software.amazon.awssdk.services.sagemaker.model.CreateTrainingJobRequest Maven / Gradle / Ivy
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/*
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
* the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0
*
* or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
* CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
* and limitations under the License.
*/
package software.amazon.awssdk.services.sagemaker.model;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.Optional;
import java.util.function.BiConsumer;
import java.util.function.Consumer;
import java.util.function.Function;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import software.amazon.awssdk.annotations.Generated;
import software.amazon.awssdk.awscore.AwsRequestOverrideConfiguration;
import software.amazon.awssdk.core.SdkField;
import software.amazon.awssdk.core.SdkPojo;
import software.amazon.awssdk.core.protocol.MarshallLocation;
import software.amazon.awssdk.core.protocol.MarshallingType;
import software.amazon.awssdk.core.traits.ListTrait;
import software.amazon.awssdk.core.traits.LocationTrait;
import software.amazon.awssdk.core.traits.MapTrait;
import software.amazon.awssdk.core.util.DefaultSdkAutoConstructList;
import software.amazon.awssdk.core.util.DefaultSdkAutoConstructMap;
import software.amazon.awssdk.core.util.SdkAutoConstructList;
import software.amazon.awssdk.core.util.SdkAutoConstructMap;
import software.amazon.awssdk.utils.ToString;
import software.amazon.awssdk.utils.builder.CopyableBuilder;
import software.amazon.awssdk.utils.builder.ToCopyableBuilder;
/**
*/
@Generated("software.amazon.awssdk:codegen")
public final class CreateTrainingJobRequest extends SageMakerRequest implements
ToCopyableBuilder {
private static final SdkField TRAINING_JOB_NAME_FIELD = SdkField. builder(MarshallingType.STRING)
.memberName("TrainingJobName").getter(getter(CreateTrainingJobRequest::trainingJobName))
.setter(setter(Builder::trainingJobName))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("TrainingJobName").build()).build();
private static final SdkField> HYPER_PARAMETERS_FIELD = SdkField
.> builder(MarshallingType.MAP)
.memberName("HyperParameters")
.getter(getter(CreateTrainingJobRequest::hyperParameters))
.setter(setter(Builder::hyperParameters))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("HyperParameters").build(),
MapTrait.builder()
.keyLocationName("key")
.valueLocationName("value")
.valueFieldInfo(
SdkField. builder(MarshallingType.STRING)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD)
.locationName("value").build()).build()).build()).build();
private static final SdkField ALGORITHM_SPECIFICATION_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("AlgorithmSpecification")
.getter(getter(CreateTrainingJobRequest::algorithmSpecification)).setter(setter(Builder::algorithmSpecification))
.constructor(AlgorithmSpecification::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("AlgorithmSpecification").build())
.build();
private static final SdkField ROLE_ARN_FIELD = SdkField. builder(MarshallingType.STRING)
.memberName("RoleArn").getter(getter(CreateTrainingJobRequest::roleArn)).setter(setter(Builder::roleArn))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("RoleArn").build()).build();
private static final SdkField> INPUT_DATA_CONFIG_FIELD = SdkField
.> builder(MarshallingType.LIST)
.memberName("InputDataConfig")
.getter(getter(CreateTrainingJobRequest::inputDataConfig))
.setter(setter(Builder::inputDataConfig))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("InputDataConfig").build(),
ListTrait
.builder()
.memberLocationName(null)
.memberFieldInfo(
SdkField. builder(MarshallingType.SDK_POJO)
.constructor(Channel::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD)
.locationName("member").build()).build()).build()).build();
private static final SdkField OUTPUT_DATA_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("OutputDataConfig")
.getter(getter(CreateTrainingJobRequest::outputDataConfig)).setter(setter(Builder::outputDataConfig))
.constructor(OutputDataConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("OutputDataConfig").build()).build();
private static final SdkField RESOURCE_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("ResourceConfig")
.getter(getter(CreateTrainingJobRequest::resourceConfig)).setter(setter(Builder::resourceConfig))
.constructor(ResourceConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("ResourceConfig").build()).build();
private static final SdkField VPC_CONFIG_FIELD = SdkField. builder(MarshallingType.SDK_POJO)
.memberName("VpcConfig").getter(getter(CreateTrainingJobRequest::vpcConfig)).setter(setter(Builder::vpcConfig))
.constructor(VpcConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("VpcConfig").build()).build();
private static final SdkField STOPPING_CONDITION_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("StoppingCondition")
.getter(getter(CreateTrainingJobRequest::stoppingCondition)).setter(setter(Builder::stoppingCondition))
.constructor(StoppingCondition::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("StoppingCondition").build()).build();
private static final SdkField> TAGS_FIELD = SdkField
.> builder(MarshallingType.LIST)
.memberName("Tags")
.getter(getter(CreateTrainingJobRequest::tags))
.setter(setter(Builder::tags))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("Tags").build(),
ListTrait
.builder()
.memberLocationName(null)
.memberFieldInfo(
SdkField. builder(MarshallingType.SDK_POJO)
.constructor(Tag::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD)
.locationName("member").build()).build()).build()).build();
private static final SdkField ENABLE_NETWORK_ISOLATION_FIELD = SdkField. builder(MarshallingType.BOOLEAN)
.memberName("EnableNetworkIsolation").getter(getter(CreateTrainingJobRequest::enableNetworkIsolation))
.setter(setter(Builder::enableNetworkIsolation))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("EnableNetworkIsolation").build())
.build();
private static final SdkField ENABLE_INTER_CONTAINER_TRAFFIC_ENCRYPTION_FIELD = SdkField
. builder(MarshallingType.BOOLEAN)
.memberName("EnableInterContainerTrafficEncryption")
.getter(getter(CreateTrainingJobRequest::enableInterContainerTrafficEncryption))
.setter(setter(Builder::enableInterContainerTrafficEncryption))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD)
.locationName("EnableInterContainerTrafficEncryption").build()).build();
private static final SdkField ENABLE_MANAGED_SPOT_TRAINING_FIELD = SdkField
. builder(MarshallingType.BOOLEAN).memberName("EnableManagedSpotTraining")
.getter(getter(CreateTrainingJobRequest::enableManagedSpotTraining))
.setter(setter(Builder::enableManagedSpotTraining))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("EnableManagedSpotTraining").build())
.build();
private static final SdkField CHECKPOINT_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("CheckpointConfig")
.getter(getter(CreateTrainingJobRequest::checkpointConfig)).setter(setter(Builder::checkpointConfig))
.constructor(CheckpointConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("CheckpointConfig").build()).build();
private static final SdkField DEBUG_HOOK_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("DebugHookConfig")
.getter(getter(CreateTrainingJobRequest::debugHookConfig)).setter(setter(Builder::debugHookConfig))
.constructor(DebugHookConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("DebugHookConfig").build()).build();
private static final SdkField> DEBUG_RULE_CONFIGURATIONS_FIELD = SdkField
.> builder(MarshallingType.LIST)
.memberName("DebugRuleConfigurations")
.getter(getter(CreateTrainingJobRequest::debugRuleConfigurations))
.setter(setter(Builder::debugRuleConfigurations))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("DebugRuleConfigurations").build(),
ListTrait
.builder()
.memberLocationName(null)
.memberFieldInfo(
SdkField. builder(MarshallingType.SDK_POJO)
.constructor(DebugRuleConfiguration::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD)
.locationName("member").build()).build()).build()).build();
private static final SdkField TENSOR_BOARD_OUTPUT_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("TensorBoardOutputConfig")
.getter(getter(CreateTrainingJobRequest::tensorBoardOutputConfig)).setter(setter(Builder::tensorBoardOutputConfig))
.constructor(TensorBoardOutputConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("TensorBoardOutputConfig").build())
.build();
private static final SdkField EXPERIMENT_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("ExperimentConfig")
.getter(getter(CreateTrainingJobRequest::experimentConfig)).setter(setter(Builder::experimentConfig))
.constructor(ExperimentConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("ExperimentConfig").build()).build();
private static final SdkField PROFILER_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("ProfilerConfig")
.getter(getter(CreateTrainingJobRequest::profilerConfig)).setter(setter(Builder::profilerConfig))
.constructor(ProfilerConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("ProfilerConfig").build()).build();
private static final SdkField> PROFILER_RULE_CONFIGURATIONS_FIELD = SdkField
.> builder(MarshallingType.LIST)
.memberName("ProfilerRuleConfigurations")
.getter(getter(CreateTrainingJobRequest::profilerRuleConfigurations))
.setter(setter(Builder::profilerRuleConfigurations))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("ProfilerRuleConfigurations").build(),
ListTrait
.builder()
.memberLocationName(null)
.memberFieldInfo(
SdkField. builder(MarshallingType.SDK_POJO)
.constructor(ProfilerRuleConfiguration::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD)
.locationName("member").build()).build()).build()).build();
private static final SdkField> ENVIRONMENT_FIELD = SdkField
.> builder(MarshallingType.MAP)
.memberName("Environment")
.getter(getter(CreateTrainingJobRequest::environment))
.setter(setter(Builder::environment))
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("Environment").build(),
MapTrait.builder()
.keyLocationName("key")
.valueLocationName("value")
.valueFieldInfo(
SdkField. builder(MarshallingType.STRING)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD)
.locationName("value").build()).build()).build()).build();
private static final SdkField RETRY_STRATEGY_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("RetryStrategy")
.getter(getter(CreateTrainingJobRequest::retryStrategy)).setter(setter(Builder::retryStrategy))
.constructor(RetryStrategy::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("RetryStrategy").build()).build();
private static final SdkField REMOTE_DEBUG_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("RemoteDebugConfig")
.getter(getter(CreateTrainingJobRequest::remoteDebugConfig)).setter(setter(Builder::remoteDebugConfig))
.constructor(RemoteDebugConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("RemoteDebugConfig").build()).build();
private static final SdkField INFRA_CHECK_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("InfraCheckConfig")
.getter(getter(CreateTrainingJobRequest::infraCheckConfig)).setter(setter(Builder::infraCheckConfig))
.constructor(InfraCheckConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("InfraCheckConfig").build()).build();
private static final SdkField SESSION_CHAINING_CONFIG_FIELD = SdkField
