: typeT, name: name)
end
sparse_tensor_dense_add(a_indices, a_values, a_shape, b, typeT: nil, tindices: nil, name: "SparseTensorDenseAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4123
def self.sparse_tensor_dense_add(a_indices, a_values, a_shape, b, typeT: nil, tindices: nil, name: "SparseTensorDenseAdd")
  self.execute("SparseTensorDenseAdd", [a_indices, a_values, a_shape, b], T: typeT, Tindices: tindices, name: name)
end
sparse_tensor_dense_mat_mul(a_indices, a_values, a_shape, b, typeT: nil, tindices: :int64, adjoint_a: false, adjoint_b: false, name: "SparseTensorDenseMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4127
def self.sparse_tensor_dense_mat_mul(a_indices, a_values, a_shape, b, typeT: nil, tindices: :int64, adjoint_a: false, adjoint_b: false, name: "SparseTensorDenseMatMul")
  self.execute("SparseTensorDenseMatMul", [a_indices, a_values, a_shape, b], T: typeT, Tindices: tindices, adjoint_a: adjoint_a, adjoint_b: adjoint_b, name: name)
end
sparse_tensor_slice_dataset(indices, values, dense_shape, tvalues: nil, name: "SparseTensorSliceDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4131
def self.sparse_tensor_slice_dataset(indices, values, dense_shape, tvalues: nil, name: "SparseTensorSliceDataset")
  self.execute("SparseTensorSliceDataset", [indices, values, dense_shape], Tvalues: tvalues, name: name)
end
sparse_tensor_to_csr_sparse_matrix(indices, values, dense_shape, typeT: nil, name: "SparseTensorToCSRSparseMatrix") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4135
def self.sparse_tensor_to_csr_sparse_matrix(indices, values, dense_shape, typeT: nil, name: "SparseTensorToCSRSparseMatrix")
  self.execute("SparseTensorToCSRSparseMatrix", [indices, values, dense_shape], T: typeT, name: name)
end
sparse_to_dense(sparse_indices, output_shape, sparse_values, default_value, validate_indices: true, typeT: nil, tindices: nil, name: "SparseToDense") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4139
def self.sparse_to_dense(sparse_indices, output_shape, sparse_values, default_value, validate_indices: true, typeT: nil, tindices: nil, name: "SparseToDense")
  self.execute("SparseToDense", [sparse_indices, output_shape, sparse_values, default_value], validate_indices: validate_indices, T: typeT, Tindices: tindices, name: name)
end
sparse_to_sparse_set_operation(set1_indices, set1_values, set1_shape, set2_indices, set2_values, set2_shape, set_operation: "", validate_indices: true, typeT: nil, name: "SparseToSparseSetOperation") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4143
def self.sparse_to_sparse_set_operation(set1_indices, set1_values, set1_shape, set2_indices, set2_values, set2_shape, set_operation: "", validate_indices: true, typeT: nil, name: "SparseToSparseSetOperation")
  self.execute("SparseToSparseSetOperation", [set1_indices, set1_values, set1_shape, set2_indices, set2_values, set2_shape], set_operation: set_operation, validate_indices: validate_indices, T: typeT, name: name)
end
split(split_dim, value, num_split: nil, typeT: nil, name: "Split") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4147
def self.split(split_dim, value, num_split: nil, typeT: nil, name: "Split")
  self.execute("Split", [split_dim, value], num_split: num_split, T: typeT, name: name)
end
split_v(value, size_splits, split_dim, num_split: nil, typeT: nil, tlen: :int64, name: "SplitV") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4151
def self.split_v(value, size_splits, split_dim, num_split: nil, typeT: nil, tlen: :int64, name: "SplitV")
  self.execute("SplitV", [value, size_splits, split_dim], num_split: num_split, T: typeT, Tlen: tlen, name: name)
end
sql_dataset(driver_name, data_source_name, query, output_types: nil, output_shapes: nil, name: "SqlDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4155
def self.sql_dataset(driver_name, data_source_name, query, output_types: nil, output_shapes: nil, name: "SqlDataset")
  self.execute("SqlDataset", [driver_name, data_source_name, query], output_types: output_types, output_shapes: output_shapes, name: name)
end
sqrt(x, typeT: nil, name: "Sqrt") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4159
def self.sqrt(x, typeT: nil, name: "Sqrt")
  self.execute("Sqrt", [x], T: typeT, name: name)
end
sqrt_grad(y, dy, typeT: nil, name: "SqrtGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4163
def self.sqrt_grad(y, dy, typeT: nil, name: "SqrtGrad")
  self.execute("SqrtGrad", [y, dy], T: typeT, name: name)
end
square(x, typeT: nil, name: "Square") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4167
def self.square(x, typeT: nil, name: "Square")
  self.execute("Square", [x], T: typeT, name: name)
end
squared_difference(x, y, typeT: nil, name: "SquaredDifference") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4171
def self.squared_difference(x, y, typeT: nil, name: "SquaredDifference")
  self.execute("SquaredDifference", [x, y], T: typeT, name: name)
end
squeeze(input, typeT: nil, squeeze_dims: [], name: "Squeeze") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4175
def self.squeeze(input, typeT: nil, squeeze_dims: [], name: "Squeeze")
  self.execute("Squeeze", [input], T: typeT, squeeze_dims: squeeze_dims, name: name)
end
stack(elem_type: nil, stack_name: "", name: "Stack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4179
def self.stack(elem_type: nil, stack_name: "", name: "Stack")
  self.execute("Stack", [], elem_type: elem_type, stack_name: stack_name, name: name)
end
stack_close(handle, name: "StackClose") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4183
def self.stack_close(handle, name: "StackClose")
  self.execute("StackClose", [handle], name: name)
end
stack_close_v2(handle, name: "StackCloseV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4187
def self.stack_close_v2(handle, name: "StackCloseV2")
  self.execute("StackCloseV2", [handle], name: name)
end
stack_pop(handle, elem_type: nil, name: "StackPop") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4191
def self.stack_pop(handle, elem_type: nil, name: "StackPop")
  self.execute("StackPop", [handle], elem_type: elem_type, name: name)
end
stack_pop_v2(handle, elem_type: nil, name: "StackPopV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4195
def self.stack_pop_v2(handle, elem_type: nil, name: "StackPopV2")
  self.execute("StackPopV2", [handle], elem_type: elem_type, name: name)
end
stack_push(handle, elem, typeT: nil, swap_memory: false, name: "StackPush") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4199
def self.stack_push(handle, elem, typeT: nil, swap_memory: false, name: "StackPush")
  self.execute("StackPush", [handle, elem], T: typeT, swap_memory: swap_memory, name: name)
end
stack_push_v2(handle, elem, typeT: nil, swap_memory: false, name: "StackPushV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4203
def self.stack_push_v2(handle, elem, typeT: nil, swap_memory: false, name: "StackPushV2")
  self.execute("StackPushV2", [handle, elem], T: typeT, swap_memory: swap_memory, name: name)
end
stack_v2(max_size, elem_type: nil, stack_name: "", name: "StackV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4207
def self.stack_v2(max_size, elem_type: nil, stack_name: "", name: "StackV2")
  self.execute("StackV2", [max_size], elem_type: elem_type, stack_name: stack_name, name: name)
end
stage(values, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "Stage") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4211
def self.stage(values, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "Stage")
  self.execute("Stage", [values], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
stage_clear(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "StageClear") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4215
def self.stage_clear(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "StageClear")
  self.execute("StageClear", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
stage_peek(index, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "StagePeek") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4219
def self.stage_peek(index, capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "StagePeek")
  self.execute("StagePeek", [index], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
stage_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "StageSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4223
def self.stage_size(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "StageSize")
  self.execute("StageSize", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
stateful_partitioned_call(args, tin: nil, tout: nil, f: nil, config: "", config_proto: "", executor_type: "", name: "StatefulPartitionedCall") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4227
def self.stateful_partitioned_call(args, tin: nil, tout: nil, f: nil, config: "", config_proto: "", executor_type: "", name: "StatefulPartitionedCall")
  self.execute("StatefulPartitionedCall", [args], Tin: tin, Tout: tout, f: f, config: config, config_proto: config_proto, executor_type: executor_type, name: name)
end
stateful_random_binomial(resource, algorithm, shape, counts, probs, s: nil, typeT: :double, dtype: :int64, name: "StatefulRandomBinomial") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4231
def self.stateful_random_binomial(resource, algorithm, shape, counts, probs, s: nil, typeT: :double, dtype: :int64, name: "StatefulRandomBinomial")
  self.execute("StatefulRandomBinomial", [resource, algorithm, shape, counts, probs], S: s, T: typeT, dtype: dtype, name: name)
end
stateful_standard_normal(resource, shape, dtype: :float, shape_dtype: :int64, name: "StatefulStandardNormal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4235
def self.stateful_standard_normal(resource, shape, dtype: :float, shape_dtype: :int64, name: "StatefulStandardNormal")
  self.execute("StatefulStandardNormal", [resource, shape], dtype: dtype, shape_dtype: shape_dtype, name: name)
end
