class Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig

Represents the configuration for a replica in a cluster.

Attributes

accelerator_config[RW]

Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about [ accelerators for training](/ml-engine/docs/using-gpus) and [accelerators for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus). Corresponds to the JSON property `acceleratorConfig` @return [Google::Apis::MlV1::GoogleCloudMlV1AcceleratorConfig]

container_args[RW]

Arguments to the entrypoint command. The following rules apply for container_command and container_args: - If you do not supply command or args: The defaults defined in the Docker image are used. - If you supply a command but no args: The default EntryPoint and the default Cmd defined in the Docker image are ignored. Your command is run without any arguments. - If you supply only args: The default Entrypoint defined in the Docker image is run with the args that you supplied. - If you supply a command and args: The default Entrypoint and the default Cmd defined in the Docker image are ignored. Your command is run with your args. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time. Corresponds to the JSON property `containerArgs` @return [Array<String>]

container_command[RW]

The command with which the replica's custom container is run. If provided, it will override default ENTRYPOINT of the docker image. If not provided, the docker image's ENTRYPOINT is used. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time. Corresponds to the JSON property `containerCommand` @return [Array<String>]

disk_config[RW]

Represents the config of disk options. Corresponds to the JSON property `diskConfig` @return [Google::Apis::MlV1::GoogleCloudMlV1DiskConfig]

image_uri[RW]

The Docker image to run on the replica. This image must be in Container Registry. Learn more about [configuring custom containers](/ai-platform/ training/docs/distributed-training-containers). Corresponds to the JSON property `imageUri` @return [String]

tpu_tf_version[RW]

The AI Platform runtime version that includes a TensorFlow version matching the one used in the custom container. This field is required if the replica is a TPU worker that uses a custom container. Otherwise, do not specify this field. This must be a [runtime version that currently supports training with TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). Note that the version of TensorFlow included in a runtime version may differ from the numbering of the runtime version itself, because it may have a different [ patch version](www.tensorflow.org/guide/version_compat# semantic_versioning_20). In this field, you must specify the runtime version ( TensorFlow minor version). For example, if your custom container runs TensorFlow `1.x.y`, specify `1.x`. Corresponds to the JSON property `tpuTfVersion` @return [String]

Public Class Methods

new(**args) click to toggle source
# File lib/google/apis/ml_v1/classes.rb, line 2202
def initialize(**args)
   update!(**args)
end

Public Instance Methods

update!(**args) click to toggle source

Update properties of this object

# File lib/google/apis/ml_v1/classes.rb, line 2207
def update!(**args)
  @accelerator_config = args[:accelerator_config] if args.key?(:accelerator_config)
  @container_args = args[:container_args] if args.key?(:container_args)
  @container_command = args[:container_command] if args.key?(:container_command)
  @disk_config = args[:disk_config] if args.key?(:disk_config)
  @image_uri = args[:image_uri] if args.key?(:image_uri)
  @tpu_tf_version = args[:tpu_tf_version] if args.key?(:tpu_tf_version)
end