. builder(MarshallingType.SDK_POJO).memberName("SessionChainingConfig")
.getter(getter(CreateTrainingJobRequest::sessionChainingConfig)).setter(setter(Builder::sessionChainingConfig))
.constructor(SessionChainingConfig::builder)
.traits(LocationTrait.builder().location(MarshallLocation.PAYLOAD).locationName("SessionChainingConfig").build())
.build();
private static final List> SDK_FIELDS = Collections.unmodifiableList(Arrays.asList(TRAINING_JOB_NAME_FIELD,
HYPER_PARAMETERS_FIELD, ALGORITHM_SPECIFICATION_FIELD, ROLE_ARN_FIELD, INPUT_DATA_CONFIG_FIELD,
OUTPUT_DATA_CONFIG_FIELD, RESOURCE_CONFIG_FIELD, VPC_CONFIG_FIELD, STOPPING_CONDITION_FIELD, TAGS_FIELD,
ENABLE_NETWORK_ISOLATION_FIELD, ENABLE_INTER_CONTAINER_TRAFFIC_ENCRYPTION_FIELD, ENABLE_MANAGED_SPOT_TRAINING_FIELD,
CHECKPOINT_CONFIG_FIELD, DEBUG_HOOK_CONFIG_FIELD, DEBUG_RULE_CONFIGURATIONS_FIELD, TENSOR_BOARD_OUTPUT_CONFIG_FIELD,
EXPERIMENT_CONFIG_FIELD, PROFILER_CONFIG_FIELD, PROFILER_RULE_CONFIGURATIONS_FIELD, ENVIRONMENT_FIELD,
RETRY_STRATEGY_FIELD, REMOTE_DEBUG_CONFIG_FIELD, INFRA_CHECK_CONFIG_FIELD, SESSION_CHAINING_CONFIG_FIELD));
private final String trainingJobName;
private final Map hyperParameters;
private final AlgorithmSpecification algorithmSpecification;
private final String roleArn;
private final List inputDataConfig;
private final OutputDataConfig outputDataConfig;
private final ResourceConfig resourceConfig;
private final VpcConfig vpcConfig;
private final StoppingCondition stoppingCondition;
private final List tags;
private final Boolean enableNetworkIsolation;
private final Boolean enableInterContainerTrafficEncryption;
private final Boolean enableManagedSpotTraining;
private final CheckpointConfig checkpointConfig;
private final DebugHookConfig debugHookConfig;
private final List debugRuleConfigurations;
private final TensorBoardOutputConfig tensorBoardOutputConfig;
private final ExperimentConfig experimentConfig;
private final ProfilerConfig profilerConfig;
private final List profilerRuleConfigurations;
private final Map environment;
private final RetryStrategy retryStrategy;
private final RemoteDebugConfig remoteDebugConfig;
private final InfraCheckConfig infraCheckConfig;
private final SessionChainingConfig sessionChainingConfig;
private CreateTrainingJobRequest(BuilderImpl builder) {
super(builder);
this.trainingJobName = builder.trainingJobName;
this.hyperParameters = builder.hyperParameters;
this.algorithmSpecification = builder.algorithmSpecification;
this.roleArn = builder.roleArn;
this.inputDataConfig = builder.inputDataConfig;
this.outputDataConfig = builder.outputDataConfig;
this.resourceConfig = builder.resourceConfig;
this.vpcConfig = builder.vpcConfig;
this.stoppingCondition = builder.stoppingCondition;
this.tags = builder.tags;
this.enableNetworkIsolation = builder.enableNetworkIsolation;
this.enableInterContainerTrafficEncryption = builder.enableInterContainerTrafficEncryption;
this.enableManagedSpotTraining = builder.enableManagedSpotTraining;
this.checkpointConfig = builder.checkpointConfig;
this.debugHookConfig = builder.debugHookConfig;
this.debugRuleConfigurations = builder.debugRuleConfigurations;
this.tensorBoardOutputConfig = builder.tensorBoardOutputConfig;
this.experimentConfig = builder.experimentConfig;
this.profilerConfig = builder.profilerConfig;
this.profilerRuleConfigurations = builder.profilerRuleConfigurations;
this.environment = builder.environment;
this.retryStrategy = builder.retryStrategy;
this.remoteDebugConfig = builder.remoteDebugConfig;
this.infraCheckConfig = builder.infraCheckConfig;
this.sessionChainingConfig = builder.sessionChainingConfig;
}
/**
*
* The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web
* Services account.
*
*
* @return The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon
* Web Services account.
*/
public final String trainingJobName() {
return trainingJobName;
}
/**
* For responses, this returns true if the service returned a value for the HyperParameters property. This DOES NOT
* check that the value is non-empty (for which, you should check the {@code isEmpty()} method on the property).
* This is useful because the SDK will never return a null collection or map, but you may need to differentiate
* between the service returning nothing (or null) and the service returning an empty collection or map. For
* requests, this returns true if a value for the property was specified in the request builder, and false if a
* value was not specified.
*/
public final boolean hasHyperParameters() {
return hyperParameters != null && !(hyperParameters instanceof SdkAutoConstructMap);
}
/**
*
* Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start
* the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
*
*
* You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value is
* limited to 256 characters, as specified by the Length Constraint.
*
*
*
* Do not include any security-sensitive information including account access IDs, secrets or tokens in any
* hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your
* training job request and return an exception error.
*
*
*
* Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
*
*
* This method will never return null. If you would like to know whether the service returned this field (so that
* you can differentiate between null and empty), you can use the {@link #hasHyperParameters} method.
*
*
* @return Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you
* start the learning process. For a list of hyperparameters for each training algorithm provided by
* SageMaker, see Algorithms.
*
* You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and
* value is limited to 256 characters, as specified by the Length Constraint.
*
*
*
* Do not include any security-sensitive information including account access IDs, secrets or tokens in any
* hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject
* your training job request and return an exception error.
*
*/
public final Map hyperParameters() {
return hyperParameters;
}
/**
*
* The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata,
* including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about providing
* your own algorithms, see Using
* Your Own Algorithms with Amazon SageMaker.
*
*
* @return The registry path of the Docker image that contains the training algorithm and algorithm-specific
* metadata, including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about
* providing your own algorithms, see Using Your Own Algorithms
* with Amazon SageMaker.
*/
public final AlgorithmSpecification algorithmSpecification() {
return algorithmSpecification;
}
/**
*
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
*
*
* During model training, SageMaker needs your permission to read input data from an S3 bucket, download a Docker
* image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs,
* and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an IAM role. For more
* information, see SageMaker
* Roles.
*
*
*
* To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
* permission.
*
*
*
* @return The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
*
*
* During model training, SageMaker needs your permission to read input data from an S3 bucket, download a
* Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon
* CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks
* to an IAM role. For more information, see SageMaker Roles.
*
*
*
* To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
* permission.
*
*/
public final String roleArn() {
return roleArn;
}
/**
* For responses, this returns true if the service returned a value for the InputDataConfig property. This DOES NOT
* check that the value is non-empty (for which, you should check the {@code isEmpty()} method on the property).
* This is useful because the SDK will never return a null collection or map, but you may need to differentiate
* between the service returning nothing (or null) and the service returning an empty collection or map. For
* requests, this returns true if a value for the property was specified in the request builder, and false if a
* value was not specified.
*/
public final boolean hasInputDataConfig() {
return inputDataConfig != null && !(inputDataConfig instanceof SdkAutoConstructList);
}
/**
*
* An array of Channel objects. Each channel is a named input source. InputDataConfig
* describes the input data and its location.
*
*
* Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels of
* input data, training_data and validation_data. The configuration for each channel
* provides the S3, EFS, or FSx location where the input data is stored. It also provides information about the
* stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
*
*
* Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3
* bucket to a local directory in the Docker container, or makes it available as input streams. For example, if you
* specify an EFS location, input data files are available as input streams. They do not need to be downloaded.
*
*
* Your input must be in the same Amazon Web Services region as your training job.
*
*
* Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
*
*
* This method will never return null. If you would like to know whether the service returned this field (so that
* you can differentiate between null and empty), you can use the {@link #hasInputDataConfig} method.
*
*
* @return An array of Channel objects. Each channel is a named input source.
* InputDataConfig describes the input data and its location.
*
* Algorithms can accept input data from one or more channels. For example, an algorithm might have two
* channels of input data, training_data and validation_data. The configuration
* for each channel provides the S3, EFS, or FSx location where the input data is stored. It also provides
* information about the stored data: the MIME type, compression method, and whether the data is wrapped in
* RecordIO format.
*
*
* Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an
* S3 bucket to a local directory in the Docker container, or makes it available as input streams. For
* example, if you specify an EFS location, input data files are available as input streams. They do not
* need to be downloaded.
*
*
* Your input must be in the same Amazon Web Services region as your training job.
*/
public final List inputDataConfig() {
return inputDataConfig;
}
/**
*
* Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders for
* the artifacts.
*
*
* @return Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates
* subfolders for the artifacts.
*/
public final OutputDataConfig outputDataConfig() {
return outputDataConfig;
}
/**
*
* The resources, including the ML compute instances and ML storage volumes, to use for model training.
*
*
* ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML storage
* volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training data, choose
* File as the TrainingInputMode in the algorithm specification. For distributed training
* algorithms, specify an instance count greater than 1.
*
*
* @return The resources, including the ML compute instances and ML storage volumes, to use for model training.
*
* ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML
* storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the
* training data, choose File as the TrainingInputMode in the algorithm
* specification. For distributed training algorithms, specify an instance count greater than 1.