stateful_standard_normal_v2(resource, algorithm, shape, dtype: :float, shape_dtype: :int64, name: "StatefulStandardNormalV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4239
def self.stateful_standard_normal_v2(resource, algorithm, shape, dtype: :float, shape_dtype: :int64, name: "StatefulStandardNormalV2")
  self.execute("StatefulStandardNormalV2", [resource, algorithm, shape], dtype: dtype, shape_dtype: shape_dtype, name: name)
end
stateful_truncated_normal(resource, algorithm, shape, dtype: :float, shape_dtype: :int64, name: "StatefulTruncatedNormal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4243
def self.stateful_truncated_normal(resource, algorithm, shape, dtype: :float, shape_dtype: :int64, name: "StatefulTruncatedNormal")
  self.execute("StatefulTruncatedNormal", [resource, algorithm, shape], dtype: dtype, shape_dtype: shape_dtype, name: name)
end
stateful_uniform(resource, algorithm, shape, dtype: :float, shape_dtype: :int64, name: "StatefulUniform") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4247
def self.stateful_uniform(resource, algorithm, shape, dtype: :float, shape_dtype: :int64, name: "StatefulUniform")
  self.execute("StatefulUniform", [resource, algorithm, shape], dtype: dtype, shape_dtype: shape_dtype, name: name)
end
stateful_uniform_full_int(resource, algorithm, shape, dtype: :uint64, shape_dtype: :int64, name: "StatefulUniformFullInt") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4251
def self.stateful_uniform_full_int(resource, algorithm, shape, dtype: :uint64, shape_dtype: :int64, name: "StatefulUniformFullInt")
  self.execute("StatefulUniformFullInt", [resource, algorithm, shape], dtype: dtype, shape_dtype: shape_dtype, name: name)
end
stateful_uniform_int(resource, algorithm, shape, minval, maxval, dtype: :int64, shape_dtype: :int64, name: "StatefulUniformInt") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4255
def self.stateful_uniform_int(resource, algorithm, shape, minval, maxval, dtype: :int64, shape_dtype: :int64, name: "StatefulUniformInt")
  self.execute("StatefulUniformInt", [resource, algorithm, shape, minval, maxval], dtype: dtype, shape_dtype: shape_dtype, name: name)
end
stateless_if(cond, input, tcond: nil, tin: nil, tout: nil, then_branch: nil, else_branch: nil, output_shapes: [], name: "StatelessIf") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4259
def self.stateless_if(cond, input, tcond: nil, tin: nil, tout: nil, then_branch: nil, else_branch: nil, output_shapes: [], name: "StatelessIf")
  self.execute("StatelessIf", [cond, input], Tcond: tcond, Tin: tin, Tout: tout, then_branch: then_branch, else_branch: else_branch, output_shapes: output_shapes, name: name)
end
stateless_multinomial(logits, num_samples, seed, typeT: nil, tseed: :int64, output_dtype: :int64, name: "StatelessMultinomial") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4263
def self.stateless_multinomial(logits, num_samples, seed, typeT: nil, tseed: :int64, output_dtype: :int64, name: "StatelessMultinomial")
  self.execute("StatelessMultinomial", [logits, num_samples, seed], T: typeT, Tseed: tseed, output_dtype: output_dtype, name: name)
end
stateless_random_normal(shape, seed, dtype: :float, typeT: :int32, tseed: :int64, name: "StatelessRandomNormal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4267
def self.stateless_random_normal(shape, seed, dtype: :float, typeT: :int32, tseed: :int64, name: "StatelessRandomNormal")
  self.execute("StatelessRandomNormal", [shape, seed], dtype: dtype, T: typeT, Tseed: tseed, name: name)
end
stateless_random_uniform(shape, seed, dtype: :float, typeT: :int32, tseed: :int64, name: "StatelessRandomUniform") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4271
def self.stateless_random_uniform(shape, seed, dtype: :float, typeT: :int32, tseed: :int64, name: "StatelessRandomUniform")
  self.execute("StatelessRandomUniform", [shape, seed], dtype: dtype, T: typeT, Tseed: tseed, name: name)
end
stateless_random_uniform_int(shape, seed, minval, maxval, dtype: nil, typeT: nil, tseed: :int64, name: "StatelessRandomUniformInt") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4275
def self.stateless_random_uniform_int(shape, seed, minval, maxval, dtype: nil, typeT: nil, tseed: :int64, name: "StatelessRandomUniformInt")
  self.execute("StatelessRandomUniformInt", [shape, seed, minval, maxval], dtype: dtype, T: typeT, Tseed: tseed, name: name)
end
stateless_truncated_normal(shape, seed, dtype: :float, typeT: :int32, tseed: :int64, name: "StatelessTruncatedNormal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4279
def self.stateless_truncated_normal(shape, seed, dtype: :float, typeT: :int32, tseed: :int64, name: "StatelessTruncatedNormal")
  self.execute("StatelessTruncatedNormal", [shape, seed], dtype: dtype, T: typeT, Tseed: tseed, name: name)
end
stateless_while(input, typeT: nil, cond: nil, body: nil, output_shapes: [], parallel_iterations: 10, name: "StatelessWhile") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4283
def self.stateless_while(input, typeT: nil, cond: nil, body: nil, output_shapes: [], parallel_iterations: 10, name: "StatelessWhile")
  self.execute("StatelessWhile", [input], T: typeT, cond: cond, body: body, output_shapes: output_shapes, parallel_iterations: parallel_iterations, name: name)
end
static_regex_full_match(input, pattern: "", name: "StaticRegexFullMatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4287
def self.static_regex_full_match(input, pattern: "", name: "StaticRegexFullMatch")
  self.execute("StaticRegexFullMatch", [input], pattern: pattern, name: name)
end
static_regex_replace(input, pattern: "", rewrite: "", replace_global: true, name: "StaticRegexReplace") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4291
def self.static_regex_replace(input, pattern: "", rewrite: "", replace_global: true, name: "StaticRegexReplace")
  self.execute("StaticRegexReplace", [input], pattern: pattern, rewrite: rewrite, replace_global: replace_global, name: name)
end
stats_aggregator_handle(container: "", shared_name: "", name: "StatsAggregatorHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4295
def self.stats_aggregator_handle(container: "", shared_name: "", name: "StatsAggregatorHandle")
  self.execute("StatsAggregatorHandle", [], container: container, shared_name: shared_name, name: name)
end
stats_aggregator_handle_v2(container: "", shared_name: "", name: "StatsAggregatorHandleV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4299
def self.stats_aggregator_handle_v2(container: "", shared_name: "", name: "StatsAggregatorHandleV2")
  self.execute("StatsAggregatorHandleV2", [], container: container, shared_name: shared_name, name: name)
end
stats_aggregator_set_summary_writer(stats_aggregator, summary, name: "StatsAggregatorSetSummaryWriter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4303
def self.stats_aggregator_set_summary_writer(stats_aggregator, summary, name: "StatsAggregatorSetSummaryWriter")
  self.execute("StatsAggregatorSetSummaryWriter", [stats_aggregator, summary], name: name)
end
stats_aggregator_summary(iterator, name: "StatsAggregatorSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4307
def self.stats_aggregator_summary(iterator, name: "StatsAggregatorSummary")
  self.execute("StatsAggregatorSummary", [iterator], name: name)
end
stop_gradient(input, typeT: nil, name: "StopGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4311
def self.stop_gradient(input, typeT: nil, name: "StopGradient")
  self.execute("StopGradient", [input], T: typeT, name: name)
end
strided_slice(input, start, stop, strides, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "StridedSlice") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4315
def self.strided_slice(input, start, stop, strides, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "StridedSlice")
  self.execute("StridedSlice", [input, start, stop, strides], T: typeT, Index: index, begin_mask: begin_mask, end_mask: end_mask, ellipsis_mask: ellipsis_mask, new_axis_mask: new_axis_mask, shrink_axis_mask: shrink_axis_mask, name: name)
end
strided_slice_assign(ref, start, stop, strides, value, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "StridedSliceAssign") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4319
def self.strided_slice_assign(ref, start, stop, strides, value, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "StridedSliceAssign")
  self.execute("StridedSliceAssign", [ref, start, stop, strides, value], T: typeT, Index: index, begin_mask: begin_mask, end_mask: end_mask, ellipsis_mask: ellipsis_mask, new_axis_mask: new_axis_mask, shrink_axis_mask: shrink_axis_mask, name: name)
end
strided_slice_grad(shape, start, stop, strides, dy, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "StridedSliceGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4323
def self.strided_slice_grad(shape, start, stop, strides, dy, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "StridedSliceGrad")
  self.execute("StridedSliceGrad", [shape, start, stop, strides, dy], T: typeT, Index: index, begin_mask: begin_mask, end_mask: end_mask, ellipsis_mask: ellipsis_mask, new_axis_mask: new_axis_mask, shrink_axis_mask: shrink_axis_mask, name: name)
end
string_format(inputs, typeT: nil, template: "%s", placeholder: "%s", summarize: 3, name: "StringFormat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4327
def self.string_format(inputs, typeT: nil, template: "%s", placeholder: "%s", summarize: 3, name: "StringFormat")
  self.execute("StringFormat", [inputs], T: typeT, template: template, placeholder: placeholder, summarize: summarize, name: name)
end
string_join(inputs, n: nil, separator: "", name: "StringJoin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4331
def self.string_join(inputs, n: nil, separator: "", name: "StringJoin")
  self.execute("StringJoin", [inputs], N: n, separator: separator, name: name)
end
string_length(input, unit: "BYTE", name: "StringLength") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4335
def self.string_length(input, unit: "BYTE", name: "StringLength")
