Class: Google::Apis::MlV1::GoogleCloudMlV1TrainingInput
- Inherits:
-
Object
- Object
- Google::Apis::MlV1::GoogleCloudMlV1TrainingInput
- 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
-
#args ⇒ Array<String>
Optional.
-
#hyperparameters ⇒ Google::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec
Represents a set of hyperparameters to optimize.
-
#job_dir ⇒ String
Optional.
-
#master_config ⇒ Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig
Represents the configuration for a replica in a cluster.
-
#master_type ⇒ String
Optional.
-
#package_uris ⇒ Array<String>
Required.
-
#parameter_server_config ⇒ Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig
Represents the configuration for a replica in a cluster.
-
#parameter_server_count ⇒ Fixnum
Optional.
-
#parameter_server_type ⇒ String
Optional.
-
#python_module ⇒ String
Required.
-
#python_version ⇒ String
Optional.
-
#region ⇒ String
Required.
-
#runtime_version ⇒ String
Optional.
-
#scale_tier ⇒ String
Required.
-
#scheduling ⇒ Google::Apis::MlV1::GoogleCloudMlV1Scheduling
All parameters related to scheduling of training jobs.
-
#use_chief_in_tf_config ⇒ Boolean
(also: #use_chief_in_tf_config?)
Optional.
-
#worker_config ⇒ Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig
Represents the configuration for a replica in a cluster.
-
#worker_count ⇒ Fixnum
Optional.
-
#worker_type ⇒ String
Optional.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudMlV1TrainingInput
constructor
A new instance of GoogleCloudMlV1TrainingInput.
-
#update!(**args) ⇒ Object
Update properties of this object.
Methods included from Core::JsonObjectSupport
Methods included from Core::Hashable
Constructor Details
#initialize(**args) ⇒ GoogleCloudMlV1TrainingInput
Returns a new instance of GoogleCloudMlV1TrainingInput.
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# File 'generated/google/apis/ml_v1/classes.rb', line 1671 def initialize(**args) update!(**args) end |
Instance Attribute Details
#args ⇒ Array<String>
Optional. Command line arguments to pass to the program.
Corresponds to the JSON property args
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# File 'generated/google/apis/ml_v1/classes.rb', line 1474 def args @args end |
#hyperparameters ⇒ Google::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec
Represents a set of hyperparameters to optimize.
Corresponds to the JSON property hyperparameters
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# File 'generated/google/apis/ml_v1/classes.rb', line 1479 def hyperparameters @hyperparameters end |
#job_dir ⇒ String
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
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# File 'generated/google/apis/ml_v1/classes.rb', line 1487 def job_dir @job_dir end |
#master_config ⇒ Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig
Represents the configuration for a replica in a cluster.
Corresponds to the JSON property masterConfig
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# File 'generated/google/apis/ml_v1/classes.rb', line 1492 def master_config @master_config end |
#master_type ⇒ String
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.
The following types are supported:
n1-standard-4
n1-standard-8
n1-standard-16
n1-standard-32
n1-standard-64
n1-standard-96
n1-highmem-2
n1-highmem-4
n1-highmem-8
n1-highmem-16
n1-highmem-32
n1-highmem-64
n1-highmem-96
n1-highcpu-16
n1-highcpu-32
n1-highcpu-64
n1-highcpu-96
Learn more about using Compute Engine machine types. Alternatively, you can use the following legacy machine types:standard
large_model
complex_model_s
complex_model_m
complex_model_l
standard_gpu
complex_model_m_gpu
complex_model_l_gpu
standard_p100
complex_model_m_p100
standard_v100
large_model_v100
complex_model_m_v100
complex_model_l_v100
Learn more about using legacy machine types. Finally, if you want to use a TPU for training, specifycloud_tpu
in this field. Learn more about the special configuration options for training with TPUs. Corresponds to the JSON propertymasterType
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# File 'generated/google/apis/ml_v1/classes.rb', line 1541 def master_type @master_type end |
#package_uris ⇒ Array<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
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# File 'generated/google/apis/ml_v1/classes.rb', line 1548 def package_uris @package_uris end |
#parameter_server_config ⇒ Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig
Represents the configuration for a replica in a cluster.