*/
public final ResourceConfig resourceConfig() {
return resourceConfig;
}
/**
*
* A VpcConfig object
* that specifies the VPC that you want your training job to connect to. Control access to and from your training
* container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon
* Virtual Private Cloud.
*
*
* @return A VpcConfig
* object that specifies the VPC that you want your training job to connect to. Control access to and from
* your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an
* Amazon Virtual Private Cloud.
*/
public final VpcConfig vpcConfig() {
return vpcConfig;
}
/**
*
* Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training
* job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap
* model training costs.
*
*
* To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for
* 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training
* are not lost.
*
*
* @return Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot
* training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use
* this API to cap model training costs.
*
* To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job
* termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so
* the results of training are not lost.
*/
public final StoppingCondition stoppingCondition() {
return stoppingCondition;
}
/**
* For responses, this returns true if the service returned a value for the Tags property. This DOES NOT check that
* the value is non-empty (for which, you should check the {@code isEmpty()} method on the property). This is useful
* because the SDK will never return a null collection or map, but you may need to differentiate between the service
* returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true
* if a value for the property was specified in the request builder, and false if a value was not specified.
*/
public final boolean hasTags() {
return tags != null && !(tags instanceof SdkAutoConstructList);
}
/**
*
* An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways,
* for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
*
*
* Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
*
*
* This method will never return null. If you would like to know whether the service returned this field (so that
* you can differentiate between null and empty), you can use the {@link #hasTags} method.
*
*
* @return An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in
* different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
* Resources.
*/
public final List tags() {
return tags;
}
/**
*
* Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers
* within a training cluster for distributed training. If you enable network isolation for training jobs that are
* configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified
* VPC, but the training container does not have network access.
*
*
* @return Isolates the training container. No inbound or outbound network calls can be made, except for calls
* between peers within a training cluster for distributed training. If you enable network isolation for
* training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model
* artifacts through the specified VPC, but the training container does not have network access.
*/
public final Boolean enableNetworkIsolation() {
return enableNetworkIsolation;
}
/**
*
* To encrypt all communications between ML compute instances in distributed training, choose True.
* Encryption provides greater security for distributed training, but training might take longer. How long it takes
* depends on the amount of communication between compute instances, especially if you use a deep learning algorithm
* in distributed training. For more information, see Protect Communications Between ML
* Compute Instances in a Distributed Training Job.
*
*
* @return To encrypt all communications between ML compute instances in distributed training, choose
* True. Encryption provides greater security for distributed training, but training might take
* longer. How long it takes depends on the amount of communication between compute instances, especially if
* you use a deep learning algorithm in distributed training. For more information, see Protect Communications Between
* ML Compute Instances in a Distributed Training Job.
*/
public final Boolean enableInterContainerTrafficEncryption() {
return enableInterContainerTrafficEncryption;
}
/**
*
* To train models using managed spot training, choose True. Managed spot training provides a fully
* managed and scalable infrastructure for training machine learning models. this option is useful when training
* jobs can be interrupted and when there is flexibility when the training job is run.
*
*
* The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a starting
* point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They can be used
* to see when managed spot training jobs are running, interrupted, resumed, or completed.
*
*
* @return To train models using managed spot training, choose True. Managed spot training provides a
* fully managed and scalable infrastructure for training machine learning models. this option is useful
* when training jobs can be interrupted and when there is flexibility when the training job is run.
*
* The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a
* starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch.
* They can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
*/
public final Boolean enableManagedSpotTraining() {
return enableManagedSpotTraining;
}
/**
*
* Contains information about the output location for managed spot training checkpoint data.
*
*
* @return Contains information about the output location for managed spot training checkpoint data.
*/
public final CheckpointConfig checkpointConfig() {
return checkpointConfig;
}
/**
* Returns the value of the DebugHookConfig property for this object.
*
* @return The value of the DebugHookConfig property for this object.
*/
public final DebugHookConfig debugHookConfig() {
return debugHookConfig;
}
/**
* For responses, this returns true if the service returned a value for the DebugRuleConfigurations property. This
* DOES NOT check that the value is non-empty (for which, you should check the {@code isEmpty()} method on the
* property). This is useful because the SDK will never return a null collection or map, but you may need to
* differentiate between the service returning nothing (or null) and the service returning an empty collection or
* map. For requests, this returns true if a value for the property was specified in the request builder, and false
* if a value was not specified.
*/
public final boolean hasDebugRuleConfigurations() {
return debugRuleConfigurations != null && !(debugRuleConfigurations instanceof SdkAutoConstructList);
}
/**
*
* Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
*
*
* Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
*
*
* This method will never return null. If you would like to know whether the service returned this field (so that
* you can differentiate between null and empty), you can use the {@link #hasDebugRuleConfigurations} method.
*
*
* @return Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
*/
public final List debugRuleConfigurations() {
return debugRuleConfigurations;
}
/**
* Returns the value of the TensorBoardOutputConfig property for this object.
*
* @return The value of the TensorBoardOutputConfig property for this object.
*/
public final TensorBoardOutputConfig tensorBoardOutputConfig() {
return tensorBoardOutputConfig;
}
/**
* Returns the value of the ExperimentConfig property for this object.
*
* @return The value of the ExperimentConfig property for this object.
*/
public final ExperimentConfig experimentConfig() {
return experimentConfig;
}
/**
* Returns the value of the ProfilerConfig property for this object.
*
* @return The value of the ProfilerConfig property for this object.
*/
public final ProfilerConfig profilerConfig() {
return profilerConfig;
}
/**
* For responses, this returns true if the service returned a value for the ProfilerRuleConfigurations property.
* This DOES NOT check that the value is non-empty (for which, you should check the {@code isEmpty()} method on the
* property). This is useful because the SDK will never return a null collection or map, but you may need to
* differentiate between the service returning nothing (or null) and the service returning an empty collection or
* map. For requests, this returns true if a value for the property was specified in the request builder, and false
* if a value was not specified.
*/
public final boolean hasProfilerRuleConfigurations() {
return profilerRuleConfigurations != null && !(profilerRuleConfigurations instanceof SdkAutoConstructList);
}
/**
*
* Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
*
*
* Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
*
*
* This method will never return null. If you would like to know whether the service returned this field (so that
* you can differentiate between null and empty), you can use the {@link #hasProfilerRuleConfigurations} method.
*
*
* @return Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
*/
public final List profilerRuleConfigurations() {
return profilerRuleConfigurations;
}
/**
* For responses, this returns true if the service returned a value for the Environment property. This DOES NOT
* check that the value is non-empty (for which, you should check the {@code isEmpty()} method on the property).
* This is useful because the SDK will never return a null collection or map, but you may need to differentiate
* between the service returning nothing (or null) and the service returning an empty collection or map. For
* requests, this returns true if a value for the property was specified in the request builder, and false if a
* value was not specified.
*/
public final boolean hasEnvironment() {
return environment != null && !(environment instanceof SdkAutoConstructMap);
}
/**
*
* The environment variables to set in the Docker container.
*
*
* Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
*
*
* This method will never return null. If you would like to know whether the service returned this field (so that
* you can differentiate between null and empty), you can use the {@link #hasEnvironment} method.
*
*
* @return The environment variables to set in the Docker container.
*/
public final Map environment() {
return environment;
}
/**
*
* The number of times to retry the job when the job fails due to an InternalServerError.
*
*
* @return The number of times to retry the job when the job fails due to an InternalServerError.
*/
public final RetryStrategy retryStrategy() {
return retryStrategy;
}
/**
*
* Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container
* through Amazon Web Services Systems Manager (SSM) for remote debugging.
*
*
* @return Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker,
* see Access a
* training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
*/
public final RemoteDebugConfig remoteDebugConfig() {
return remoteDebugConfig;
}
/**
*
* Contains information about the infrastructure health check configuration for the training job.
*
*
* @return Contains information about the infrastructure health check configuration for the training job.
*/
public final InfraCheckConfig infraCheckConfig() {
return infraCheckConfig;
}
/**
*
* Contains information about attribute-based access control (ABAC) for the training job.
*
*
* @return Contains information about attribute-based access control (ABAC) for the training job.