  self.execute("StringLength", [input], unit: unit, name: name)
end
string_lower(input, encoding: "", name: "StringLower") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4339
def self.string_lower(input, encoding: "", name: "StringLower")
  self.execute("StringLower", [input], encoding: encoding, name: name)
end
string_n_grams(data, data_splits, separator: "", ngram_widths: nil, left_pad: "", right_pad: "", pad_width: nil, preserve_short_sequences: nil, tsplits: :int64, name: "StringNGrams") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4343
def self.string_n_grams(data, data_splits, separator: "", ngram_widths: nil, left_pad: "", right_pad: "", pad_width: nil, preserve_short_sequences: nil, tsplits: :int64, name: "StringNGrams")
  self.execute("StringNGrams", [data, data_splits], separator: separator, ngram_widths: ngram_widths, left_pad: left_pad, right_pad: right_pad, pad_width: pad_width, preserve_short_sequences: preserve_short_sequences, Tsplits: tsplits, name: name)
end
string_split(input, delimiter, skip_empty: true, name: "StringSplit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4347
def self.string_split(input, delimiter, skip_empty: true, name: "StringSplit")
  self.execute("StringSplit", [input, delimiter], skip_empty: skip_empty, name: name)
end
string_split_v2(input, sep, maxsplit: -1, name: "StringSplitV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4351
def self.string_split_v2(input, sep, maxsplit: -1, name: "StringSplitV2")
  self.execute("StringSplitV2", [input, sep], maxsplit: maxsplit, name: name)
end
string_strip(input, name: "StringStrip") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4355
def self.string_strip(input, name: "StringStrip")
  self.execute("StringStrip", [input], name: name)
end
string_to_hash_bucket(string_tensor, num_buckets: nil, name: "StringToHashBucket") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4359
def self.string_to_hash_bucket(string_tensor, num_buckets: nil, name: "StringToHashBucket")
  self.execute("StringToHashBucket", [string_tensor], num_buckets: num_buckets, name: name)
end
string_to_hash_bucket_fast(input, num_buckets: nil, name: "StringToHashBucketFast") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4363
def self.string_to_hash_bucket_fast(input, num_buckets: nil, name: "StringToHashBucketFast")
  self.execute("StringToHashBucketFast", [input], num_buckets: num_buckets, name: name)
end
string_to_hash_bucket_strong(input, num_buckets: nil, key: nil, name: "StringToHashBucketStrong") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4367
def self.string_to_hash_bucket_strong(input, num_buckets: nil, key: nil, name: "StringToHashBucketStrong")
  self.execute("StringToHashBucketStrong", [input], num_buckets: num_buckets, key: key, name: name)
end
string_to_number(string_tensor, out_type: :float, name: "StringToNumber") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4371
def self.string_to_number(string_tensor, out_type: :float, name: "StringToNumber")
  self.execute("StringToNumber", [string_tensor], out_type: out_type, name: name)
end
string_upper(input, encoding: "", name: "StringUpper") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4375
def self.string_upper(input, encoding: "", name: "StringUpper")
  self.execute("StringUpper", [input], encoding: encoding, name: name)
end
sub(x, y, typeT: nil, name: "Sub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4379
def self.sub(x, y, typeT: nil, name: "Sub")
  self.execute("Sub", [x, y], T: typeT, name: name)
end
substr(input, pos, len, typeT: nil, unit: "BYTE", name: "Substr") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4383
def self.substr(input, pos, len, typeT: nil, unit: "BYTE", name: "Substr")
  self.execute("Substr", [input, pos, len], T: typeT, unit: unit, name: name)
end
sum(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Sum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4387
def self.sum(input, reduction_indices, keep_dims: false, typeT: nil, tidx: :int32, name: "Sum")
  self.execute("Sum", [input, reduction_indices], keep_dims: keep_dims, T: typeT, Tidx: tidx, name: name)
end
summary_writer(shared_name: "", container: "", name: "SummaryWriter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4391
def self.summary_writer(shared_name: "", container: "", name: "SummaryWriter")
  self.execute("SummaryWriter", [], shared_name: shared_name, container: container, name: name)
end
svd(input, compute_uv: true, full_matrices: false, typeT: nil, name: "Svd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4395
def self.svd(input, compute_uv: true, full_matrices: false, typeT: nil, name: "Svd")
  self.execute("Svd", [input], compute_uv: compute_uv, full_matrices: full_matrices, T: typeT, name: name)
end
switch(data, pred, typeT: nil, name: "Switch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4399
def self.switch(data, pred, typeT: nil, name: "Switch")
  self.execute("Switch", [data, pred], T: typeT, name: name)
end
symbolic_gradient(input, tin: nil, tout: nil, f: nil, name: "SymbolicGradient") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4403
def self.symbolic_gradient(input, tin: nil, tout: nil, f: nil, name: "SymbolicGradient")
  self.execute("SymbolicGradient", [input], Tin: tin, Tout: tout, f: f, name: name)
end
take_dataset(input_dataset, count, output_types: nil, output_shapes: nil, name: "TakeDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4447
def self.take_dataset(input_dataset, count, output_types: nil, output_shapes: nil, name: "TakeDataset")
  self.execute("TakeDataset", [input_dataset, count], output_types: output_types, output_shapes: output_shapes, name: name)
end
take_many_sparse_from_tensors_map(sparse_handles, dtype: nil, container: "", shared_name: "", name: "TakeManySparseFromTensorsMap") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4451
def self.take_many_sparse_from_tensors_map(sparse_handles, dtype: nil, container: "", shared_name: "", name: "TakeManySparseFromTensorsMap")
  self.execute("TakeManySparseFromTensorsMap", [sparse_handles], dtype: dtype, container: container, shared_name: shared_name, name: name)
end
take_while_dataset(input_dataset, other_arguments, predicate: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "TakeWhileDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4455
def self.take_while_dataset(input_dataset, other_arguments, predicate: nil, targuments: nil, output_types: nil, output_shapes: nil, name: "TakeWhileDataset")
  self.execute("TakeWhileDataset", [input_dataset, other_arguments], predicate: predicate, Targuments: targuments, output_types: output_types, output_shapes: output_shapes, name: name)
end
tan(x, typeT: nil, name: "Tan") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4459
def self.tan(x, typeT: nil, name: "Tan")
  self.execute("Tan", [x], T: typeT, name: name)
end
tanh(x, typeT: nil, name: "Tanh") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4463
def self.tanh(x, typeT: nil, name: "Tanh")
  self.execute("Tanh", [x], T: typeT, name: name)
end
tanh_grad(y, dy, typeT: nil, name: "TanhGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4467
def self.tanh_grad(y, dy, typeT: nil, name: "TanhGrad")
  self.execute("TanhGrad", [y, dy], T: typeT, name: name)
end
temporary_variable(shape: nil, dtype: nil, var_name: "", name: "TemporaryVariable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4471
def self.temporary_variable(shape: nil, dtype: nil, var_name: "", name: "TemporaryVariable")
  self.execute("TemporaryVariable", [], shape: shape, dtype: dtype, var_name: var_name, name: name)
end
tensor_array(size, dtype: nil, dynamic_size: false, clear_after_read: true, tensor_array_name: "", element_shape: [], name: "TensorArray") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4475
def self.tensor_array(size, dtype: nil, dynamic_size: false, clear_after_read: true, tensor_array_name: "", element_shape: [], name: "TensorArray")
  self.execute("TensorArray", [size], dtype: dtype, dynamic_size: dynamic_size, clear_after_read: clear_after_read, tensor_array_name: tensor_array_name, element_shape: element_shape, name: name)
end
tensor_array_close(handle, name: "TensorArrayClose") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4479
def self.tensor_array_close(handle, name: "TensorArrayClose")
  self.execute("TensorArrayClose", [handle], name: name)
end
tensor_array_close_v2(handle, name: "TensorArrayCloseV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4483
def self.tensor_array_close_v2(handle, name: "TensorArrayCloseV2")
  self.execute("TensorArrayCloseV2", [handle], name: name)
end
tensor_array_close_v3(handle, name: "TensorArrayCloseV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4487
def self.tensor_array_close_v3(handle, name: "TensorArrayCloseV3")
  self.execute("TensorArrayCloseV3", [handle], name: name)
end
tensor_array_concat(handle, flow_in, dtype: nil, element_shape_except0: [], name: "TensorArrayConcat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4491
def self.tensor_array_concat(handle, flow_in, dtype: nil, element_shape_except0: [], name: "TensorArrayConcat")
  self.execute("TensorArrayConcat", [handle, flow_in], dtype: dtype, element_shape_except0: element_shape_except0, name: name)
end
tensor_array_concat_v2(handle, flow_in, dtype: nil, element_shape_except0: [], name: "TensorArrayConcatV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4495
def self.tensor_array_concat_v2(handle, flow_in, dtype: nil, element_shape_except0: [], name: "TensorArrayConcatV2")
  self.execute("TensorArrayConcatV2", [handle, flow_in], dtype: dtype, element_shape_except0: element_shape_except0, name: name)
end
tensor_array_concat_v3(handle, flow_in, dtype: nil, element_shape_except0: [], name: "TensorArrayConcatV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4499
def self.tensor_array_concat_v3(handle, flow_in, dtype: nil, element_shape_except0: [], name: "TensorArrayConcatV3")
  self.execute("TensorArrayConcatV3", [handle, flow_in], dtype: dtype, element_shape_except0: element_shape_except0, name: name)
