Class: Google::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec
- Inherits:
-
Object
- Object
- Google::Apis::MlV1::GoogleCloudMlV1HyperparameterSpec
- 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 a set of hyperparameters to optimize.
Instance Attribute Summary collapse
-
#algorithm ⇒ String
Optional.
-
#enable_trial_early_stopping ⇒ Boolean
(also: #enable_trial_early_stopping?)
Optional.
-
#goal ⇒ String
Required.
-
#hyperparameter_metric_tag ⇒ String
Optional.
-
#max_failed_trials ⇒ Fixnum
Optional.
-
#max_parallel_trials ⇒ Fixnum
Optional.
-
#max_trials ⇒ Fixnum
Optional.
-
#params ⇒ Array<Google::Apis::MlV1::GoogleCloudMlV1ParameterSpec>
Required.
-
#resume_previous_job_id ⇒ String
Optional.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudMlV1HyperparameterSpec
constructor
A new instance of GoogleCloudMlV1HyperparameterSpec.
-
#update!(**args) ⇒ Object
Update properties of this object.
Methods included from Core::JsonObjectSupport
Methods included from Core::Hashable
Constructor Details
#initialize(**args) ⇒ GoogleCloudMlV1HyperparameterSpec
Returns a new instance of GoogleCloudMlV1HyperparameterSpec
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# File 'generated/google/apis/ml_v1/classes.rb', line 462 def initialize(**args) update!(**args) end |
Instance Attribute Details
#algorithm ⇒ String
Optional. The search algorithm specified for the hyperparameter
tuning job.
Uses the default AI Platform hyperparameter tuning
algorithm if unspecified.
Corresponds to the JSON property algorithm
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# File 'generated/google/apis/ml_v1/classes.rb', line 397 def algorithm @algorithm end |
#enable_trial_early_stopping ⇒ Boolean Also known as: enable_trial_early_stopping?
Optional. Indicates if the hyperparameter tuning job enables auto trial
early stopping.
Corresponds to the JSON property enableTrialEarlyStopping
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# File 'generated/google/apis/ml_v1/classes.rb', line 403 def enable_trial_early_stopping @enable_trial_early_stopping end |
#goal ⇒ String
Required. The type of goal to use for tuning. Available types are
MAXIMIZE
and MINIMIZE
.
Defaults to MAXIMIZE
.
Corresponds to the JSON property goal
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# File 'generated/google/apis/ml_v1/classes.rb', line 411 def goal @goal end |
#hyperparameter_metric_tag ⇒ String
Optional. The TensorFlow summary tag name to use for optimizing trials. For
current versions of TensorFlow, this tag name should exactly match what is
shown in TensorBoard, including all scopes. For versions of TensorFlow
prior to 0.12, this should be only the tag passed to tf.Summary.
By default, "training/hptuning/metric" will be used.
Corresponds to the JSON property hyperparameterMetricTag
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# File 'generated/google/apis/ml_v1/classes.rb', line 420 def hyperparameter_metric_tag @hyperparameter_metric_tag end |
#max_failed_trials ⇒ Fixnum
Optional. The number of failed trials that need to be seen before failing
the hyperparameter tuning job. You can specify this field to override the
default failing criteria for AI Platform hyperparameter tuning jobs.
Defaults to zero, which means the service decides when a hyperparameter
job should fail.
Corresponds to the JSON property maxFailedTrials
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# File 'generated/google/apis/ml_v1/classes.rb', line 429 def max_failed_trials @max_failed_trials end |
#max_parallel_trials ⇒ Fixnum
Optional. The number of training trials to run concurrently.
You can reduce the time it takes to perform hyperparameter tuning by adding
trials in parallel. However, each trail only benefits from the information
gained in completed trials. That means that a trial does not get access to
the results of trials running at the same time, which could reduce the
quality of the overall optimization.
Each trial will use the same scale tier and machine types.
Defaults to one.
Corresponds to the JSON property maxParallelTrials
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# File 'generated/google/apis/ml_v1/classes.rb', line 441 def max_parallel_trials @max_parallel_trials end |
#max_trials ⇒ Fixnum
Optional. How many training trials should be attempted to optimize
the specified hyperparameters.
Defaults to one.
Corresponds to the JSON property maxTrials
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# File 'generated/google/apis/ml_v1/classes.rb', line 448 def max_trials @max_trials end |
#params ⇒ Array<Google::Apis::MlV1::GoogleCloudMlV1ParameterSpec>
Required. The set of parameters to tune.
Corresponds to the JSON property params
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# File 'generated/google/apis/ml_v1/classes.rb', line 453 def params @params end |
#resume_previous_job_id ⇒ String
Optional. The prior hyperparameter tuning job id that users hope to
continue with. The job id will be used to find the corresponding vizier
study guid and resume the study.
Corresponds to the JSON property resumePreviousJobId
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# File 'generated/google/apis/ml_v1/classes.rb', line 460 def resume_previous_job_id @resume_previous_job_id 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 467 def update!(**args) @algorithm = args[:algorithm] if args.key?(:algorithm) @enable_trial_early_stopping = args[:enable_trial_early_stopping] if args.key?(:enable_trial_early_stopping) @goal = args[:goal] if args.key?(:goal) @hyperparameter_metric_tag = args[:hyperparameter_metric_tag] if args.key?(:hyperparameter_metric_tag) @max_failed_trials = args[:max_failed_trials] if args.key?(:max_failed_trials) @max_parallel_trials = args[:max_parallel_trials] if args.key?(:max_parallel_trials) @max_trials = args[:max_trials] if args.key?(:max_trials) @params = args[:params] if args.key?(:params) @resume_previous_job_id = args[:resume_previous_job_id] if args.key?(:resume_previous_job_id) end |