Class GoogleCloudMlV1TrainingInput

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to submitting a training job.

Inheritance
object
GoogleCloudMlV1TrainingInput
Implements
Inherited Members
Namespace: Google.Apis.CloudMachineLearningEngine.v1.Data
Assembly: Google.Apis.CloudMachineLearningEngine.v1.dll
Syntax
public class GoogleCloudMlV1TrainingInput : IDirectResponseSchema

Properties

Args

Optional. Command-line arguments passed to the training application when it starts. If your job uses a custom container, then the arguments are passed to the container's ENTRYPOINT command.

Declaration
[JsonProperty("args")]
public virtual IList<string> Args { get; set; }
Property Value
Type Description
IList<string>

ETag

The ETag of the item.

Declaration
public virtual string ETag { get; set; }
Property Value
Type Description
string

EnableWebAccess

Optional. Whether you want AI Platform Training to enable interactive shell access to training containers. If set to true, you can access interactive shells at the URIs given by TrainingOutput.web_access_uris or HyperparameterOutput.web_access_uris (within TrainingOutput.trials).

Declaration
[JsonProperty("enableWebAccess")]
public virtual bool? EnableWebAccess { get; set; }
Property Value
Type Description
bool?

EncryptionConfig

Optional. Options for using customer-managed encryption keys (CMEK) to protect resources created by a training job, instead of using Google's default encryption. If this is set, then all resources created by the training job will be encrypted with the customer-managed encryption key that you specify. Learn how and when to use CMEK with AI Platform Training.

Declaration
[JsonProperty("encryptionConfig")]
public virtual GoogleCloudMlV1EncryptionConfig EncryptionConfig { get; set; }
Property Value
Type Description
GoogleCloudMlV1EncryptionConfig

EvaluatorConfig

Optional. The configuration for evaluators. You should only set evaluatorConfig.acceleratorConfig if evaluatorType is set to a Compute Engine machine type. Learn about restrictions on accelerator configurations for training. Set evaluatorConfig.imageUri only if you build a custom image for your evaluator. If evaluatorConfig.imageUri has not been set, AI Platform uses the value of masterConfig.imageUri. Learn more about configuring custom containers.

Declaration
[JsonProperty("evaluatorConfig")]
public virtual GoogleCloudMlV1ReplicaConfig EvaluatorConfig { get; set; }
Property Value
Type Description
GoogleCloudMlV1ReplicaConfig

EvaluatorCount

Optional. The number of evaluator replicas to use for the training job. Each replica in the cluster will be of the type specified in evaluator_type. This value can only be used when scale_tier is set to CUSTOM. If you set this value, you must also set evaluator_type. The default value is zero.

Declaration
[JsonProperty("evaluatorCount")]
public virtual long? EvaluatorCount { get; set; }
Property Value
Type Description
long?

EvaluatorType

Optional. Specifies the type of virtual machine to use for your training job's evaluator nodes. The supported values are the same as those described in the entry for masterType. This value must be consistent with the category of machine type that masterType uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when scaleTier is set to CUSTOM and evaluatorCount is greater than zero.

Declaration
[JsonProperty("evaluatorType")]
public virtual string EvaluatorType { get; set; }
Property Value
Type Description
string

Hyperparameters

Optional. The set of Hyperparameters to tune.

Declaration
[JsonProperty("hyperparameters")]
public virtual GoogleCloudMlV1HyperparameterSpec Hyperparameters { get; set; }
Property Value
Type Description
GoogleCloudMlV1HyperparameterSpec

JobDir

Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.

Declaration
[JsonProperty("jobDir")]
public virtual string JobDir { get; set; }
Property Value
Type Description
string

MasterConfig

Optional. The configuration for your master worker. You should only set masterConfig.acceleratorConfig if masterType is set to a Compute Engine machine type. Learn about restrictions on accelerator configurations for training. Set masterConfig.imageUri only if you build a custom image. Only one of masterConfig.imageUri and runtimeVersion should be set. Learn more about configuring custom containers.

Declaration
[JsonProperty("masterConfig")]
public virtual GoogleCloudMlV1ReplicaConfig MasterConfig { get; set; }
Property Value
Type Description
GoogleCloudMlV1ReplicaConfig

MasterType

Optional. Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when scaleTier is set to CUSTOM. You can use certain Compute Engine machine types directly in this field. See the list of compatible Compute Engine machine types. Alternatively, you can use the certain legacy machine types in this field. See the list of legacy machine types. Finally, if you want to use a TPU for training, specify cloud_tpu in this field. Learn more about the special configuration options for training with TPUs.

Declaration
[JsonProperty("masterType")]
public virtual string MasterType { get; set; }
Property Value
Type Description
string

Network

Optional. The full name of the Compute Engine network to which the Job is peered. For example, projects/12345/global/networks/myVPC. The format of this field is projects/{project}/global/networks/{network}, where {project} is a project number (like 12345) and {network} is network name. Private services access must already be configured for the network. If left unspecified, the Job is not peered with any network. Learn about using VPC Network Peering..

Declaration
[JsonProperty("network")]
public virtual string Network { get; set; }
Property Value
Type Description
string

PackageUris

Required. The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.