end
tensor_array_gather(handle, indices, flow_in, dtype: nil, element_shape: [], name: "TensorArrayGather") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4503
def self.tensor_array_gather(handle, indices, flow_in, dtype: nil, element_shape: [], name: "TensorArrayGather")
  self.execute("TensorArrayGather", [handle, indices, flow_in], dtype: dtype, element_shape: element_shape, name: name)
end
tensor_array_gather_v2(handle, indices, flow_in, dtype: nil, element_shape: [], name: "TensorArrayGatherV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4507
def self.tensor_array_gather_v2(handle, indices, flow_in, dtype: nil, element_shape: [], name: "TensorArrayGatherV2")
  self.execute("TensorArrayGatherV2", [handle, indices, flow_in], dtype: dtype, element_shape: element_shape, name: name)
end
tensor_array_gather_v3(handle, indices, flow_in, dtype: nil, element_shape: [], name: "TensorArrayGatherV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4511
def self.tensor_array_gather_v3(handle, indices, flow_in, dtype: nil, element_shape: [], name: "TensorArrayGatherV3")
  self.execute("TensorArrayGatherV3", [handle, indices, flow_in], dtype: dtype, element_shape: element_shape, name: name)
end
tensor_array_grad(handle, flow_in, source: "", name: "TensorArrayGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4515
def self.tensor_array_grad(handle, flow_in, source: "", name: "TensorArrayGrad")
  self.execute("TensorArrayGrad", [handle, flow_in], source: source, name: name)
end
tensor_array_grad_v2(handle, flow_in, source: "", name: "TensorArrayGradV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4519
def self.tensor_array_grad_v2(handle, flow_in, source: "", name: "TensorArrayGradV2")
  self.execute("TensorArrayGradV2", [handle, flow_in], source: source, name: name)
end
tensor_array_grad_v3(handle, flow_in, source: "", name: "TensorArrayGradV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4523
def self.tensor_array_grad_v3(handle, flow_in, source: "", name: "TensorArrayGradV3")
  self.execute("TensorArrayGradV3", [handle, flow_in], source: source, name: name)
end
tensor_array_grad_with_shape(handle, flow_in, shape_to_prepend, source: "", name: "TensorArrayGradWithShape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4527
def self.tensor_array_grad_with_shape(handle, flow_in, shape_to_prepend, source: "", name: "TensorArrayGradWithShape")
  self.execute("TensorArrayGradWithShape", [handle, flow_in, shape_to_prepend], source: source, name: name)
end
tensor_array_pack(handle, flow_in, dtype: nil, element_shape: [], name: "TensorArrayPack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4531
def self.tensor_array_pack(handle, flow_in, dtype: nil, element_shape: [], name: "TensorArrayPack")
  self.execute("TensorArrayPack", [handle, flow_in], dtype: dtype, element_shape: element_shape, name: name)
end
tensor_array_read(handle, index, flow_in, dtype: nil, name: "TensorArrayRead") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4535
def self.tensor_array_read(handle, index, flow_in, dtype: nil, name: "TensorArrayRead")
  self.execute("TensorArrayRead", [handle, index, flow_in], dtype: dtype, name: name)
end
tensor_array_read_v2(handle, index, flow_in, dtype: nil, name: "TensorArrayReadV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4539
def self.tensor_array_read_v2(handle, index, flow_in, dtype: nil, name: "TensorArrayReadV2")
  self.execute("TensorArrayReadV2", [handle, index, flow_in], dtype: dtype, name: name)
end
tensor_array_read_v3(handle, index, flow_in, dtype: nil, name: "TensorArrayReadV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4543
def self.tensor_array_read_v3(handle, index, flow_in, dtype: nil, name: "TensorArrayReadV3")
  self.execute("TensorArrayReadV3", [handle, index, flow_in], dtype: dtype, name: name)
end
tensor_array_scatter(handle, indices, value, flow_in, typeT: nil, name: "TensorArrayScatter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4547
def self.tensor_array_scatter(handle, indices, value, flow_in, typeT: nil, name: "TensorArrayScatter")
  self.execute("TensorArrayScatter", [handle, indices, value, flow_in], T: typeT, name: name)
end
tensor_array_scatter_v2(handle, indices, value, flow_in, typeT: nil, name: "TensorArrayScatterV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4551
def self.tensor_array_scatter_v2(handle, indices, value, flow_in, typeT: nil, name: "TensorArrayScatterV2")
  self.execute("TensorArrayScatterV2", [handle, indices, value, flow_in], T: typeT, name: name)
end
tensor_array_scatter_v3(handle, indices, value, flow_in, typeT: nil, name: "TensorArrayScatterV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4555
def self.tensor_array_scatter_v3(handle, indices, value, flow_in, typeT: nil, name: "TensorArrayScatterV3")
  self.execute("TensorArrayScatterV3", [handle, indices, value, flow_in], T: typeT, name: name)
end
tensor_array_size(handle, flow_in, name: "TensorArraySize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4559
def self.tensor_array_size(handle, flow_in, name: "TensorArraySize")
  self.execute("TensorArraySize", [handle, flow_in], name: name)
end
tensor_array_size_v2(handle, flow_in, name: "TensorArraySizeV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4563
def self.tensor_array_size_v2(handle, flow_in, name: "TensorArraySizeV2")
  self.execute("TensorArraySizeV2", [handle, flow_in], name: name)
end
tensor_array_size_v3(handle, flow_in, name: "TensorArraySizeV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4567
def self.tensor_array_size_v3(handle, flow_in, name: "TensorArraySizeV3")
  self.execute("TensorArraySizeV3", [handle, flow_in], name: name)
end
tensor_array_split(handle, value, lengths, flow_in, typeT: nil, name: "TensorArraySplit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4571
def self.tensor_array_split(handle, value, lengths, flow_in, typeT: nil, name: "TensorArraySplit")
  self.execute("TensorArraySplit", [handle, value, lengths, flow_in], T: typeT, name: name)
end
tensor_array_split_v2(handle, value, lengths, flow_in, typeT: nil, name: "TensorArraySplitV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4575
def self.tensor_array_split_v2(handle, value, lengths, flow_in, typeT: nil, name: "TensorArraySplitV2")
  self.execute("TensorArraySplitV2", [handle, value, lengths, flow_in], T: typeT, name: name)
end
tensor_array_split_v3(handle, value, lengths, flow_in, typeT: nil, name: "TensorArraySplitV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4579
def self.tensor_array_split_v3(handle, value, lengths, flow_in, typeT: nil, name: "TensorArraySplitV3")
  self.execute("TensorArraySplitV3", [handle, value, lengths, flow_in], T: typeT, name: name)
end
tensor_array_unpack(handle, value, flow_in, typeT: nil, name: "TensorArrayUnpack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4583
def self.tensor_array_unpack(handle, value, flow_in, typeT: nil, name: "TensorArrayUnpack")
  self.execute("TensorArrayUnpack", [handle, value, flow_in], T: typeT, name: name)
end
tensor_array_v2(size, dtype: nil, element_shape: [], dynamic_size: false, clear_after_read: true, tensor_array_name: "", name: "TensorArrayV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4587
def self.tensor_array_v2(size, dtype: nil, element_shape: [], dynamic_size: false, clear_after_read: true, tensor_array_name: "", name: "TensorArrayV2")
  self.execute("TensorArrayV2", [size], dtype: dtype, element_shape: element_shape, dynamic_size: dynamic_size, clear_after_read: clear_after_read, tensor_array_name: tensor_array_name, name: name)
end
tensor_array_v3(size, dtype: nil, element_shape: [], dynamic_size: false, clear_after_read: true, identical_element_shapes: false, tensor_array_name: "", name: "TensorArrayV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4591
def self.tensor_array_v3(size, dtype: nil, element_shape: [], dynamic_size: false, clear_after_read: true, identical_element_shapes: false, tensor_array_name: "", name: "TensorArrayV3")
  self.execute("TensorArrayV3", [size], dtype: dtype, element_shape: element_shape, dynamic_size: dynamic_size, clear_after_read: clear_after_read, identical_element_shapes: identical_element_shapes, tensor_array_name: tensor_array_name, name: name)
end
tensor_array_write(handle, index, value, flow_in, typeT: nil, name: "TensorArrayWrite") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4595
def self.tensor_array_write(handle, index, value, flow_in, typeT: nil, name: "TensorArrayWrite")
  self.execute("TensorArrayWrite", [handle, index, value, flow_in], T: typeT, name: name)
end
tensor_array_write_v2(handle, index, value, flow_in, typeT: nil, name: "TensorArrayWriteV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4599
def self.tensor_array_write_v2(handle, index, value, flow_in, typeT: nil, name: "TensorArrayWriteV2")
  self.execute("TensorArrayWriteV2", [handle, index, value, flow_in], T: typeT, name: name)
end
tensor_array_write_v3(handle, index, value, flow_in, typeT: nil, name: "TensorArrayWriteV3") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4603
def self.tensor_array_write_v3(handle, index, value, flow_in, typeT: nil, name: "TensorArrayWriteV3")
  self.execute("TensorArrayWriteV3", [handle, index, value, flow_in], T: typeT, name: name)
end
tensor_dataset(components, toutput_types: nil, output_shapes: nil, name: "TensorDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4607
def self.tensor_dataset(components, toutput_types: nil, output_shapes: nil, name: "TensorDataset")
  self.execute("TensorDataset", [components], Toutput_types: toutput_types, output_shapes: output_shapes, name: name)
end
tensor_forest_create_tree_variable(tree_handle, tree_config, name: "TensorForestCreateTreeVariable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4611
def self.tensor_forest_create_tree_variable(tree_handle, tree_config, name: "TensorForestCreateTreeVariable")
  self.execute("TensorForestCreateTreeVariable", [tree_handle, tree_config], name: name)
