com.google.api.services.ml.v1.model

Class GoogleCloudMlV1HyperparameterSpec

java.lang.Object

java.util.AbstractMap<String,Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.ml.v1.model.GoogleCloudMlV1HyperparameterSpec

All Implemented Interfaces:

Cloneable, Map<String,Object>

public final class GoogleCloudMlV1HyperparameterSpec
extends GenericJson

Represents a set of hyperparameters to optimize.

This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the AI Platform Training & Prediction API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

GenericData.Flags

Nested classes/interfaces inherited from class java.util.AbstractMap

AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>

Nested classes/interfaces inherited from interface java.util.Map

Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
GoogleCloudMlV1HyperparameterSpec()

Method Summary

Modifier and Type	Method and Description
GoogleCloudMlV1HyperparameterSpec	clone()
String	getAlgorithm() Optional.
Boolean	getEnableTrialEarlyStopping() Optional.
String	getGoal() Required.
String	getHyperparameterMetricTag() Optional.
Integer	getMaxFailedTrials() Optional.
Integer	getMaxParallelTrials() Optional.
Integer	getMaxTrials() Optional.
List<GoogleCloudMlV1ParameterSpec>	getParams() Required.
String	getResumePreviousJobId() Optional.
GoogleCloudMlV1HyperparameterSpec	set(String fieldName, Object value)
GoogleCloudMlV1HyperparameterSpec	setAlgorithm(String algorithm) Optional.
GoogleCloudMlV1HyperparameterSpec	setEnableTrialEarlyStopping(Boolean enableTrialEarlyStopping) Optional.
GoogleCloudMlV1HyperparameterSpec	setGoal(String goal) Required.
GoogleCloudMlV1HyperparameterSpec	setHyperparameterMetricTag(String hyperparameterMetricTag) Optional.
GoogleCloudMlV1HyperparameterSpec	setMaxFailedTrials(Integer maxFailedTrials) Optional.
GoogleCloudMlV1HyperparameterSpec	setMaxParallelTrials(Integer maxParallelTrials) Optional.
GoogleCloudMlV1HyperparameterSpec	setMaxTrials(Integer maxTrials) Optional.
GoogleCloudMlV1HyperparameterSpec	setParams(List<GoogleCloudMlV1ParameterSpec> params) Required.
GoogleCloudMlV1HyperparameterSpec	setResumePreviousJobId(String resumePreviousJobId) Optional.

Methods inherited from class com.google.api.client.json.GenericJson

getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData

entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

clear, containsKey, containsValue, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Constructor Detail

GoogleCloudMlV1HyperparameterSpec

public GoogleCloudMlV1HyperparameterSpec()

Method Detail

getAlgorithm

public String getAlgorithm()

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.

Returns:

value or null for none

setAlgorithm

public GoogleCloudMlV1HyperparameterSpec setAlgorithm(String algorithm)

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.

Parameters:

algorithm - algorithm or null for none

getEnableTrialEarlyStopping

public Boolean getEnableTrialEarlyStopping()

Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.

Returns:

value or null for none

setEnableTrialEarlyStopping

public GoogleCloudMlV1HyperparameterSpec setEnableTrialEarlyStopping(Boolean enableTrialEarlyStopping)

Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.

Parameters:

enableTrialEarlyStopping - enableTrialEarlyStopping or null for none

getGoal

public String getGoal()

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

Returns:

value or null for none

setGoal

public GoogleCloudMlV1HyperparameterSpec setGoal(String goal)

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

Parameters:

goal - goal or null for none

getHyperparameterMetricTag

public String getHyperparameterMetricTag()

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.

Returns:

value or null for none

setHyperparameterMetricTag

public GoogleCloudMlV1HyperparameterSpec setHyperparameterMetricTag(String hyperparameterMetricTag)

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.

Parameters:

hyperparameterMetricTag - hyperparameterMetricTag or null for none

getMaxFailedTrials

public Integer getMaxFailedTrials()

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.

Returns:

value or null for none

setMaxFailedTrials

public GoogleCloudMlV1HyperparameterSpec setMaxFailedTrials(Integer maxFailedTrials)

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.

Parameters:

maxFailedTrials - maxFailedTrials or null for none

getMaxParallelTrials

public Integer getMaxParallelTrials()

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.

Returns:

value or null for none

setMaxParallelTrials

public GoogleCloudMlV1HyperparameterSpec setMaxParallelTrials(Integer maxParallelTrials)

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.

Parameters:

maxParallelTrials - maxParallelTrials or null for none

getMaxTrials

public Integer getMaxTrials()

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

Returns:

value or null for none

setMaxTrials

public GoogleCloudMlV1HyperparameterSpec setMaxTrials(Integer maxTrials)

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

Parameters:

maxTrials - maxTrials or null for none

getParams

public List<GoogleCloudMlV1ParameterSpec> getParams()

Required. The set of parameters to tune.

Returns:

value or null for none

setParams

public GoogleCloudMlV1HyperparameterSpec setParams(List<GoogleCloudMlV1ParameterSpec> params)

Required. The set of parameters to tune.

Parameters:

params - params or null for none

getResumePreviousJobId

public String getResumePreviousJobId()

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.

Returns:

value or null for none

setResumePreviousJobId

public GoogleCloudMlV1HyperparameterSpec setResumePreviousJobId(String resumePreviousJobId)

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.

Parameters:

resumePreviousJobId - resumePreviousJobId or null for none

set

public GoogleCloudMlV1HyperparameterSpec set(String fieldName,
                                             Object value)

Overrides:

set in class GenericJson

clone

public GoogleCloudMlV1HyperparameterSpec clone()

Overrides:

clone in class GenericJson