*/
public final SessionChainingConfig sessionChainingConfig() {
return sessionChainingConfig;
}
@Override
public Builder toBuilder() {
return new BuilderImpl(this);
}
public static Builder builder() {
return new BuilderImpl();
}
public static Class serializableBuilderClass() {
return BuilderImpl.class;
}
@Override
public final int hashCode() {
int hashCode = 1;
hashCode = 31 * hashCode + super.hashCode();
hashCode = 31 * hashCode + Objects.hashCode(trainingJobName());
hashCode = 31 * hashCode + Objects.hashCode(hasHyperParameters() ? hyperParameters() : null);
hashCode = 31 * hashCode + Objects.hashCode(algorithmSpecification());
hashCode = 31 * hashCode + Objects.hashCode(roleArn());
hashCode = 31 * hashCode + Objects.hashCode(hasInputDataConfig() ? inputDataConfig() : null);
hashCode = 31 * hashCode + Objects.hashCode(outputDataConfig());
hashCode = 31 * hashCode + Objects.hashCode(resourceConfig());
hashCode = 31 * hashCode + Objects.hashCode(vpcConfig());
hashCode = 31 * hashCode + Objects.hashCode(stoppingCondition());
hashCode = 31 * hashCode + Objects.hashCode(hasTags() ? tags() : null);
hashCode = 31 * hashCode + Objects.hashCode(enableNetworkIsolation());
hashCode = 31 * hashCode + Objects.hashCode(enableInterContainerTrafficEncryption());
hashCode = 31 * hashCode + Objects.hashCode(enableManagedSpotTraining());
hashCode = 31 * hashCode + Objects.hashCode(checkpointConfig());
hashCode = 31 * hashCode + Objects.hashCode(debugHookConfig());
hashCode = 31 * hashCode + Objects.hashCode(hasDebugRuleConfigurations() ? debugRuleConfigurations() : null);
hashCode = 31 * hashCode + Objects.hashCode(tensorBoardOutputConfig());
hashCode = 31 * hashCode + Objects.hashCode(experimentConfig());
hashCode = 31 * hashCode + Objects.hashCode(profilerConfig());
hashCode = 31 * hashCode + Objects.hashCode(hasProfilerRuleConfigurations() ? profilerRuleConfigurations() : null);
hashCode = 31 * hashCode + Objects.hashCode(hasEnvironment() ? environment() : null);
hashCode = 31 * hashCode + Objects.hashCode(retryStrategy());
hashCode = 31 * hashCode + Objects.hashCode(remoteDebugConfig());
hashCode = 31 * hashCode + Objects.hashCode(infraCheckConfig());
hashCode = 31 * hashCode + Objects.hashCode(sessionChainingConfig());
return hashCode;
}
@Override
public final boolean equals(Object obj) {
return super.equals(obj) && equalsBySdkFields(obj);
}
@Override
public final boolean equalsBySdkFields(Object obj) {
if (this == obj) {
return true;
}
if (obj == null) {
return false;
}
if (!(obj instanceof CreateTrainingJobRequest)) {
return false;
}
CreateTrainingJobRequest other = (CreateTrainingJobRequest) obj;
return Objects.equals(trainingJobName(), other.trainingJobName()) && hasHyperParameters() == other.hasHyperParameters()
&& Objects.equals(hyperParameters(), other.hyperParameters())
&& Objects.equals(algorithmSpecification(), other.algorithmSpecification())
&& Objects.equals(roleArn(), other.roleArn()) && hasInputDataConfig() == other.hasInputDataConfig()
&& Objects.equals(inputDataConfig(), other.inputDataConfig())
&& Objects.equals(outputDataConfig(), other.outputDataConfig())
&& Objects.equals(resourceConfig(), other.resourceConfig()) && Objects.equals(vpcConfig(), other.vpcConfig())
&& Objects.equals(stoppingCondition(), other.stoppingCondition()) && hasTags() == other.hasTags()
&& Objects.equals(tags(), other.tags())
&& Objects.equals(enableNetworkIsolation(), other.enableNetworkIsolation())
&& Objects.equals(enableInterContainerTrafficEncryption(), other.enableInterContainerTrafficEncryption())
&& Objects.equals(enableManagedSpotTraining(), other.enableManagedSpotTraining())
&& Objects.equals(checkpointConfig(), other.checkpointConfig())
&& Objects.equals(debugHookConfig(), other.debugHookConfig())
&& hasDebugRuleConfigurations() == other.hasDebugRuleConfigurations()
&& Objects.equals(debugRuleConfigurations(), other.debugRuleConfigurations())
&& Objects.equals(tensorBoardOutputConfig(), other.tensorBoardOutputConfig())
&& Objects.equals(experimentConfig(), other.experimentConfig())
&& Objects.equals(profilerConfig(), other.profilerConfig())
&& hasProfilerRuleConfigurations() == other.hasProfilerRuleConfigurations()
&& Objects.equals(profilerRuleConfigurations(), other.profilerRuleConfigurations())
&& hasEnvironment() == other.hasEnvironment() && Objects.equals(environment(), other.environment())
&& Objects.equals(retryStrategy(), other.retryStrategy())
&& Objects.equals(remoteDebugConfig(), other.remoteDebugConfig())
&& Objects.equals(infraCheckConfig(), other.infraCheckConfig())
&& Objects.equals(sessionChainingConfig(), other.sessionChainingConfig());
}
/**
* Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be
* redacted from this string using a placeholder value.
*/
@Override
public final String toString() {
return ToString.builder("CreateTrainingJobRequest").add("TrainingJobName", trainingJobName())
.add("HyperParameters", hasHyperParameters() ? hyperParameters() : null)
.add("AlgorithmSpecification", algorithmSpecification()).add("RoleArn", roleArn())
.add("InputDataConfig", hasInputDataConfig() ? inputDataConfig() : null)
.add("OutputDataConfig", outputDataConfig()).add("ResourceConfig", resourceConfig())
.add("VpcConfig", vpcConfig()).add("StoppingCondition", stoppingCondition())
.add("Tags", hasTags() ? tags() : null).add("EnableNetworkIsolation", enableNetworkIsolation())
.add("EnableInterContainerTrafficEncryption", enableInterContainerTrafficEncryption())
.add("EnableManagedSpotTraining", enableManagedSpotTraining()).add("CheckpointConfig", checkpointConfig())
.add("DebugHookConfig", debugHookConfig())
.add("DebugRuleConfigurations", hasDebugRuleConfigurations() ? debugRuleConfigurations() : null)
.add("TensorBoardOutputConfig", tensorBoardOutputConfig()).add("ExperimentConfig", experimentConfig())
.add("ProfilerConfig", profilerConfig())
.add("ProfilerRuleConfigurations", hasProfilerRuleConfigurations() ? profilerRuleConfigurations() : null)
.add("Environment", hasEnvironment() ? environment() : null).add("RetryStrategy", retryStrategy())
.add("RemoteDebugConfig", remoteDebugConfig()).add("InfraCheckConfig", infraCheckConfig())
.add("SessionChainingConfig", sessionChainingConfig()).build();
}
public final Optional getValueForField(String fieldName, Class clazz) {
switch (fieldName) {
case "TrainingJobName":
return Optional.ofNullable(clazz.cast(trainingJobName()));
case "HyperParameters":
return Optional.ofNullable(clazz.cast(hyperParameters()));
case "AlgorithmSpecification":
return Optional.ofNullable(clazz.cast(algorithmSpecification()));
case "RoleArn":
return Optional.ofNullable(clazz.cast(roleArn()));
case "InputDataConfig":
return Optional.ofNullable(clazz.cast(inputDataConfig()));
case "OutputDataConfig":
return Optional.ofNullable(clazz.cast(outputDataConfig()));
case "ResourceConfig":
return Optional.ofNullable(clazz.cast(resourceConfig()));
case "VpcConfig":
return Optional.ofNullable(clazz.cast(vpcConfig()));
case "StoppingCondition":
return Optional.ofNullable(clazz.cast(stoppingCondition()));
case "Tags":
return Optional.ofNullable(clazz.cast(tags()));
case "EnableNetworkIsolation":
return Optional.ofNullable(clazz.cast(enableNetworkIsolation()));
case "EnableInterContainerTrafficEncryption":
return Optional.ofNullable(clazz.cast(enableInterContainerTrafficEncryption()));
case "EnableManagedSpotTraining":
return Optional.ofNullable(clazz.cast(enableManagedSpotTraining()));
case "CheckpointConfig":
return Optional.ofNullable(clazz.cast(checkpointConfig()));
case "DebugHookConfig":
return Optional.ofNullable(clazz.cast(debugHookConfig()));
case "DebugRuleConfigurations":
return Optional.ofNullable(clazz.cast(debugRuleConfigurations()));
case "TensorBoardOutputConfig":
return Optional.ofNullable(clazz.cast(tensorBoardOutputConfig()));
case "ExperimentConfig":
return Optional.ofNullable(clazz.cast(experimentConfig()));
case "ProfilerConfig":
return Optional.ofNullable(clazz.cast(profilerConfig()));
case "ProfilerRuleConfigurations":
return Optional.ofNullable(clazz.cast(profilerRuleConfigurations()));
case "Environment":
return Optional.ofNullable(clazz.cast(environment()));
case "RetryStrategy":
return Optional.ofNullable(clazz.cast(retryStrategy()));
case "RemoteDebugConfig":
return Optional.ofNullable(clazz.cast(remoteDebugConfig()));
case "InfraCheckConfig":
return Optional.ofNullable(clazz.cast(infraCheckConfig()));
case "SessionChainingConfig":
return Optional.ofNullable(clazz.cast(sessionChainingConfig()));
default:
return Optional.empty();
}
}
@Override
public final List> sdkFields() {
return SDK_FIELDS;
}
private static Function getter(Function g) {
return obj -> g.apply((CreateTrainingJobRequest) obj);
}
private static BiConsumer setter(BiConsumer s) {
return (obj, val) -> s.accept((Builder) obj, val);
}
public interface Builder extends SageMakerRequest.Builder, SdkPojo, CopyableBuilder {
/**
*
* The name of the training job. The name must be unique within an Amazon Web Services Region in an Amazon Web
* Services account.
*
*
* @param trainingJobName
* The name of the training job. The name must be unique within an Amazon Web Services Region in an
* Amazon Web Services account.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder trainingJobName(String trainingJobName);
/**
*
* Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you
* start the learning process. For a list of hyperparameters for each training algorithm provided by SageMaker,
* see Algorithms.
*
*
* You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key and value
* is limited to 256 characters, as specified by the Length Constraint.
*
*
*
* Do not include any security-sensitive information including account access IDs, secrets or tokens in any
* hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will reject your
* training job request and return an exception error.
*
*
*
* @param hyperParameters
* Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before
* you start the learning process. For a list of hyperparameters for each training algorithm provided by
* SageMaker, see Algorithms.
*
*
* You can specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value pair. Each key
* and value is limited to 256 characters, as specified by the Length Constraint.
*
*
*
* Do not include any security-sensitive information including account access IDs, secrets or tokens in
* any hyperparameter field. If the use of security-sensitive credentials are detected, SageMaker will
* reject your training job request and return an exception error.
*
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder hyperParameters(Map hyperParameters);
/**
*
* The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata,
* including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about
* providing your own algorithms, see Using Your Own Algorithms with
* Amazon SageMaker.
*
*
* @param algorithmSpecification
* The registry path of the Docker image that contains the training algorithm and algorithm-specific
* metadata, including the input mode. For more information about algorithms provided by SageMaker, see
* Algorithms. For information
* about providing your own algorithms, see Using Your Own Algorithms
* with Amazon SageMaker.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification);
/**
*
* The registry path of the Docker image that contains the training algorithm and algorithm-specific metadata,
* including the input mode. For more information about algorithms provided by SageMaker, see Algorithms. For information about
* providing your own algorithms, see Using Your Own Algorithms with
* Amazon SageMaker.