end
tensor_forest_tree_deserialize(tree_handle, tree_config, name: "TensorForestTreeDeserialize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4615
def self.tensor_forest_tree_deserialize(tree_handle, tree_config, name: "TensorForestTreeDeserialize")
  self.execute("TensorForestTreeDeserialize", [tree_handle, tree_config], name: name)
end
tensor_forest_tree_is_initialized_op(tree_handle, name: "TensorForestTreeIsInitializedOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4619
def self.tensor_forest_tree_is_initialized_op(tree_handle, name: "TensorForestTreeIsInitializedOp")
  self.execute("TensorForestTreeIsInitializedOp", [tree_handle], name: name)
end
tensor_forest_tree_predict(tree_handle, dense_features, logits_dimension: nil, name: "TensorForestTreePredict") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4623
def self.tensor_forest_tree_predict(tree_handle, dense_features, logits_dimension: nil, name: "TensorForestTreePredict")
  self.execute("TensorForestTreePredict", [tree_handle, dense_features], logits_dimension: logits_dimension, name: name)
end
tensor_forest_tree_resource_handle_op(container: "", shared_name: "", name: "TensorForestTreeResourceHandleOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4627
def self.tensor_forest_tree_resource_handle_op(container: "", shared_name: "", name: "TensorForestTreeResourceHandleOp")
  self.execute("TensorForestTreeResourceHandleOp", [], container: container, shared_name: shared_name, name: name)
end
tensor_forest_tree_serialize(tree_handle, name: "TensorForestTreeSerialize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4631
def self.tensor_forest_tree_serialize(tree_handle, name: "TensorForestTreeSerialize")
  self.execute("TensorForestTreeSerialize", [tree_handle], name: name)
end
tensor_forest_tree_size(tree_handle, name: "TensorForestTreeSize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4635
def self.tensor_forest_tree_size(tree_handle, name: "TensorForestTreeSize")
  self.execute("TensorForestTreeSize", [tree_handle], name: name)
end
tensor_list_concat(input_handle, element_dtype: nil, element_shape: [], name: "TensorListConcat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4639
def self.tensor_list_concat(input_handle, element_dtype: nil, element_shape: [], name: "TensorListConcat")
  self.execute("TensorListConcat", [input_handle], element_dtype: element_dtype, element_shape: element_shape, name: name)
end
tensor_list_concat_lists(input_a, input_b, element_dtype: nil, name: "TensorListConcatLists") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4643
def self.tensor_list_concat_lists(input_a, input_b, element_dtype: nil, name: "TensorListConcatLists")
  self.execute("TensorListConcatLists", [input_a, input_b], element_dtype: element_dtype, name: name)
end
tensor_list_concat_v2(input_handle, element_shape, leading_dims, element_dtype: nil, shape_type: nil, name: "TensorListConcatV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4647
def self.tensor_list_concat_v2(input_handle, element_shape, leading_dims, element_dtype: nil, shape_type: nil, name: "TensorListConcatV2")
  self.execute("TensorListConcatV2", [input_handle, element_shape, leading_dims], element_dtype: element_dtype, shape_type: shape_type, name: name)
end
tensor_list_element_shape(input_handle, shape_type: nil, name: "TensorListElementShape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4651
def self.tensor_list_element_shape(input_handle, shape_type: nil, name: "TensorListElementShape")
  self.execute("TensorListElementShape", [input_handle], shape_type: shape_type, name: name)
end
tensor_list_from_tensor(tensor, element_shape, element_dtype: nil, shape_type: nil, name: "TensorListFromTensor") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4655
def self.tensor_list_from_tensor(tensor, element_shape, element_dtype: nil, shape_type: nil, name: "TensorListFromTensor")
  self.execute("TensorListFromTensor", [tensor, element_shape], element_dtype: element_dtype, shape_type: shape_type, name: name)
end
tensor_list_gather(input_handle, indices, element_shape, element_dtype: nil, name: "TensorListGather") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4659
def self.tensor_list_gather(input_handle, indices, element_shape, element_dtype: nil, name: "TensorListGather")
  self.execute("TensorListGather", [input_handle, indices, element_shape], element_dtype: element_dtype, name: name)
end
tensor_list_get_item(input_handle, index, element_shape, element_dtype: nil, name: "TensorListGetItem") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4663
def self.tensor_list_get_item(input_handle, index, element_shape, element_dtype: nil, name: "TensorListGetItem")
  self.execute("TensorListGetItem", [input_handle, index, element_shape], element_dtype: element_dtype, name: name)
end
tensor_list_length(input_handle, name: "TensorListLength") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4667
def self.tensor_list_length(input_handle, name: "TensorListLength")
  self.execute("TensorListLength", [input_handle], name: name)
end
tensor_list_pop_back(input_handle, element_shape, element_dtype: nil, name: "TensorListPopBack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4671
def self.tensor_list_pop_back(input_handle, element_shape, element_dtype: nil, name: "TensorListPopBack")
  self.execute("TensorListPopBack", [input_handle, element_shape], element_dtype: element_dtype, name: name)
end
tensor_list_push_back(input_handle, tensor, element_dtype: nil, name: "TensorListPushBack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4675
def self.tensor_list_push_back(input_handle, tensor, element_dtype: nil, name: "TensorListPushBack")
  self.execute("TensorListPushBack", [input_handle, tensor], element_dtype: element_dtype, name: name)
end
tensor_list_push_back_batch(input_handles, tensor, element_dtype: nil, name: "TensorListPushBackBatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4679
def self.tensor_list_push_back_batch(input_handles, tensor, element_dtype: nil, name: "TensorListPushBackBatch")
  self.execute("TensorListPushBackBatch", [input_handles, tensor], element_dtype: element_dtype, name: name)
end
tensor_list_reserve(element_shape, num_elements, element_dtype: nil, shape_type: nil, name: "TensorListReserve") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4683
def self.tensor_list_reserve(element_shape, num_elements, element_dtype: nil, shape_type: nil, name: "TensorListReserve")
  self.execute("TensorListReserve", [element_shape, num_elements], element_dtype: element_dtype, shape_type: shape_type, name: name)
end
tensor_list_resize(input_handle, size, name: "TensorListResize") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4687
def self.tensor_list_resize(input_handle, size, name: "TensorListResize")
  self.execute("TensorListResize", [input_handle, size], name: name)
end
tensor_list_scatter(tensor, indices, element_shape, element_dtype: nil, shape_type: nil, name: "TensorListScatter") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4691
def self.tensor_list_scatter(tensor, indices, element_shape, element_dtype: nil, shape_type: nil, name: "TensorListScatter")
  self.execute("TensorListScatter", [tensor, indices, element_shape], element_dtype: element_dtype, shape_type: shape_type, name: name)
end
tensor_list_scatter_into_existing_list(input_handle, tensor, indices, element_dtype: nil, name: "TensorListScatterIntoExistingList") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4695
def self.tensor_list_scatter_into_existing_list(input_handle, tensor, indices, element_dtype: nil, name: "TensorListScatterIntoExistingList")
  self.execute("TensorListScatterIntoExistingList", [input_handle, tensor, indices], element_dtype: element_dtype, name: name)
end
tensor_list_scatter_v2(tensor, indices, element_shape, num_elements, element_dtype: nil, shape_type: nil, name: "TensorListScatterV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4699
def self.tensor_list_scatter_v2(tensor, indices, element_shape, num_elements, element_dtype: nil, shape_type: nil, name: "TensorListScatterV2")
  self.execute("TensorListScatterV2", [tensor, indices, element_shape, num_elements], element_dtype: element_dtype, shape_type: shape_type, name: name)
end
tensor_list_set_item(input_handle, index, item, element_dtype: nil, name: "TensorListSetItem") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4703
def self.tensor_list_set_item(input_handle, index, item, element_dtype: nil, name: "TensorListSetItem")
  self.execute("TensorListSetItem", [input_handle, index, item], element_dtype: element_dtype, name: name)
end
tensor_list_split(tensor, element_shape, lengths, element_dtype: nil, shape_type: nil, name: "TensorListSplit") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4707
def self.tensor_list_split(tensor, element_shape, lengths, element_dtype: nil, shape_type: nil, name: "TensorListSplit")
  self.execute("TensorListSplit", [tensor, element_shape, lengths], element_dtype: element_dtype, shape_type: shape_type, name: name)
end
tensor_list_stack(input_handle, element_shape, element_dtype: nil, num_elements: -1, name: "TensorListStack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4711
def self.tensor_list_stack(input_handle, element_shape, element_dtype: nil, num_elements: -1, name: "TensorListStack")
  self.execute("TensorListStack", [input_handle, element_shape], element_dtype: element_dtype, num_elements: num_elements, name: name)
end
tensor_scatter_add(tensor, indices, updates, typeT: nil, tindices: nil, name: "TensorScatterAdd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4715
def self.tensor_scatter_add(tensor, indices, updates, typeT: nil, tindices: nil, name: "TensorScatterAdd")
  self.execute("TensorScatterAdd", [tensor, indices, updates], T: typeT, Tindices: tindices, name: name)
end
tensor_scatter_sub(tensor, indices, updates, typeT: nil, tindices: nil, name: "TensorScatterSub") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4719
