Struct google_ml1_beta1::GoogleCloudMlV1beta1__HyperparameterSpec [] [src]

pub struct GoogleCloudMlV1beta1__HyperparameterSpec {
    pub max_trials: Option<i32>,
    pub hyperparameter_metric_tag: Option<String>,
    pub params: Option<Vec<GoogleCloudMlV1beta1__ParameterSpec>>,
    pub max_parallel_trials: Option<i32>,
    pub goal: Option<String>,
}

Represents a set of hyperparameters to optimize.

This type is not used in any activity, and only used as part of another schema.

Fields

Optional. How many training trials should be attempted to optimize the specified hyperparameters.

Defaults to one.

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.

Required. The set of parameters to tune.

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.

Required. The type of goal to use for tuning. Available types are MAXIMIZE and MINIMIZE.

Defaults to MAXIMIZE.

Trait Implementations

impl Default for GoogleCloudMlV1beta1__HyperparameterSpec
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Returns the "default value" for a type. Read more

impl Clone for GoogleCloudMlV1beta1__HyperparameterSpec
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Returns a copy of the value. Read more

1.0.0
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Performs copy-assignment from source. Read more

impl Debug for GoogleCloudMlV1beta1__HyperparameterSpec
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Formats the value using the given formatter.

impl Part for GoogleCloudMlV1beta1__HyperparameterSpec
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