*
* This is a convenience method that creates an instance of the {@link AlgorithmSpecification.Builder} avoiding
* the need to create one manually via {@link AlgorithmSpecification#builder()}.
*
*
* When the {@link Consumer} completes, {@link AlgorithmSpecification.Builder#build()} is called immediately and
* its result is passed to {@link #algorithmSpecification(AlgorithmSpecification)}.
*
* @param algorithmSpecification
* a consumer that will call methods on {@link AlgorithmSpecification.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #algorithmSpecification(AlgorithmSpecification)
*/
default Builder algorithmSpecification(Consumer algorithmSpecification) {
return algorithmSpecification(AlgorithmSpecification.builder().applyMutation(algorithmSpecification).build());
}
/**
*
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your behalf.
*
*
* During model training, SageMaker needs your permission to read input data from an S3 bucket, download a
* Docker image that contains training code, write model artifacts to an S3 bucket, write logs to Amazon
* CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of these tasks to an
* IAM role. For more information, see SageMaker Roles.
*
*
*
* To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
* permission.
*
*
*
* @param roleArn
* The Amazon Resource Name (ARN) of an IAM role that SageMaker can assume to perform tasks on your
* behalf.
*
* During model training, SageMaker needs your permission to read input data from an S3 bucket, download
* a Docker image that contains training code, write model artifacts to an S3 bucket, write logs to
* Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant permissions for all of
* these tasks to an IAM role. For more information, see SageMaker Roles.
*
*
*
* To be able to pass this role to SageMaker, the caller of this API must have the
* iam:PassRole permission.
*
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder roleArn(String roleArn);
/**
*
* An array of Channel objects. Each channel is a named input source. InputDataConfig
* describes the input data and its location.
*
*
* Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels
* of input data, training_data and validation_data. The configuration for each
* channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information
* about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
*
*
* Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3
* bucket to a local directory in the Docker container, or makes it available as input streams. For example, if
* you specify an EFS location, input data files are available as input streams. They do not need to be
* downloaded.
*
*
* Your input must be in the same Amazon Web Services region as your training job.
*
*
* @param inputDataConfig
* An array of Channel objects. Each channel is a named input source.
* InputDataConfig describes the input data and its location.
*
* Algorithms can accept input data from one or more channels. For example, an algorithm might have two
* channels of input data, training_data and validation_data. The configuration
* for each channel provides the S3, EFS, or FSx location where the input data is stored. It also
* provides information about the stored data: the MIME type, compression method, and whether the data is
* wrapped in RecordIO format.
*
*
* Depending on the input mode that the algorithm supports, SageMaker either copies input data files from
* an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For
* example, if you specify an EFS location, input data files are available as input streams. They do not
* need to be downloaded.
*
*
* Your input must be in the same Amazon Web Services region as your training job.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder inputDataConfig(Collection inputDataConfig);
/**
*
* An array of Channel objects. Each channel is a named input source. InputDataConfig
* describes the input data and its location.
*
*
* Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels
* of input data, training_data and validation_data. The configuration for each
* channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information
* about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
*
*
* Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3
* bucket to a local directory in the Docker container, or makes it available as input streams. For example, if
* you specify an EFS location, input data files are available as input streams. They do not need to be
* downloaded.
*
*
* Your input must be in the same Amazon Web Services region as your training job.
*
*
* @param inputDataConfig
* An array of Channel objects. Each channel is a named input source.
* InputDataConfig describes the input data and its location.
*
* Algorithms can accept input data from one or more channels. For example, an algorithm might have two
* channels of input data, training_data and validation_data. The configuration
* for each channel provides the S3, EFS, or FSx location where the input data is stored. It also
* provides information about the stored data: the MIME type, compression method, and whether the data is
* wrapped in RecordIO format.
*
*
* Depending on the input mode that the algorithm supports, SageMaker either copies input data files from
* an S3 bucket to a local directory in the Docker container, or makes it available as input streams. For
* example, if you specify an EFS location, input data files are available as input streams. They do not
* need to be downloaded.
*
*
* Your input must be in the same Amazon Web Services region as your training job.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder inputDataConfig(Channel... inputDataConfig);
/**
*
* An array of Channel objects. Each channel is a named input source. InputDataConfig
* describes the input data and its location.
*
*
* Algorithms can accept input data from one or more channels. For example, an algorithm might have two channels
* of input data, training_data and validation_data. The configuration for each
* channel provides the S3, EFS, or FSx location where the input data is stored. It also provides information
* about the stored data: the MIME type, compression method, and whether the data is wrapped in RecordIO format.
*
*
* Depending on the input mode that the algorithm supports, SageMaker either copies input data files from an S3
* bucket to a local directory in the Docker container, or makes it available as input streams. For example, if
* you specify an EFS location, input data files are available as input streams. They do not need to be
* downloaded.
*
*
* Your input must be in the same Amazon Web Services region as your training job.
*
* This is a convenience method that creates an instance of the
* {@link software.amazon.awssdk.services.sagemaker.model.Channel.Builder} avoiding the need to create one
* manually via {@link software.amazon.awssdk.services.sagemaker.model.Channel#builder()}.
*
*
* When the {@link Consumer} completes,
* {@link software.amazon.awssdk.services.sagemaker.model.Channel.Builder#build()} is called immediately and its
* result is passed to {@link #inputDataConfig(List)}.
*
* @param inputDataConfig
* a consumer that will call methods on
* {@link software.amazon.awssdk.services.sagemaker.model.Channel.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #inputDataConfig(java.util.Collection)
*/
Builder inputDataConfig(Consumer... inputDataConfig);
/**
*
* Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders
* for the artifacts.
*
*
* @param outputDataConfig
* Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates
* subfolders for the artifacts.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder outputDataConfig(OutputDataConfig outputDataConfig);
/**
*
* Specifies the path to the S3 location where you want to store model artifacts. SageMaker creates subfolders
* for the artifacts.
*
* This is a convenience method that creates an instance of the {@link OutputDataConfig.Builder} avoiding the
* need to create one manually via {@link OutputDataConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link OutputDataConfig.Builder#build()} is called immediately and its
* result is passed to {@link #outputDataConfig(OutputDataConfig)}.
*
* @param outputDataConfig
* a consumer that will call methods on {@link OutputDataConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #outputDataConfig(OutputDataConfig)
*/
default Builder outputDataConfig(Consumer outputDataConfig) {
return outputDataConfig(OutputDataConfig.builder().applyMutation(outputDataConfig).build());
}
/**
*
* The resources, including the ML compute instances and ML storage volumes, to use for model training.
*
*
* ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML
* storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training
* data, choose File as the TrainingInputMode in the algorithm specification. For
* distributed training algorithms, specify an instance count greater than 1.
*
*
* @param resourceConfig
* The resources, including the ML compute instances and ML storage volumes, to use for model training.
*
*
* ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML
* storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the
* training data, choose File as the TrainingInputMode in the algorithm
* specification. For distributed training algorithms, specify an instance count greater than 1.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder resourceConfig(ResourceConfig resourceConfig);
/**
*
* The resources, including the ML compute instances and ML storage volumes, to use for model training.
*
*
* ML storage volumes store model artifacts and incremental states. Training algorithms might also use ML
* storage volumes for scratch space. If you want SageMaker to use the ML storage volume to store the training
* data, choose File as the TrainingInputMode in the algorithm specification. For
* distributed training algorithms, specify an instance count greater than 1.
*
* This is a convenience method that creates an instance of the {@link ResourceConfig.Builder} avoiding the need
* to create one manually via {@link ResourceConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link ResourceConfig.Builder#build()} is called immediately and its
* result is passed to {@link #resourceConfig(ResourceConfig)}.
*
* @param resourceConfig
* a consumer that will call methods on {@link ResourceConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #resourceConfig(ResourceConfig)
*/
default Builder resourceConfig(Consumer resourceConfig) {
return resourceConfig(ResourceConfig.builder().applyMutation(resourceConfig).build());
}
/**
*
* A VpcConfig object
* that specifies the VPC that you want your training job to connect to. Control access to and from your
* training container by configuring the VPC. For more information, see Protect Training Jobs by Using an
* Amazon Virtual Private Cloud.
*
*
* @param vpcConfig
* A VpcConfig
* object that specifies the VPC that you want your training job to connect to. Control access to and
* from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using
* an Amazon Virtual Private Cloud.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder vpcConfig(VpcConfig vpcConfig);
/**
*
* A VpcConfig object
* that specifies the VPC that you want your training job to connect to. Control access to and from your
* training container by configuring the VPC. For more information, see Protect Training Jobs by Using an
* Amazon Virtual Private Cloud.
*
* This is a convenience method that creates an instance of the {@link VpcConfig.Builder} avoiding the need to
* create one manually via {@link VpcConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link VpcConfig.Builder#build()} is called immediately and its result
* is passed to {@link #vpcConfig(VpcConfig)}.
*
* @param vpcConfig
* a consumer that will call methods on {@link VpcConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #vpcConfig(VpcConfig)
*/
default Builder vpcConfig(Consumer vpcConfig) {
return vpcConfig(VpcConfig.builder().applyMutation(vpcConfig).build());
}
/**
*
* Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot
* training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this
* API to cap model training costs.
*
*
* To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination
* for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of
* training are not lost.
*
*
* @param stoppingCondition
* Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot
* training job has to complete. When the job reaches the time limit, SageMaker ends the training job.
* Use this API to cap model training costs.
*
* To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job
* termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so
* the results of training are not lost.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder stoppingCondition(StoppingCondition stoppingCondition);
/**
*
* Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot
* training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this
* API to cap model training costs.
*
*
* To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination
* for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of
* training are not lost.
*
* This is a convenience method that creates an instance of the {@link StoppingCondition.Builder} avoiding the
* need to create one manually via {@link StoppingCondition#builder()}.