def self.tensor_scatter_sub(tensor, indices, updates, typeT: nil, tindices: nil, name: "TensorScatterSub")
  self.execute("TensorScatterSub", [tensor, indices, updates], T: typeT, Tindices: tindices, name: name)
end
tensor_scatter_update(tensor, indices, updates, typeT: nil, tindices: nil, name: "TensorScatterUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4723
def self.tensor_scatter_update(tensor, indices, updates, typeT: nil, tindices: nil, name: "TensorScatterUpdate")
  self.execute("TensorScatterUpdate", [tensor, indices, updates], T: typeT, Tindices: tindices, name: name)
end
tensor_slice_dataset(components, toutput_types: nil, output_shapes: nil, name: "TensorSliceDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4727
def self.tensor_slice_dataset(components, toutput_types: nil, output_shapes: nil, name: "TensorSliceDataset")
  self.execute("TensorSliceDataset", [components], Toutput_types: toutput_types, output_shapes: output_shapes, name: name)
end
tensor_strided_slice_update(input, start, stop, strides, value, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "TensorStridedSliceUpdate") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4731
def self.tensor_strided_slice_update(input, start, stop, strides, value, typeT: nil, index: nil, begin_mask: 0, end_mask: 0, ellipsis_mask: 0, new_axis_mask: 0, shrink_axis_mask: 0, name: "TensorStridedSliceUpdate")
  self.execute("TensorStridedSliceUpdate", [input, start, stop, strides, value], T: typeT, Index: index, begin_mask: begin_mask, end_mask: end_mask, ellipsis_mask: ellipsis_mask, new_axis_mask: new_axis_mask, shrink_axis_mask: shrink_axis_mask, name: name)
end
tensor_summary(tensor, typeT: nil, description: "", labels: [], display_name: "", name: "TensorSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4735
def self.tensor_summary(tensor, typeT: nil, description: "", labels: [], display_name: "", name: "TensorSummary")
  self.execute("TensorSummary", [tensor], T: typeT, description: description, labels: labels, display_name: display_name, name: name)
end
tensor_summary_v2(tag, tensor, serialized_summary_metadata, typeT: nil, name: "TensorSummaryV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4739
def self.tensor_summary_v2(tag, tensor, serialized_summary_metadata, typeT: nil, name: "TensorSummaryV2")
  self.execute("TensorSummaryV2", [tag, tensor, serialized_summary_metadata], T: typeT, name: name)
end
text_line_dataset(filenames, compression_type, buffer_size, name: "TextLineDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4743
def self.text_line_dataset(filenames, compression_type, buffer_size, name: "TextLineDataset")
  self.execute("TextLineDataset", [filenames, compression_type, buffer_size], name: name)
end
text_line_reader(skip_header_lines: 0, container: "", shared_name: "", name: "TextLineReader") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4747
def self.text_line_reader(skip_header_lines: 0, container: "", shared_name: "", name: "TextLineReader")
  self.execute("TextLineReader", [], skip_header_lines: skip_header_lines, container: container, shared_name: shared_name, name: name)
end
text_line_reader_v2(skip_header_lines: 0, container: "", shared_name: "", name: "TextLineReaderV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4751
def self.text_line_reader_v2(skip_header_lines: 0, container: "", shared_name: "", name: "TextLineReaderV2")
  self.execute("TextLineReaderV2", [], skip_header_lines: skip_header_lines, container: container, shared_name: shared_name, name: name)
end
tf_record_dataset(filenames, compression_type, buffer_size, name: "TFRecordDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4407
def self.tf_record_dataset(filenames, compression_type, buffer_size, name: "TFRecordDataset")
  self.execute("TFRecordDataset", [filenames, compression_type, buffer_size], name: name)
end
tf_record_reader(container: "", shared_name: "", compression_type: "", name: "TFRecordReader") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4411
def self.tf_record_reader(container: "", shared_name: "", compression_type: "", name: "TFRecordReader")
  self.execute("TFRecordReader", [], container: container, shared_name: shared_name, compression_type: compression_type, name: name)
end
tf_record_reader_v2(container: "", shared_name: "", compression_type: "", name: "TFRecordReaderV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4415
def self.tf_record_reader_v2(container: "", shared_name: "", compression_type: "", name: "TFRecordReaderV2")
  self.execute("TFRecordReaderV2", [], container: container, shared_name: shared_name, compression_type: compression_type, name: name)
end
thread_pool_dataset(input_dataset, thread_pool, output_types: nil, output_shapes: nil, name: "ThreadPoolDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4755
def self.thread_pool_dataset(input_dataset, thread_pool, output_types: nil, output_shapes: nil, name: "ThreadPoolDataset")
  self.execute("ThreadPoolDataset", [input_dataset, thread_pool], output_types: output_types, output_shapes: output_shapes, name: name)
end
thread_pool_handle(num_threads: nil, max_intra_op_parallelism: 1, display_name: "", container: "", shared_name: "", name: "ThreadPoolHandle") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4759
def self.thread_pool_handle(num_threads: nil, max_intra_op_parallelism: 1, display_name: "", container: "", shared_name: "", name: "ThreadPoolHandle")
  self.execute("ThreadPoolHandle", [], num_threads: num_threads, max_intra_op_parallelism: max_intra_op_parallelism, display_name: display_name, container: container, shared_name: shared_name, name: name)
end
thread_unsafe_unigram_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "ThreadUnsafeUnigramCandidateSampler") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4763
def self.thread_unsafe_unigram_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "ThreadUnsafeUnigramCandidateSampler")
  self.execute("ThreadUnsafeUnigramCandidateSampler", [true_classes], num_true: num_true, num_sampled: num_sampled, unique: unique, range_max: range_max, seed: seed, seed2: seed2, name: name)
end
tile(input, multiples, typeT: nil, tmultiples: :int32, name: "Tile") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4767
def self.tile(input, multiples, typeT: nil, tmultiples: :int32, name: "Tile")
  self.execute("Tile", [input, multiples], T: typeT, Tmultiples: tmultiples, name: name)
end
tile_grad(input, multiples, typeT: nil, name: "TileGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4771
def self.tile_grad(input, multiples, typeT: nil, name: "TileGrad")
  self.execute("TileGrad", [input, multiples], T: typeT, name: name)
end
timestamp(name: "Timestamp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4775
def self.timestamp(name: "Timestamp")
  self.execute("Timestamp", [], name: name)
end
top_k(input, k: nil, sorted: true, typeT: nil, name: "TopK") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4779
def self.top_k(input, k: nil, sorted: true, typeT: nil, name: "TopK")
  self.execute("TopK", [input], k: k, sorted: sorted, T: typeT, name: name)
end
top_kv2(input, k, sorted: true, typeT: nil, name: "TopKV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4783
def self.top_kv2(input, k, sorted: true, typeT: nil, name: "TopKV2")
  self.execute("TopKV2", [input, k], sorted: sorted, T: typeT, name: name)
end
tpu_compilation_result(name: "TPUCompilationResult") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4419
def self.tpu_compilation_result(name: "TPUCompilationResult")
  self.execute("TPUCompilationResult", [], name: name)
end
tpu_embedding_activations(embedding_variable, sliced_activations, table_id: nil, lookup_id: nil, name: "TPUEmbeddingActivations") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4423
def self.tpu_embedding_activations(embedding_variable, sliced_activations, table_id: nil, lookup_id: nil, name: "TPUEmbeddingActivations")
  self.execute("TPUEmbeddingActivations", [embedding_variable, sliced_activations], table_id: table_id, lookup_id: lookup_id, name: name)
end
tpu_ordinal_selector(name: "TPUOrdinalSelector") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4427
def self.tpu_ordinal_selector(name: "TPUOrdinalSelector")
  self.execute("TPUOrdinalSelector", [], name: name)
end
tpu_partitioned_call(args, device_ordinal, tin: nil, tout: nil, f: nil, autotuner_thresh: 0, name: "TPUPartitionedCall") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4431
def self.tpu_partitioned_call(args, device_ordinal, tin: nil, tout: nil, f: nil, autotuner_thresh: 0, name: "TPUPartitionedCall")
  self.execute("TPUPartitionedCall", [args, device_ordinal], Tin: tin, Tout: tout, f: f, autotuner_thresh: autotuner_thresh, name: name)
end
tpu_replicate_metadata(num_replicas: nil, num_cores_per_replica: 1, topology: "", use_tpu: true, device_assignment: [], computation_shape: [], host_compute_core: [], padding_map: [], step_marker_location: "STEP_MARK_AT_ENTRY", allow_soft_placement: false, name: "TPUReplicateMetadata") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4435
def self.tpu_replicate_metadata(num_replicas: nil, num_cores_per_replica: 1, topology: "", use_tpu: true, device_assignment: [], computation_shape: [], host_compute_core: [], padding_map: [], step_marker_location: "STEP_MARK_AT_ENTRY", allow_soft_placement: false, name: "TPUReplicateMetadata")
  self.execute("TPUReplicateMetadata", [], num_replicas: num_replicas, num_cores_per_replica: num_cores_per_replica, topology: topology, use_tpu: use_tpu, device_assignment: device_assignment, computation_shape: computation_shape, host_compute_core: host_compute_core, padding_map: padding_map, step_marker_location: step_marker_location, allow_soft_placement: allow_soft_placement, name: name)
end
tpu_replicated_input(inputs, n: nil, typeT: nil, is_mirrored_variable: false, index: -1, name: "TPUReplicatedInput") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4439