Declaration
[JsonProperty("packageUris")]
public virtual IList<string> PackageUris { get; set; }
Property Value
Type Description
IList<string>

ParameterServerConfig

Optional. The configuration for parameter servers. You should only set parameterServerConfig.acceleratorConfig if parameterServerType is set to a Compute Engine machine type. Learn about restrictions on accelerator configurations for training. Set parameterServerConfig.imageUri only if you build a custom image for your parameter server. If parameterServerConfig.imageUri has not been set, AI Platform uses the value of masterConfig.imageUri. Learn more about configuring custom containers.

Declaration
[JsonProperty("parameterServerConfig")]
public virtual GoogleCloudMlV1ReplicaConfig ParameterServerConfig { get; set; }
Property Value
Type Description
GoogleCloudMlV1ReplicaConfig

ParameterServerCount

Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in parameter_server_type. This value can only be used when scale_tier is set to CUSTOM. If you set this value, you must also set parameter_server_type. The default value is zero.

Declaration
[JsonProperty("parameterServerCount")]
public virtual long? ParameterServerCount { get; set; }
Property Value
Type Description
long?

ParameterServerType

Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for master_type. This value must be consistent with the category of machine type that masterType uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when scaleTier is set to CUSTOM and parameter_server_count is greater than zero.

Declaration
[JsonProperty("parameterServerType")]
public virtual string ParameterServerType { get; set; }
Property Value
Type Description
string

PythonModule

Required. The Python module name to run after installing the packages.

Declaration
[JsonProperty("pythonModule")]
public virtual string PythonModule { get; set; }
Property Value
Type Description
string

PythonVersion

Optional. The version of Python used in training. You must either specify this field or specify masterConfig.imageUri. The following Python versions are available: * Python '3.7' is available when runtime_version is set to '1.15' or later. * Python '3.5' is available when runtime_version is set to a version from '1.4' to '1.14'. * Python '2.7' is available when runtime_version is set to '1.15' or earlier. Read more about the Python versions available for each runtime version.

Declaration
[JsonProperty("pythonVersion")]
public virtual string PythonVersion { get; set; }
Property Value
Type Description
string

Region

Required. The region to run the training job in. See the available regions for AI Platform Training.

Declaration
[JsonProperty("region")]
public virtual string Region { get; set; }
Property Value
Type Description
string

RuntimeVersion

Optional. The AI Platform runtime version to use for training. You must either specify this field or specify masterConfig.imageUri. For more information, see the runtime version list and learn how to manage runtime versions.

Declaration
[JsonProperty("runtimeVersion")]
public virtual string RuntimeVersion { get; set; }
Property Value
Type Description
string

ScaleTier

Required. Specifies the machine types, the number of replicas for workers and parameter servers.

Declaration
[JsonProperty("scaleTier")]
public virtual string ScaleTier { get; set; }
Property Value
Type Description
string

Scheduling

Optional. Scheduling options for a training job.

Declaration
[JsonProperty("scheduling")]
public virtual GoogleCloudMlV1Scheduling Scheduling { get; set; }
Property Value
Type Description
GoogleCloudMlV1Scheduling

ServiceAccount

Optional. The email address of a service account to use when running the training appplication. You must have the iam.serviceAccounts.actAs permission for the specified service account. In addition, the AI Platform Training Google-managed service account must have the roles/iam.serviceAccountAdmin role for the specified service account. Learn more about configuring a service account. If not specified, the AI Platform Training Google-managed service account is used by default.

Declaration
[JsonProperty("serviceAccount")]
public virtual string ServiceAccount { get; set; }
Property Value
Type Description
string

UseChiefInTfConfig

Optional. Use chief instead of master in the TF_CONFIG environment variable when training with a custom container. Defaults to false. Learn more about this field. This field has no effect for training jobs that don't use a custom container.

Declaration
[JsonProperty("useChiefInTfConfig")]
public virtual bool? UseChiefInTfConfig { get; set; }
Property Value
Type Description
bool?

WorkerConfig

Optional. The configuration for workers. You should only set workerConfig.acceleratorConfig if workerType is set to a Compute Engine machine type. Learn about restrictions on accelerator configurations for training. Set workerConfig.imageUri only if you build a custom image for your worker. If workerConfig.imageUri has not been set, AI Platform uses the value of masterConfig.imageUri. Learn more about configuring custom containers.

Declaration
[JsonProperty("workerConfig")]
public virtual GoogleCloudMlV1ReplicaConfig WorkerConfig { get; set; }
Property Value
Type Description
GoogleCloudMlV1ReplicaConfig

WorkerCount

Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in worker_type. This value can only be used when scale_tier is set to CUSTOM. If you set this value, you must also set worker_type. The default value is zero.

Declaration
[JsonProperty("workerCount")]
public virtual long? WorkerCount { get; set; }
Property Value
Type Description
long?

WorkerType

Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for masterType. This value must be consistent with the category of machine type that masterType uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. If you use cloud_tpu for this value, see special instructions for configuring a custom TPU machine. This value must be present when scaleTier is set to CUSTOM and workerCount is greater than zero.

Declaration
[JsonProperty("workerType")]
public virtual string WorkerType { get; set; }
Property Value
Type Description
string

Implements