*
*
* When the {@link Consumer} completes, {@link StoppingCondition.Builder#build()} is called immediately and its
* result is passed to {@link #stoppingCondition(StoppingCondition)}.
*
* @param stoppingCondition
* a consumer that will call methods on {@link StoppingCondition.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #stoppingCondition(StoppingCondition)
*/
default Builder stoppingCondition(Consumer stoppingCondition) {
return stoppingCondition(StoppingCondition.builder().applyMutation(stoppingCondition).build());
}
/**
*
* An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different
* ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
* Resources.
*
*
* @param tags
* An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in
* different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
* Resources.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder tags(Collection tags);
/**
*
* An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different
* ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
* Resources.
*
*
* @param tags
* An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in
* different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
* Resources.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder tags(Tag... tags);
/**
*
* An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different
* ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
* Resources.
*
* This is a convenience method that creates an instance of the
* {@link software.amazon.awssdk.services.sagemaker.model.Tag.Builder} avoiding the need to create one manually
* via {@link software.amazon.awssdk.services.sagemaker.model.Tag#builder()}.
*
*
* When the {@link Consumer} completes,
* {@link software.amazon.awssdk.services.sagemaker.model.Tag.Builder#build()} is called immediately and its
* result is passed to {@link #tags(List)}.
*
* @param tags
* a consumer that will call methods on
* {@link software.amazon.awssdk.services.sagemaker.model.Tag.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #tags(java.util.Collection)
*/
Builder tags(Consumer... tags);
/**
*
* Isolates the training container. No inbound or outbound network calls can be made, except for calls between
* peers within a training cluster for distributed training. If you enable network isolation for training jobs
* that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through
* the specified VPC, but the training container does not have network access.
*
*
* @param enableNetworkIsolation
* Isolates the training container. No inbound or outbound network calls can be made, except for calls
* between peers within a training cluster for distributed training. If you enable network isolation for
* training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and
* model artifacts through the specified VPC, but the training container does not have network access.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder enableNetworkIsolation(Boolean enableNetworkIsolation);
/**
*
* To encrypt all communications between ML compute instances in distributed training, choose True.
* Encryption provides greater security for distributed training, but training might take longer. How long it
* takes depends on the amount of communication between compute instances, especially if you use a deep learning
* algorithm in distributed training. For more information, see Protect Communications Between ML
* Compute Instances in a Distributed Training Job.
*
*
* @param enableInterContainerTrafficEncryption
* To encrypt all communications between ML compute instances in distributed training, choose
* True. Encryption provides greater security for distributed training, but training might
* take longer. How long it takes depends on the amount of communication between compute instances,
* especially if you use a deep learning algorithm in distributed training. For more information, see Protect Communications
* Between ML Compute Instances in a Distributed Training Job.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder enableInterContainerTrafficEncryption(Boolean enableInterContainerTrafficEncryption);
/**
*
* To train models using managed spot training, choose True. Managed spot training provides a fully
* managed and scalable infrastructure for training machine learning models. this option is useful when training
* jobs can be interrupted and when there is flexibility when the training job is run.
*
*
* The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a
* starting point to train models incrementally. Amazon SageMaker provides metrics and logs in CloudWatch. They
* can be used to see when managed spot training jobs are running, interrupted, resumed, or completed.
*
*
* @param enableManagedSpotTraining
* To train models using managed spot training, choose True. Managed spot training provides
* a fully managed and scalable infrastructure for training machine learning models. this option is
* useful when training jobs can be interrupted and when there is flexibility when the training job is
* run.
*
* The complete and intermediate results of jobs are stored in an Amazon S3 bucket, and can be used as a
* starting point to train models incrementally. Amazon SageMaker provides metrics and logs in
* CloudWatch. They can be used to see when managed spot training jobs are running, interrupted, resumed,
* or completed.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder enableManagedSpotTraining(Boolean enableManagedSpotTraining);
/**
*
* Contains information about the output location for managed spot training checkpoint data.
*
*
* @param checkpointConfig
* Contains information about the output location for managed spot training checkpoint data.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder checkpointConfig(CheckpointConfig checkpointConfig);
/**
*
* Contains information about the output location for managed spot training checkpoint data.
*
* This is a convenience method that creates an instance of the {@link CheckpointConfig.Builder} avoiding the
* need to create one manually via {@link CheckpointConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link CheckpointConfig.Builder#build()} is called immediately and its
* result is passed to {@link #checkpointConfig(CheckpointConfig)}.
*
* @param checkpointConfig
* a consumer that will call methods on {@link CheckpointConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #checkpointConfig(CheckpointConfig)
*/
default Builder checkpointConfig(Consumer checkpointConfig) {
return checkpointConfig(CheckpointConfig.builder().applyMutation(checkpointConfig).build());
}
/**
* Sets the value of the DebugHookConfig property for this object.
*
* @param debugHookConfig
* The new value for the DebugHookConfig property for this object.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder debugHookConfig(DebugHookConfig debugHookConfig);
/**
* Sets the value of the DebugHookConfig property for this object.
*
* This is a convenience method that creates an instance of the {@link DebugHookConfig.Builder} avoiding the
* need to create one manually via {@link DebugHookConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link DebugHookConfig.Builder#build()} is called immediately and its
* result is passed to {@link #debugHookConfig(DebugHookConfig)}.
*
* @param debugHookConfig
* a consumer that will call methods on {@link DebugHookConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #debugHookConfig(DebugHookConfig)
*/
default Builder debugHookConfig(Consumer debugHookConfig) {
return debugHookConfig(DebugHookConfig.builder().applyMutation(debugHookConfig).build());
}
/**
*
* Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
*
*
* @param debugRuleConfigurations
* Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder debugRuleConfigurations(Collection debugRuleConfigurations);
/**
*
* Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
*
*
* @param debugRuleConfigurations
* Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder debugRuleConfigurations(DebugRuleConfiguration... debugRuleConfigurations);
/**
*
* Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
*
* This is a convenience method that creates an instance of the
* {@link software.amazon.awssdk.services.sagemaker.model.DebugRuleConfiguration.Builder} avoiding the need to
* create one manually via
* {@link software.amazon.awssdk.services.sagemaker.model.DebugRuleConfiguration#builder()}.
*
*
* When the {@link Consumer} completes,
* {@link software.amazon.awssdk.services.sagemaker.model.DebugRuleConfiguration.Builder#build()} is called
* immediately and its result is passed to {@link #debugRuleConfigurations(List)}.
*
* @param debugRuleConfigurations
* a consumer that will call methods on
* {@link software.amazon.awssdk.services.sagemaker.model.DebugRuleConfiguration.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #debugRuleConfigurations(java.util.Collection)
*/
Builder debugRuleConfigurations(Consumer... debugRuleConfigurations);
/**
* Sets the value of the TensorBoardOutputConfig property for this object.
*
* @param tensorBoardOutputConfig
* The new value for the TensorBoardOutputConfig property for this object.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder tensorBoardOutputConfig(TensorBoardOutputConfig tensorBoardOutputConfig);
/**
* Sets the value of the TensorBoardOutputConfig property for this object.
*
* This is a convenience method that creates an instance of the {@link TensorBoardOutputConfig.Builder} avoiding
* the need to create one manually via {@link TensorBoardOutputConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link TensorBoardOutputConfig.Builder#build()} is called immediately
* and its result is passed to {@link #tensorBoardOutputConfig(TensorBoardOutputConfig)}.
*
* @param tensorBoardOutputConfig
* a consumer that will call methods on {@link TensorBoardOutputConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #tensorBoardOutputConfig(TensorBoardOutputConfig)
*/
default Builder tensorBoardOutputConfig(Consumer tensorBoardOutputConfig) {
return tensorBoardOutputConfig(TensorBoardOutputConfig.builder().applyMutation(tensorBoardOutputConfig).build());
}
/**
* Sets the value of the ExperimentConfig property for this object.
*
* @param experimentConfig
* The new value for the ExperimentConfig property for this object.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder experimentConfig(ExperimentConfig experimentConfig);
/**
* Sets the value of the ExperimentConfig property for this object.
*
* This is a convenience method that creates an instance of the {@link ExperimentConfig.Builder} avoiding the
* need to create one manually via {@link ExperimentConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link ExperimentConfig.Builder#build()} is called immediately and its
* result is passed to {@link #experimentConfig(ExperimentConfig)}.
*
* @param experimentConfig
* a consumer that will call methods on {@link ExperimentConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #experimentConfig(ExperimentConfig)
*/
default Builder experimentConfig(Consumer experimentConfig) {
return experimentConfig(ExperimentConfig.builder().applyMutation(experimentConfig).build());
}
/**
* Sets the value of the ProfilerConfig property for this object.
*
* @param profilerConfig
* The new value for the ProfilerConfig property for this object.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder profilerConfig(ProfilerConfig profilerConfig);
/**
* Sets the value of the ProfilerConfig property for this object.
*
* This is a convenience method that creates an instance of the {@link ProfilerConfig.Builder} avoiding the need
* to create one manually via {@link ProfilerConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link ProfilerConfig.Builder#build()} is called immediately and its
* result is passed to {@link #profilerConfig(ProfilerConfig)}.
*
* @param profilerConfig
* a consumer that will call methods on {@link ProfilerConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #profilerConfig(ProfilerConfig)
*/
default Builder profilerConfig(Consumer profilerConfig) {
return profilerConfig(ProfilerConfig.builder().applyMutation(profilerConfig).build());
}
/**
*
* Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
*
*
* @param profilerRuleConfigurations
* Configuration information for Amazon SageMaker Debugger rules for profiling system and framework
* metrics.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder profilerRuleConfigurations(Collection profilerRuleConfigurations);
/**
*
* Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
*
*
* @param profilerRuleConfigurations
* Configuration information for Amazon SageMaker Debugger rules for profiling system and framework
* metrics.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder profilerRuleConfigurations(ProfilerRuleConfiguration... profilerRuleConfigurations);
/**
*
* Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
*
* This is a convenience method that creates an instance of the
* {@link software.amazon.awssdk.services.sagemaker.model.ProfilerRuleConfiguration.Builder} avoiding the need
* to create one manually via
* {@link software.amazon.awssdk.services.sagemaker.model.ProfilerRuleConfiguration#builder()}.