def self.tpu_replicated_input(inputs, n: nil, typeT: nil, is_mirrored_variable: false, index: -1, name: "TPUReplicatedInput")
  self.execute("TPUReplicatedInput", [inputs], N: n, T: typeT, is_mirrored_variable: is_mirrored_variable, index: index, name: name)
end
tpu_replicated_output(input, num_replicas: nil, typeT: nil, name: "TPUReplicatedOutput") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4443
def self.tpu_replicated_output(input, num_replicas: nil, typeT: nil, name: "TPUReplicatedOutput")
  self.execute("TPUReplicatedOutput", [input], num_replicas: num_replicas, T: typeT, name: name)
end
transpose(x, perm, typeT: nil, tperm: :int32, name: "Transpose") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4787
def self.transpose(x, perm, typeT: nil, tperm: :int32, name: "Transpose")
  self.execute("Transpose", [x, perm], T: typeT, Tperm: tperm, name: name)
end
tridiagonal_mat_mul(superdiag, maindiag, subdiag, rhs, typeT: nil, name: "TridiagonalMatMul") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4791
def self.tridiagonal_mat_mul(superdiag, maindiag, subdiag, rhs, typeT: nil, name: "TridiagonalMatMul")
  self.execute("TridiagonalMatMul", [superdiag, maindiag, subdiag, rhs], T: typeT, name: name)
end
tridiagonal_solve(diagonals, rhs, partial_pivoting: true, typeT: nil, name: "TridiagonalSolve") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4795
def self.tridiagonal_solve(diagonals, rhs, partial_pivoting: true, typeT: nil, name: "TridiagonalSolve")
  self.execute("TridiagonalSolve", [diagonals, rhs], partial_pivoting: partial_pivoting, T: typeT, name: name)
end
truncate_div(x, y, typeT: nil, name: "TruncateDiv") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4799
def self.truncate_div(x, y, typeT: nil, name: "TruncateDiv")
  self.execute("TruncateDiv", [x, y], T: typeT, name: name)
end
truncate_mod(x, y, typeT: nil, name: "TruncateMod") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4803
def self.truncate_mod(x, y, typeT: nil, name: "TruncateMod")
  self.execute("TruncateMod", [x, y], T: typeT, name: name)
end
truncated_normal(shape, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "TruncatedNormal") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4807
def self.truncated_normal(shape, seed: 0, seed2: 0, dtype: nil, typeT: nil, name: "TruncatedNormal")
  self.execute("TruncatedNormal", [shape], seed: seed, seed2: seed2, dtype: dtype, T: typeT, name: name)
end
try_rpc(address, method, request, protocol: "", fail_fast: true, timeout_in_ms: 0, name: "TryRpc") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4811
def self.try_rpc(address, method, request, protocol: "", fail_fast: true, timeout_in_ms: 0, name: "TryRpc")
  self.execute("TryRpc", [address, method, request], protocol: protocol, fail_fast: fail_fast, timeout_in_ms: timeout_in_ms, name: name)
end
unbatch(batched_tensor, batch_index, id, timeout_micros: nil, container: "", shared_name: "", typeT: nil, name: "Unbatch") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4815
def self.unbatch(batched_tensor, batch_index, id, timeout_micros: nil, container: "", shared_name: "", typeT: nil, name: "Unbatch")
  self.execute("Unbatch", [batched_tensor, batch_index, id], timeout_micros: timeout_micros, container: container, shared_name: shared_name, T: typeT, name: name)
end
unbatch_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "UnbatchDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4819
def self.unbatch_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "UnbatchDataset")
  self.execute("UnbatchDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
unbatch_grad(original_input, batch_index, grad, id, container: "", shared_name: "", typeT: nil, name: "UnbatchGrad") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4823
def self.unbatch_grad(original_input, batch_index, grad, id, container: "", shared_name: "", typeT: nil, name: "UnbatchGrad")
  self.execute("UnbatchGrad", [original_input, batch_index, grad, id], container: container, shared_name: shared_name, T: typeT, name: name)
end
unicode_decode(input, input_encoding: "", errors: "replace", replacement_char: 65533, replace_control_characters: false, tsplits: :int64, name: "UnicodeDecode") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4827
def self.unicode_decode(input, input_encoding: "", errors: "replace", replacement_char: 65533, replace_control_characters: false, tsplits: :int64, name: "UnicodeDecode")
  self.execute("UnicodeDecode", [input], input_encoding: input_encoding, errors: errors, replacement_char: replacement_char, replace_control_characters: replace_control_characters, Tsplits: tsplits, name: name)
end
unicode_decode_with_offsets(input, input_encoding: "", errors: "replace", replacement_char: 65533, replace_control_characters: false, tsplits: :int64, name: "UnicodeDecodeWithOffsets") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4831
def self.unicode_decode_with_offsets(input, input_encoding: "", errors: "replace", replacement_char: 65533, replace_control_characters: false, tsplits: :int64, name: "UnicodeDecodeWithOffsets")
  self.execute("UnicodeDecodeWithOffsets", [input], input_encoding: input_encoding, errors: errors, replacement_char: replacement_char, replace_control_characters: replace_control_characters, Tsplits: tsplits, name: name)
end
unicode_encode(input_values, input_splits, errors: "replace", output_encoding: nil, replacement_char: 65533, tsplits: :int64, name: "UnicodeEncode") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4835
def self.unicode_encode(input_values, input_splits, errors: "replace", output_encoding: nil, replacement_char: 65533, tsplits: :int64, name: "UnicodeEncode")
  self.execute("UnicodeEncode", [input_values, input_splits], errors: errors, output_encoding: output_encoding, replacement_char: replacement_char, Tsplits: tsplits, name: name)
end
unicode_script(input, name: "UnicodeScript") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4839
def self.unicode_script(input, name: "UnicodeScript")
  self.execute("UnicodeScript", [input], name: name)
end
unicode_transcode(input, input_encoding: "", output_encoding: nil, errors: "replace", replacement_char: 65533, replace_control_characters: false, name: "UnicodeTranscode") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4843
def self.unicode_transcode(input, input_encoding: "", output_encoding: nil, errors: "replace", replacement_char: 65533, replace_control_characters: false, name: "UnicodeTranscode")
  self.execute("UnicodeTranscode", [input], input_encoding: input_encoding, output_encoding: output_encoding, errors: errors, replacement_char: replacement_char, replace_control_characters: replace_control_characters, name: name)
end
uniform_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "UniformCandidateSampler") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4847
def self.uniform_candidate_sampler(true_classes, num_true: nil, num_sampled: nil, unique: nil, range_max: nil, seed: 0, seed2: 0, name: "UniformCandidateSampler")
  self.execute("UniformCandidateSampler", [true_classes], num_true: num_true, num_sampled: num_sampled, unique: unique, range_max: range_max, seed: seed, seed2: seed2, name: name)
end
unique(x, typeT: nil, out_idx: :int32, name: "Unique") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4851
def self.unique(x, typeT: nil, out_idx: :int32, name: "Unique")
  self.execute("Unique", [x], T: typeT, out_idx: out_idx, name: name)
end
unique_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "UniqueDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4855
def self.unique_dataset(input_dataset, output_types: nil, output_shapes: nil, name: "UniqueDataset")
  self.execute("UniqueDataset", [input_dataset], output_types: output_types, output_shapes: output_shapes, name: name)
end
unique_v2(x, axis, typeT: nil, taxis: :int64, out_idx: :int32, name: "UniqueV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4859
def self.unique_v2(x, axis, typeT: nil, taxis: :int64, out_idx: :int32, name: "UniqueV2")
  self.execute("UniqueV2", [x, axis], T: typeT, Taxis: taxis, out_idx: out_idx, name: name)
end
unique_with_counts(x, typeT: nil, out_idx: :int32, name: "UniqueWithCounts") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4863
def self.unique_with_counts(x, typeT: nil, out_idx: :int32, name: "UniqueWithCounts")
  self.execute("UniqueWithCounts", [x], T: typeT, out_idx: out_idx, name: name)
end
unique_with_counts_v2(x, axis, typeT: nil, taxis: :int64, out_idx: :int32, name: "UniqueWithCountsV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4867
def self.unique_with_counts_v2(x, axis, typeT: nil, taxis: :int64, out_idx: :int32, name: "UniqueWithCountsV2")
  self.execute("UniqueWithCountsV2", [x, axis], T: typeT, Taxis: taxis, out_idx: out_idx, name: name)
end
unpack(value, num: nil, typeT: nil, axis: 0, name: "Unpack") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4871
def self.unpack(value, num: nil, typeT: nil, axis: 0, name: "Unpack")
  self.execute("Unpack", [value], num: num, T: typeT, axis: axis, name: name)
end
unravel_index(indices, dims, tidx: :int32, name: "UnravelIndex") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4875
def self.unravel_index(indices, dims, tidx: :int32, name: "UnravelIndex")
  self.execute("UnravelIndex", [indices, dims], Tidx: tidx, name: name)
end
unsorted_segment_join(inputs, segment_ids, num_segments, separator: "", tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentJoin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4879
def self.unsorted_segment_join(inputs, segment_ids, num_segments, separator: "", tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentJoin")
  self.execute("UnsortedSegmentJoin", [inputs, segment_ids, num_segments], separator: separator, Tindices: tindices, Tnumsegments: tnumsegments, name: name)
end
unsorted_segment_max(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentMax") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4883
def self.unsorted_segment_max(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentMax")