Corresponds to the JSON property parameterServerConfig
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# File 'generated/google/apis/ml_v1/classes.rb', line 1553 def parameter_server_config @parameter_server_config end |
#parameter_server_count ⇒ Fixnum
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.
Corresponds to the JSON property parameterServerCount
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# File 'generated/google/apis/ml_v1/classes.rb', line 1563 def parameter_server_count @parameter_server_count end |
#parameter_server_type ⇒ String
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.
Corresponds to the JSON property parameterServerType
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# File 'generated/google/apis/ml_v1/classes.rb', line 1576 def parameter_server_type @parameter_server_type end |
#python_module ⇒ String
Required. The Python module name to run after installing the packages.
Corresponds to the JSON property pythonModule
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# File 'generated/google/apis/ml_v1/classes.rb', line 1581 def python_module @python_module end |
#python_version ⇒ String
Optional. The version of Python used in training. If not set, the default version is '2.7'. Starting January 13, 2020, this field is required. 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. (Runtime versions released after January 1, 2020 do not support Python 2.7.) Read more about the Python versions available for each runtime version. Corresponds to the JSON propertypythonVersion
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# File 'generated/google/apis/ml_v1/classes.rb', line 1600 def python_version @python_version end |
#region ⇒ String
Required. The Google Compute Engine region to run the training job in.
See the available regions
for AI Platform services.
Corresponds to the JSON property region
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# File 'generated/google/apis/ml_v1/classes.rb', line 1607 def region @region end |
#runtime_version ⇒ String
Optional. The AI Platform runtime version to use for training. If not
set, AI Platform uses the default stable version, 1.0. Starting January
13, 2020, this field is
required.
For more information, see the
runtime version list
and
how to manage runtime versions.
Corresponds to the JSON property runtimeVersion
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# File 'generated/google/apis/ml_v1/classes.rb', line 1619 def runtime_version @runtime_version end |
#scale_tier ⇒ String
Required. Specifies the machine types, the number of replicas for workers
and parameter servers.
Corresponds to the JSON property scaleTier
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# File 'generated/google/apis/ml_v1/classes.rb', line 1625 def scale_tier @scale_tier end |
#scheduling ⇒ Google::Apis::MlV1::GoogleCloudMlV1Scheduling
All parameters related to scheduling of training jobs.
Corresponds to the JSON property scheduling
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# File 'generated/google/apis/ml_v1/classes.rb', line 1630 def scheduling @scheduling end |
#use_chief_in_tf_config ⇒ Boolean Also known as: use_chief_in_tf_config?
Optional. Use 'chief' instead of 'master' in TF_CONFIG when Custom
Container is used and evaluator is not specified.
Defaults to false.
Corresponds to the JSON property useChiefInTfConfig
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# File 'generated/google/apis/ml_v1/classes.rb', line 1637 def use_chief_in_tf_config @use_chief_in_tf_config end |
#worker_config ⇒ Google::Apis::MlV1::GoogleCloudMlV1ReplicaConfig
Represents the configuration for a replica in a cluster.
Corresponds to the JSON property workerConfig
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# File 'generated/google/apis/ml_v1/classes.rb', line 1643 def worker_config @worker_config end |
#worker_count ⇒ Fixnum
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.
Corresponds to the JSON property workerCount
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# File 'generated/google/apis/ml_v1/classes.rb', line 1652 def worker_count @worker_count end |
#worker_type ⇒ String
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.
Corresponds to the JSON property workerType
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# File 'generated/google/apis/ml_v1/classes.rb', line 1669 def worker_type @worker_type end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'generated/google/apis/ml_v1/classes.rb', line 1676 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_config = args[:master_config] if args.key?(:master_config) @master_type = args[:master_type] if args.key?(:master_type) @package_uris = args[:package_uris] if args.key?(:package_uris) @parameter_server_config = args[:parameter_server_config] if args.key?(:parameter_server_config) @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) @scheduling = args[:scheduling] if args.key?(:scheduling) @use_chief_in_tf_config = args[:use_chief_in_tf_config] if args.key?(:use_chief_in_tf_config) @worker_config = args[:worker_config] if args.key?(:worker_config) @worker_count = args[:worker_count] if args.key?(:worker_count) @worker_type = args[:worker_type] if args.key?(:worker_type) end |