*
*
* When the {@link Consumer} completes,
* {@link software.amazon.awssdk.services.sagemaker.model.ProfilerRuleConfiguration.Builder#build()} is called
* immediately and its result is passed to {@link #profilerRuleConfigurations(List)}.
*
* @param profilerRuleConfigurations
* a consumer that will call methods on
* {@link software.amazon.awssdk.services.sagemaker.model.ProfilerRuleConfiguration.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #profilerRuleConfigurations(java.util.Collection)
*/
Builder profilerRuleConfigurations(Consumer... profilerRuleConfigurations);
/**
*
* The environment variables to set in the Docker container.
*
*
* @param environment
* The environment variables to set in the Docker container.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder environment(Map environment);
/**
*
* The number of times to retry the job when the job fails due to an InternalServerError.
*
*
* @param retryStrategy
* The number of times to retry the job when the job fails due to an InternalServerError.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder retryStrategy(RetryStrategy retryStrategy);
/**
*
* The number of times to retry the job when the job fails due to an InternalServerError.
*
* This is a convenience method that creates an instance of the {@link RetryStrategy.Builder} avoiding the need
* to create one manually via {@link RetryStrategy#builder()}.
*
*
* When the {@link Consumer} completes, {@link RetryStrategy.Builder#build()} is called immediately and its
* result is passed to {@link #retryStrategy(RetryStrategy)}.
*
* @param retryStrategy
* a consumer that will call methods on {@link RetryStrategy.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #retryStrategy(RetryStrategy)
*/
default Builder retryStrategy(Consumer retryStrategy) {
return retryStrategy(RetryStrategy.builder().applyMutation(retryStrategy).build());
}
/**
*
* Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see
* Access a training
* container through Amazon Web Services Systems Manager (SSM) for remote debugging.
*
*
* @param remoteDebugConfig
* Configuration for remote debugging. To learn more about the remote debugging functionality of
* SageMaker, see Access a training
* container through Amazon Web Services Systems Manager (SSM) for remote debugging.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder remoteDebugConfig(RemoteDebugConfig remoteDebugConfig);
/**
*
* Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see
* Access a training
* container through Amazon Web Services Systems Manager (SSM) for remote debugging.
*
* This is a convenience method that creates an instance of the {@link RemoteDebugConfig.Builder} avoiding the
* need to create one manually via {@link RemoteDebugConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link RemoteDebugConfig.Builder#build()} is called immediately and its
* result is passed to {@link #remoteDebugConfig(RemoteDebugConfig)}.
*
* @param remoteDebugConfig
* a consumer that will call methods on {@link RemoteDebugConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #remoteDebugConfig(RemoteDebugConfig)
*/
default Builder remoteDebugConfig(Consumer remoteDebugConfig) {
return remoteDebugConfig(RemoteDebugConfig.builder().applyMutation(remoteDebugConfig).build());
}
/**
*
* Contains information about the infrastructure health check configuration for the training job.
*
*
* @param infraCheckConfig
* Contains information about the infrastructure health check configuration for the training job.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder infraCheckConfig(InfraCheckConfig infraCheckConfig);
/**
*
* Contains information about the infrastructure health check configuration for the training job.
*
* This is a convenience method that creates an instance of the {@link InfraCheckConfig.Builder} avoiding the
* need to create one manually via {@link InfraCheckConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link InfraCheckConfig.Builder#build()} is called immediately and its
* result is passed to {@link #infraCheckConfig(InfraCheckConfig)}.
*
* @param infraCheckConfig
* a consumer that will call methods on {@link InfraCheckConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #infraCheckConfig(InfraCheckConfig)
*/
default Builder infraCheckConfig(Consumer infraCheckConfig) {
return infraCheckConfig(InfraCheckConfig.builder().applyMutation(infraCheckConfig).build());
}
/**
*
* Contains information about attribute-based access control (ABAC) for the training job.
*
*
* @param sessionChainingConfig
* Contains information about attribute-based access control (ABAC) for the training job.
* @return Returns a reference to this object so that method calls can be chained together.
*/
Builder sessionChainingConfig(SessionChainingConfig sessionChainingConfig);
/**
*
* Contains information about attribute-based access control (ABAC) for the training job.
*
* This is a convenience method that creates an instance of the {@link SessionChainingConfig.Builder} avoiding
* the need to create one manually via {@link SessionChainingConfig#builder()}.
*
*
* When the {@link Consumer} completes, {@link SessionChainingConfig.Builder#build()} is called immediately and
* its result is passed to {@link #sessionChainingConfig(SessionChainingConfig)}.
*
* @param sessionChainingConfig
* a consumer that will call methods on {@link SessionChainingConfig.Builder}
* @return Returns a reference to this object so that method calls can be chained together.
* @see #sessionChainingConfig(SessionChainingConfig)
*/
default Builder sessionChainingConfig(Consumer sessionChainingConfig) {
return sessionChainingConfig(SessionChainingConfig.builder().applyMutation(sessionChainingConfig).build());
}
@Override
Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration);
@Override
Builder overrideConfiguration(Consumer builderConsumer);
}
static final class BuilderImpl extends SageMakerRequest.BuilderImpl implements Builder {
private String trainingJobName;
private Map hyperParameters = DefaultSdkAutoConstructMap.getInstance();
private AlgorithmSpecification algorithmSpecification;
private String roleArn;
private List inputDataConfig = DefaultSdkAutoConstructList.getInstance();
private OutputDataConfig outputDataConfig;
private ResourceConfig resourceConfig;
private VpcConfig vpcConfig;
private StoppingCondition stoppingCondition;
private List tags = DefaultSdkAutoConstructList.getInstance();
private Boolean enableNetworkIsolation;
private Boolean enableInterContainerTrafficEncryption;
private Boolean enableManagedSpotTraining;
private CheckpointConfig checkpointConfig;
private DebugHookConfig debugHookConfig;
private List debugRuleConfigurations = DefaultSdkAutoConstructList.getInstance();
private TensorBoardOutputConfig tensorBoardOutputConfig;
private ExperimentConfig experimentConfig;
private ProfilerConfig profilerConfig;
private List profilerRuleConfigurations = DefaultSdkAutoConstructList.getInstance();
private Map environment = DefaultSdkAutoConstructMap.getInstance();
private RetryStrategy retryStrategy;
private RemoteDebugConfig remoteDebugConfig;
private InfraCheckConfig infraCheckConfig;
private SessionChainingConfig sessionChainingConfig;
private BuilderImpl() {
}
private BuilderImpl(CreateTrainingJobRequest model) {
super(model);
trainingJobName(model.trainingJobName);
hyperParameters(model.hyperParameters);
algorithmSpecification(model.algorithmSpecification);
roleArn(model.roleArn);
inputDataConfig(model.inputDataConfig);
outputDataConfig(model.outputDataConfig);
resourceConfig(model.resourceConfig);
vpcConfig(model.vpcConfig);
stoppingCondition(model.stoppingCondition);
tags(model.tags);
enableNetworkIsolation(model.enableNetworkIsolation);
enableInterContainerTrafficEncryption(model.enableInterContainerTrafficEncryption);
enableManagedSpotTraining(model.enableManagedSpotTraining);
checkpointConfig(model.checkpointConfig);
debugHookConfig(model.debugHookConfig);
debugRuleConfigurations(model.debugRuleConfigurations);
tensorBoardOutputConfig(model.tensorBoardOutputConfig);
experimentConfig(model.experimentConfig);
profilerConfig(model.profilerConfig);
profilerRuleConfigurations(model.profilerRuleConfigurations);
environment(model.environment);
retryStrategy(model.retryStrategy);
remoteDebugConfig(model.remoteDebugConfig);
infraCheckConfig(model.infraCheckConfig);
sessionChainingConfig(model.sessionChainingConfig);
}
public final String getTrainingJobName() {
return trainingJobName;
}
public final void setTrainingJobName(String trainingJobName) {
this.trainingJobName = trainingJobName;
}
@Override
public final Builder trainingJobName(String trainingJobName) {
this.trainingJobName = trainingJobName;
return this;
}
public final Map getHyperParameters() {
if (hyperParameters instanceof SdkAutoConstructMap) {
return null;
}
return hyperParameters;
}
public final void setHyperParameters(Map hyperParameters) {
this.hyperParameters = HyperParametersCopier.copy(hyperParameters);
}
@Override
public final Builder hyperParameters(Map hyperParameters) {
this.hyperParameters = HyperParametersCopier.copy(hyperParameters);
return this;
}
public final AlgorithmSpecification.Builder getAlgorithmSpecification() {
return algorithmSpecification != null ? algorithmSpecification.toBuilder() : null;
}
public final void setAlgorithmSpecification(AlgorithmSpecification.BuilderImpl algorithmSpecification) {
this.algorithmSpecification = algorithmSpecification != null ? algorithmSpecification.build() : null;
}
@Override
public final Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification) {
this.algorithmSpecification = algorithmSpecification;
return this;
}
public final String getRoleArn() {
return roleArn;
}
public final void setRoleArn(String roleArn) {
