module Tensorflow::Ops
Public Class Methods
broadcast_mul(vector, matrix)
click to toggle source
# File lib/tensorflow/ops/gradients.rb, line 3 def self.broadcast_mul(vector, matrix) vector = Tensorflow.expand_dims(vector, -1) vector * matrix end
Public Instance Methods
cast(x, destination_dtype, source_dtype: nil, truncate: false)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 4 def cast(x, destination_dtype, source_dtype: nil, truncate: false) RawOps.cast(x, srct: source_dtype, dstt: destination_dtype, truncate: truncate) end
constant(value, dtype: nil, shape: [], name: 'Const')
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 8 def constant(value, dtype: nil, shape: [], name: 'Const') tensor = value.is_a?(Tensor) ? value : Tensor.new(value, dtype: dtype, shape: shape) RawOps.const(value: tensor, dtype: tensor.dtype, name: name) end
expand_dims(input, axis)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 13 def expand_dims(input, axis) RawOps.expand_dims(input, axis) end
fill(dims, value, dtype: nil)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 17 def fill(dims, value, dtype: nil) RawOps.fill(dims, value, typeT: dtype) end
identity(input)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 21 def identity(input) RawOps.identity(input) end
ones(dims, dtype: :float)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 25 def ones(dims, dtype: :float) fill(dims, 1, dtype: dtype) end
pack(values, n: nil, typeT: nil, axis: 0)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 29 def pack(values, n: nil, typeT: nil, axis: 0) typeT ||= TensorData.figure_dtype(values) n ||= values.count RawOps.pack(values, n: n, typeT: typeT, axis: axis) end
placeholder(dtype, name: 'Placeholder', shape: nil)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 35 def placeholder(dtype, name: 'Placeholder', shape: nil) RawOps.placeholder(dtype: dtype, shape: shape, name: name) end
prevent_gradient(input, typeT: nil, message: "")
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 39 def prevent_gradient(input, typeT: nil, message: "") RawOps.prevent_gradient(input, typeT: typeT, message: message, name: "PreventGradient") end
range(start, limit = nil, delta = 1)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 47 def range(start, limit = nil, delta = 1) unless limit limit = start start = 0 end RawOps.range(start, limit, delta) end
rank(input, typeT: nil)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 43 def rank(input, typeT: nil) RawOps.rank(input, typeT: typeT) end
reshape(tensor, shape)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 55 def reshape(tensor, shape) RawOps.reshape(tensor, shape, typeT: tensor.output_types.first) end
shape(input, out_type)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 59 def shape(input, out_type) RawOps.shape(input, out_type: out_type) end
split(value, split_dim, num_split: nil, typeT: nil)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 63 def split(value, split_dim, num_split: nil, typeT: nil) RawOps.split(split_dim, value, num_split: num_split, typeT: typeT) end
split_v(value, size_splits, split_dim=0, num_split: nil, typeT: nil, tlen: nil)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 67 def split_v(value, size_splits, split_dim=0, num_split: nil, typeT: nil, tlen: nil) num_split ||= size_splits.length RawOps.split_v(value, size_splits, split_dim, num_split: num_split, typeT: typeT, tlen: tlen) end
squeeze(input, axis: nil)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 72 def squeeze(input, axis: nil) RawOps.squeeze(input, squeeze_dims: axis) end
timestamp()
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 76 def timestamp RawOps.timestamp end
transpose(x, perm: [1, 0])
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 80 def transpose(x, perm: [1, 0]) RawOps.transpose(x, perm) end
where(condition, x: nil, y: nil)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 84 def where(condition, x: nil, y: nil) if x.nil? && y.nil? RawOps.where(condition) elsif x && y RawOps.select_v2(condition, x, y) else raise(Error::InvalidArgumentError, "x and y must both be non nil or both be nil") end end
zeros(dims, dtype: :float)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 94 def zeros(dims, dtype: :float) fill(dims, 0, dtype: dtype) end
zeros_like(x)
click to toggle source
# File lib/tensorflow/ops/ops.rb, line 98 def zeros_like(x) RawOps.zeros_like(x) end