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
475 476 477 |
# File 'generated/google/apis/ml_v1/classes.rb', line 475 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
410 411 412 |
# File 'generated/google/apis/ml_v1/classes.rb', line 410 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
416 417 418 |
# File 'generated/google/apis/ml_v1/classes.rb', line 416 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
424 425 426 |
# File 'generated/google/apis/ml_v1/classes.rb', line 424 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
433 434 435 |
# File 'generated/google/apis/ml_v1/classes.rb', line 433 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
442 443 444 |
# File 'generated/google/apis/ml_v1/classes.rb', line 442 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
454 455 456 |
# File 'generated/google/apis/ml_v1/classes.rb', line 454 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
461 462 463 |
# File 'generated/google/apis/ml_v1/classes.rb', line 461 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
466 467 468 |
# File 'generated/google/apis/ml_v1/classes.rb', line 466 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
473 474 475 |
# File 'generated/google/apis/ml_v1/classes.rb', line 473 def resume_previous_job_id @resume_previous_job_id end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
480 481 482 483 484 485 486 487 488 489 490 |
# File 'generated/google/apis/ml_v1/classes.rb', line 480 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 |