  self.execute("UnsortedSegmentMax", [data, segment_ids, num_segments], T: typeT, Tindices: tindices, Tnumsegments: tnumsegments, name: name)
end
unsorted_segment_min(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentMin") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4887
def self.unsorted_segment_min(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentMin")
  self.execute("UnsortedSegmentMin", [data, segment_ids, num_segments], T: typeT, Tindices: tindices, Tnumsegments: tnumsegments, name: name)
end
unsorted_segment_prod(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentProd") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4891
def self.unsorted_segment_prod(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentProd")
  self.execute("UnsortedSegmentProd", [data, segment_ids, num_segments], T: typeT, Tindices: tindices, Tnumsegments: tnumsegments, name: name)
end
unsorted_segment_sum(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentSum") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4895
def self.unsorted_segment_sum(data, segment_ids, num_segments, typeT: nil, tindices: nil, tnumsegments: :int32, name: "UnsortedSegmentSum")
  self.execute("UnsortedSegmentSum", [data, segment_ids, num_segments], T: typeT, Tindices: tindices, Tnumsegments: tnumsegments, name: name)
end
unstage(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "Unstage") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4899
def self.unstage(capacity: 0, memory_limit: 0, dtypes: nil, container: "", shared_name: "", name: "Unstage")
  self.execute("Unstage", [], capacity: capacity, memory_limit: memory_limit, dtypes: dtypes, container: container, shared_name: shared_name, name: name)
end
unwrap_dataset_variant(input_handle, name: "UnwrapDatasetVariant") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4903
def self.unwrap_dataset_variant(input_handle, name: "UnwrapDatasetVariant")
  self.execute("UnwrapDatasetVariant", [input_handle], name: name)
end
upper_bound(sorted_inputs, values, typeT: nil, out_type: :int32, name: "UpperBound") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4907
def self.upper_bound(sorted_inputs, values, typeT: nil, out_type: :int32, name: "UpperBound")
  self.execute("UpperBound", [sorted_inputs, values], T: typeT, out_type: out_type, name: name)
end
var_handle_op(container: "", shared_name: "", dtype: nil, shape: nil, name: "VarHandleOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4911
def self.var_handle_op(container: "", shared_name: "", dtype: nil, shape: nil, name: "VarHandleOp")
  self.execute("VarHandleOp", [], container: container, shared_name: shared_name, dtype: dtype, shape: shape, name: name)
end
var_is_initialized_op(resource, name: "VarIsInitializedOp") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4915
def self.var_is_initialized_op(resource, name: "VarIsInitializedOp")
  self.execute("VarIsInitializedOp", [resource], name: name)
end
variable(shape: nil, dtype: nil, container: "", shared_name: "", name: "Variable") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4919
def self.variable(shape: nil, dtype: nil, container: "", shared_name: "", name: "Variable")
  self.execute("Variable", [], shape: shape, dtype: dtype, container: container, shared_name: shared_name, name: name)
end
variable_shape(input, out_type: :int32, name: "VariableShape") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4923
def self.variable_shape(input, out_type: :int32, name: "VariableShape")
  self.execute("VariableShape", [input], out_type: out_type, name: name)
end
variable_v2(shape: nil, dtype: nil, container: "", shared_name: "", name: "VariableV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4927
def self.variable_v2(shape: nil, dtype: nil, container: "", shared_name: "", name: "VariableV2")
  self.execute("VariableV2", [], shape: shape, dtype: dtype, container: container, shared_name: shared_name, name: name)
end
where(input, typeT: :bool, name: "Where") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4931
def self.where(input, typeT: :bool, name: "Where")
  self.execute("Where", [input], T: typeT, name: name)
end
while(input, typeT: nil, cond: nil, body: nil, output_shapes: [], parallel_iterations: 10, name: "While") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4935
def self.while(input, typeT: nil, cond: nil, body: nil, output_shapes: [], parallel_iterations: 10, name: "While")
  self.execute("While", [input], T: typeT, cond: cond, body: body, output_shapes: output_shapes, parallel_iterations: parallel_iterations, name: name)
end
whole_file_reader(container: "", shared_name: "", name: "WholeFileReader") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4939
def self.whole_file_reader(container: "", shared_name: "", name: "WholeFileReader")
  self.execute("WholeFileReader", [], container: container, shared_name: shared_name, name: name)
end
whole_file_reader_v2(container: "", shared_name: "", name: "WholeFileReaderV2") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4943
def self.whole_file_reader_v2(container: "", shared_name: "", name: "WholeFileReaderV2")
  self.execute("WholeFileReaderV2", [], container: container, shared_name: shared_name, name: name)
end
window_dataset(input_dataset, size, shift, stride, drop_remainder, output_types: nil, output_shapes: nil, name: "WindowDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4947
def self.window_dataset(input_dataset, size, shift, stride, drop_remainder, output_types: nil, output_shapes: nil, name: "WindowDataset")
  self.execute("WindowDataset", [input_dataset, size, shift, stride, drop_remainder], output_types: output_types, output_shapes: output_shapes, name: name)
end
worker_heartbeat(request, name: "WorkerHeartbeat") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4951
def self.worker_heartbeat(request, name: "WorkerHeartbeat")
  self.execute("WorkerHeartbeat", [request], name: name)
end
wrap_dataset_variant(input_handle, name: "WrapDatasetVariant") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4955
def self.wrap_dataset_variant(input_handle, name: "WrapDatasetVariant")
  self.execute("WrapDatasetVariant", [input_handle], name: name)
end
write_audio_summary(writer, step, tag, tensor, sample_rate, max_outputs: 3, name: "WriteAudioSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4959
def self.write_audio_summary(writer, step, tag, tensor, sample_rate, max_outputs: 3, name: "WriteAudioSummary")
  self.execute("WriteAudioSummary", [writer, step, tag, tensor, sample_rate], max_outputs: max_outputs, name: name)
end
write_file(filename, contents, name: "WriteFile") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4963
def self.write_file(filename, contents, name: "WriteFile")
  self.execute("WriteFile", [filename, contents], name: name)
end
write_graph_summary(writer, step, tensor, name: "WriteGraphSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4967
def self.write_graph_summary(writer, step, tensor, name: "WriteGraphSummary")
  self.execute("WriteGraphSummary", [writer, step, tensor], name: name)
end
write_histogram_summary(writer, step, tag, values, typeT: :float, name: "WriteHistogramSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4971
def self.write_histogram_summary(writer, step, tag, values, typeT: :float, name: "WriteHistogramSummary")
  self.execute("WriteHistogramSummary", [writer, step, tag, values], T: typeT, name: name)
end
write_image_summary(writer, step, tag, tensor, bad_color, max_images: 3, typeT: :float, name: "WriteImageSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4975
def self.write_image_summary(writer, step, tag, tensor, bad_color, max_images: 3, typeT: :float, name: "WriteImageSummary")
  self.execute("WriteImageSummary", [writer, step, tag, tensor, bad_color], max_images: max_images, T: typeT, name: name)
end
write_raw_proto_summary(writer, step, tensor, name: "WriteRawProtoSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4979
def self.write_raw_proto_summary(writer, step, tensor, name: "WriteRawProtoSummary")
  self.execute("WriteRawProtoSummary", [writer, step, tensor], name: name)
end
write_scalar_summary(writer, step, tag, value, typeT: nil, name: "WriteScalarSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4983
def self.write_scalar_summary(writer, step, tag, value, typeT: nil, name: "WriteScalarSummary")
  self.execute("WriteScalarSummary", [writer, step, tag, value], T: typeT, name: name)
end
write_summary(writer, step, tensor, tag, summary_metadata, typeT: nil, name: "WriteSummary") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4987
def self.write_summary(writer, step, tensor, tag, summary_metadata, typeT: nil, name: "WriteSummary")
  self.execute("WriteSummary", [writer, step, tensor, tag, summary_metadata], T: typeT, name: name)
end
xdivy(x, y, typeT: nil, name: "Xdivy") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4991
def self.xdivy(x, y, typeT: nil, name: "Xdivy")
  self.execute("Xdivy", [x, y], T: typeT, name: name)
end
xlogy(x, y, typeT: nil, name: "Xlogy") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4995
def self.xlogy(x, y, typeT: nil, name: "Xlogy")
  self.execute("Xlogy", [x, y], T: typeT, name: name)
end
zeros_like(x, typeT: nil, name: "ZerosLike") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 4999
def self.zeros_like(x, typeT: nil, name: "ZerosLike")
  self.execute("ZerosLike", [x], T: typeT, name: name)
end
zeta(x, q, typeT: nil, name: "Zeta") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5003
def self.zeta(x, q, typeT: nil, name: "Zeta")
  self.execute("Zeta", [x, q], T: typeT, name: name)
end
zip_dataset(input_datasets, output_types: nil, output_shapes: nil, n: nil, name: "ZipDataset") click to toggle source
# File lib/tensorflow/ops/raw_ops.rb, line 5007
def self.zip_dataset(input_datasets, output_types: nil, output_shapes: nil, n: nil, name: "ZipDataset")
  self.execute("ZipDataset", [input_datasets], output_types: output_types, output_shapes: output_shapes, N: n, name: name)
end