Class: Google::Apis::MlV1::GoogleCloudMlV1TrainingInput

Inherits:
Object
  • Object
show all
Includes:
Core::Hashable, Core::JsonObjectSupport
Defined in:
generated/google/apis/ml_v1/classes.rb,
generated/google/apis/ml_v1/representations.rb,
generated/google/apis/ml_v1/representations.rb

Overview

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.

Instance Attribute Summary collapse

Instance Method Summary collapse

Methods included from Core::JsonObjectSupport

#to_json

Methods included from Core::Hashable

process_value, #to_h

Constructor Details

#initialize(**args) ⇒ GoogleCloudMlV1TrainingInput

Returns a new instance of GoogleCloudMlV1TrainingInput



1182
1183
1184
# File 'generated/google/apis/ml_v1/classes.rb', line 1182

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#argsArray<String>

Optional. Command line arguments to pass to the program. Corresponds to the JSON property args

Returns:

  • (Array<String>)


1018
1019
1020
# File 'generated/google/apis/ml_v1/classes.rb', line 1018

def args
  @args
end

#hyperparametersGoogle::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec

Represents a set of hyperparameters to optimize. Corresponds to the JSON property hyperparameters



1023
1024
1025
# File 'generated/google/apis/ml_v1/classes.rb', line 1023

def hyperparameters
  @hyperparameters
end

#job_dirString

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. Corresponds to the JSON property jobDir

Returns:

  • (String)


1031
1032
1033
# File 'generated/google/apis/ml_v1/classes.rb', line 1031

def job_dir
  @job_dir
end

#master_typeString

Optional. Specifies the type of virtual machine to use for your training job's master worker. The following types are supported:

standard
A basic machine configuration suitable for training simple models with small to moderate datasets.
large_model
A machine with a lot of memory, specially suited for parameter servers when your model is large (having many hidden layers or layers with very large numbers of nodes).
complex_model_s
A machine suitable for the master and workers of the cluster when your model requires more computation than the standard machine can handle satisfactorily.
complex_model_m
A machine with roughly twice the number of cores and roughly double the memory of complex_model_s.
complex_model_l
A machine with roughly twice the number of cores and roughly double the memory of complex_model_m.
standard_gpu
A machine equivalent to standard that also includes a single NVIDIA Tesla K80 GPU. See more about using GPUs to train your model.
complex_model_m_gpu
A machine equivalent to complex_model_m that also includes four NVIDIA Tesla K80 GPUs.
complex_model_l_gpu
A machine equivalent to complex_model_l that also includes eight NVIDIA Tesla K80 GPUs.
standard_p100
A machine equivalent to standard that also includes a single NVIDIA Tesla P100 GPU. The availability of these GPUs is in the Beta launch stage.
complex_model_m_p100
A machine equivalent to complex_model_m that also includes four NVIDIA Tesla P100 GPUs. The availability of these GPUs is in the Beta launch stage.
cloud_tpu
A TPU VM including one Cloud TPU. The availability of Cloud TPU is in Beta launch stage. See more about using TPUs to train your model.

You must set this value when scaleTier is set to CUSTOM. Corresponds to the JSON property masterType

Returns:

  • (String)


1104
1105
1106
# File 'generated/google/apis/ml_v1/classes.rb', line 1104

def master_type
  @master_type
end

#package_urisArray<String>

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. Corresponds to the JSON property packageUris

Returns:

  • (Array<String>)


1111
1112
1113
# File 'generated/google/apis/ml_v1/classes.rb', line 1111

def package_uris
  @package_uris
end

#parameter_server_countFixnum

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. Corresponds to the JSON property parameterServerCount

Returns:

  • (Fixnum)


1120
1121
1122
# File 'generated/google/apis/ml_v1/classes.rb', line 1120

def parameter_server_count
  @parameter_server_count
end

#parameter_server_typeString

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 present when scaleTier is set to CUSTOM and parameter_server_count is greater than zero. Corresponds to the JSON property parameterServerType

Returns:

  • (String)


1130
1131
1132
# File 'generated/google/apis/ml_v1/classes.rb', line 1130

def parameter_server_type
  @parameter_server_type
end

#python_moduleString

Required. The Python module name to run after installing the packages. Corresponds to the JSON property pythonModule

Returns:

  • (String)


1135
1136
1137
# File 'generated/google/apis/ml_v1/classes.rb', line 1135

def python_module
  @python_module
end

#python_versionString

Optional. The version of Python used in training. If not set, the default version is '2.7'. Python '3.5' is available when runtime_version is set to '1.4' and above. Python '2.7' works with all supported runtime versions. Corresponds to the JSON property pythonVersion

Returns:

  • (String)


1142
1143
1144
# File 'generated/google/apis/ml_v1/classes.rb', line 1142

def python_version
  @python_version
end

#regionString

Required. The Google Compute Engine region to run the training job in. See the available regions for ML Engine services. Corresponds to the JSON property region

Returns:

  • (String)


1149
1150
1151
# File 'generated/google/apis/ml_v1/classes.rb', line 1149

def region
  @region
end

#runtime_versionString

Optional. The Google Cloud ML runtime version to use for training. If not set, Google Cloud ML will choose a stable version, which is defined in the documentation of runtime version list. Corresponds to the JSON property runtimeVersion

Returns:

  • (String)


1156
1157
1158
# File 'generated/google/apis/ml_v1/classes.rb', line 1156

def runtime_version
  @runtime_version
end

#scale_tierString

Required. Specifies the machine types, the number of replicas for workers and parameter servers. Corresponds to the JSON property scaleTier

Returns:

  • (String)


1162
1163
1164
# File 'generated/google/apis/ml_v1/classes.rb', line 1162

def scale_tier
  @scale_tier
end

#worker_countFixnum

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. Corresponds to the JSON property workerCount

Returns:

  • (Fixnum)


1170
1171
1172
# File 'generated/google/apis/ml_v1/classes.rb', line 1170

def worker_count
  @worker_count
end

#worker_typeString

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 present when scaleTier is set to CUSTOM and workerCount is greater than zero. Corresponds to the JSON property workerType

Returns:

  • (String)


1180
1181
1182
# File 'generated/google/apis/ml_v1/classes.rb', line 1180

def worker_type
  @worker_type
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
# File 'generated/google/apis/ml_v1/classes.rb', line 1187

def update!(**args)
  @args = args[:args] if args.key?(:args)
  @hyperparameters = args[:hyperparameters] if args.key?(:hyperparameters)
  @job_dir = args[:job_dir] if args.key?(:job_dir)
  @master_type = args[:master_type] if args.key?(:master_type)
  @package_uris = args[:package_uris] if args.key?(:package_uris)
  @parameter_server_count = args[:parameter_server_count] if args.key?(:parameter_server_count)
  @parameter_server_type = args[:parameter_server_type] if args.key?(:parameter_server_type)
  @python_module = args[:python_module] if args.key?(:python_module)
  @python_version = args[:python_version] if args.key?(:python_version)
  @region = args[:region] if args.key?(:region)
  @runtime_version = args[:runtime_version] if args.key?(:runtime_version)
  @scale_tier = args[:scale_tier] if args.key?(:scale_tier)
  @worker_count = args[:worker_count] if args.key?(:worker_count)
  @worker_type = args[:worker_type] if args.key?(:worker_type)
end