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
-
#goal ⇒ String
Required.
-
#hyperparameter_metric_tag ⇒ String
Optional.
-
#max_parallel_trials ⇒ Fixnum
Optional.
-
#max_trials ⇒ Fixnum
Optional.
-
#params ⇒ Array<Google::Apis::MlV1::GoogleCloudMlV1ParameterSpec>
Required.
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 1003 def initialize(**args) update!(**args) end |
Instance Attribute Details
#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 968 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 977 def hyperparameter_metric_tag @hyperparameter_metric_tag 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 1001 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 989 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 982 def params @params 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 1008 def update!(**args) @goal = args[:goal] if args.key?(:goal) @hyperparameter_metric_tag = args[:hyperparameter_metric_tag] if args.key?(:hyperparameter_metric_tag) @params = args[:params] if args.key?(:params) @max_trials = args[:max_trials] if args.key?(:max_trials) @max_parallel_trials = args[:max_parallel_trials] if args.key?(:max_parallel_trials) end |