this.roleArn = roleArn;
}
@Override
public final Builder roleArn(String roleArn) {
this.roleArn = roleArn;
return this;
}
public final List getInputDataConfig() {
List result = InputDataConfigCopier.copyToBuilder(this.inputDataConfig);
if (result instanceof SdkAutoConstructList) {
return null;
}
return result;
}
public final void setInputDataConfig(Collection inputDataConfig) {
this.inputDataConfig = InputDataConfigCopier.copyFromBuilder(inputDataConfig);
}
@Override
public final Builder inputDataConfig(Collection inputDataConfig) {
this.inputDataConfig = InputDataConfigCopier.copy(inputDataConfig);
return this;
}
@Override
@SafeVarargs
public final Builder inputDataConfig(Channel... inputDataConfig) {
inputDataConfig(Arrays.asList(inputDataConfig));
return this;
}
@Override
@SafeVarargs
public final Builder inputDataConfig(Consumer... inputDataConfig) {
inputDataConfig(Stream.of(inputDataConfig).map(c -> Channel.builder().applyMutation(c).build())
.collect(Collectors.toList()));
return this;
}
public final OutputDataConfig.Builder getOutputDataConfig() {
return outputDataConfig != null ? outputDataConfig.toBuilder() : null;
}
public final void setOutputDataConfig(OutputDataConfig.BuilderImpl outputDataConfig) {
this.outputDataConfig = outputDataConfig != null ? outputDataConfig.build() : null;
}
@Override
public final Builder outputDataConfig(OutputDataConfig outputDataConfig) {
this.outputDataConfig = outputDataConfig;
return this;
}
public final ResourceConfig.Builder getResourceConfig() {
return resourceConfig != null ? resourceConfig.toBuilder() : null;
}
public final void setResourceConfig(ResourceConfig.BuilderImpl resourceConfig) {
this.resourceConfig = resourceConfig != null ? resourceConfig.build() : null;
}
@Override
public final Builder resourceConfig(ResourceConfig resourceConfig) {
this.resourceConfig = resourceConfig;
return this;
}
public final VpcConfig.Builder getVpcConfig() {
return vpcConfig != null ? vpcConfig.toBuilder() : null;
}
public final void setVpcConfig(VpcConfig.BuilderImpl vpcConfig) {
this.vpcConfig = vpcConfig != null ? vpcConfig.build() : null;
}
@Override
public final Builder vpcConfig(VpcConfig vpcConfig) {
this.vpcConfig = vpcConfig;
return this;
}
public final StoppingCondition.Builder getStoppingCondition() {
return stoppingCondition != null ? stoppingCondition.toBuilder() : null;
}
public final void setStoppingCondition(StoppingCondition.BuilderImpl stoppingCondition) {
this.stoppingCondition = stoppingCondition != null ? stoppingCondition.build() : null;
}
@Override
public final Builder stoppingCondition(StoppingCondition stoppingCondition) {
this.stoppingCondition = stoppingCondition;
return this;
}
public final List getTags() {
List result = TagListCopier.copyToBuilder(this.tags);
if (result instanceof SdkAutoConstructList) {
return null;
}
return result;
}
public final void setTags(Collection tags) {
this.tags = TagListCopier.copyFromBuilder(tags);
}
@Override
public final Builder tags(Collection tags) {
this.tags = TagListCopier.copy(tags);
return this;
}
@Override
@SafeVarargs
public final Builder tags(Tag... tags) {
tags(Arrays.asList(tags));
return this;
}
@Override
@SafeVarargs
public final Builder tags(Consumer... tags) {
tags(Stream.of(tags).map(c -> Tag.builder().applyMutation(c).build()).collect(Collectors.toList()));
return this;
}
public final Boolean getEnableNetworkIsolation() {
return enableNetworkIsolation;
}
public final void setEnableNetworkIsolation(Boolean enableNetworkIsolation) {
this.enableNetworkIsolation = enableNetworkIsolation;
}
@Override
public final Builder enableNetworkIsolation(Boolean enableNetworkIsolation) {
this.enableNetworkIsolation = enableNetworkIsolation;
return this;
}
public final Boolean getEnableInterContainerTrafficEncryption() {
return enableInterContainerTrafficEncryption;
}
public final void setEnableInterContainerTrafficEncryption(Boolean enableInterContainerTrafficEncryption) {
this.enableInterContainerTrafficEncryption = enableInterContainerTrafficEncryption;
}
@Override
public final Builder enableInterContainerTrafficEncryption(Boolean enableInterContainerTrafficEncryption) {
this.enableInterContainerTrafficEncryption = enableInterContainerTrafficEncryption;
return this;
}
public final Boolean getEnableManagedSpotTraining() {
return enableManagedSpotTraining;
}
public final void setEnableManagedSpotTraining(Boolean enableManagedSpotTraining) {
this.enableManagedSpotTraining = enableManagedSpotTraining;
}
@Override
public final Builder enableManagedSpotTraining(Boolean enableManagedSpotTraining) {
this.enableManagedSpotTraining = enableManagedSpotTraining;
return this;
}
public final CheckpointConfig.Builder getCheckpointConfig() {
return checkpointConfig != null ? checkpointConfig.toBuilder() : null;
}
public final void setCheckpointConfig(CheckpointConfig.BuilderImpl checkpointConfig) {
this.checkpointConfig = checkpointConfig != null ? checkpointConfig.build() : null;
}
@Override
public final Builder checkpointConfig(CheckpointConfig checkpointConfig) {
this.checkpointConfig = checkpointConfig;
return this;
}
public final DebugHookConfig.Builder getDebugHookConfig() {
return debugHookConfig != null ? debugHookConfig.toBuilder() : null;
}
public final void setDebugHookConfig(DebugHookConfig.BuilderImpl debugHookConfig) {
this.debugHookConfig = debugHookConfig != null ? debugHookConfig.build() : null;
}
@Override
public final Builder debugHookConfig(DebugHookConfig debugHookConfig) {
this.debugHookConfig = debugHookConfig;
return this;
}
public final List getDebugRuleConfigurations() {
List result = DebugRuleConfigurationsCopier
.copyToBuilder(this.debugRuleConfigurations);
if (result instanceof SdkAutoConstructList) {
return null;
}
return result;
}
public final void setDebugRuleConfigurations(Collection debugRuleConfigurations) {
this.debugRuleConfigurations = DebugRuleConfigurationsCopier.copyFromBuilder(debugRuleConfigurations);
}
@Override
public final Builder debugRuleConfigurations(Collection debugRuleConfigurations) {
this.debugRuleConfigurations = DebugRuleConfigurationsCopier.copy(debugRuleConfigurations);
return this;
}
@Override
@SafeVarargs
public final Builder debugRuleConfigurations(DebugRuleConfiguration... debugRuleConfigurations) {
debugRuleConfigurations(Arrays.asList(debugRuleConfigurations));
return this;
}
@Override
@SafeVarargs
public final Builder debugRuleConfigurations(Consumer... debugRuleConfigurations) {
debugRuleConfigurations(Stream.of(debugRuleConfigurations)
.map(c -> DebugRuleConfiguration.builder().applyMutation(c).build()).collect(Collectors.toList()));
return this;
}
public final TensorBoardOutputConfig.Builder getTensorBoardOutputConfig() {
return tensorBoardOutputConfig != null ? tensorBoardOutputConfig.toBuilder() : null;
}
public final void setTensorBoardOutputConfig(TensorBoardOutputConfig.BuilderImpl tensorBoardOutputConfig) {
this.tensorBoardOutputConfig = tensorBoardOutputConfig != null ? tensorBoardOutputConfig.build() : null;
}
@Override
public final Builder tensorBoardOutputConfig(TensorBoardOutputConfig tensorBoardOutputConfig) {
this.tensorBoardOutputConfig = tensorBoardOutputConfig;
return this;
}
public final ExperimentConfig.Builder getExperimentConfig() {
return experimentConfig != null ? experimentConfig.toBuilder() : null;
}
public final void setExperimentConfig(ExperimentConfig.BuilderImpl experimentConfig) {
this.experimentConfig = experimentConfig != null ? experimentConfig.build() : null;
}
@Override
public final Builder experimentConfig(ExperimentConfig experimentConfig) {
this.experimentConfig = experimentConfig;
return this;
}
public final ProfilerConfig.Builder getProfilerConfig() {
return profilerConfig != null ? profilerConfig.toBuilder() : null;
}
public final void setProfilerConfig(ProfilerConfig.BuilderImpl profilerConfig) {
this.profilerConfig = profilerConfig != null ? profilerConfig.build() : null;
}
@Override
public final Builder profilerConfig(ProfilerConfig profilerConfig) {
this.profilerConfig = profilerConfig;
return this;
}
public final List getProfilerRuleConfigurations() {
List result = ProfilerRuleConfigurationsCopier
.copyToBuilder(this.profilerRuleConfigurations);
if (result instanceof SdkAutoConstructList) {
return null;
}
return result;
}
public final void setProfilerRuleConfigurations(
Collection profilerRuleConfigurations) {
this.profilerRuleConfigurations = ProfilerRuleConfigurationsCopier.copyFromBuilder(profilerRuleConfigurations);
}
@Override
public final Builder profilerRuleConfigurations(Collection profilerRuleConfigurations) {
this.profilerRuleConfigurations = ProfilerRuleConfigurationsCopier.copy(profilerRuleConfigurations);
return this;
}
@Override
@SafeVarargs
public final Builder profilerRuleConfigurations(ProfilerRuleConfiguration... profilerRuleConfigurations) {
profilerRuleConfigurations(Arrays.asList(profilerRuleConfigurations));
return this;
}
@Override
@SafeVarargs
public final Builder profilerRuleConfigurations(Consumer... profilerRuleConfigurations) {
profilerRuleConfigurations(Stream.of(profilerRuleConfigurations)
.map(c -> ProfilerRuleConfiguration.builder().applyMutation(c).build()).collect(Collectors.toList()));
return this;
}
public final Map getEnvironment() {
if (environment instanceof SdkAutoConstructMap) {
return null;
}
return environment;
}
public final void setEnvironment(Map environment) {
this.environment = TrainingEnvironmentMapCopier.copy(environment);
}
@Override
public final Builder environment(Map environment) {
this.environment = TrainingEnvironmentMapCopier.copy(environment);
return this;
}
public final RetryStrategy.Builder getRetryStrategy() {
return retryStrategy != null ? retryStrategy.toBuilder() : null;
}
public final void setRetryStrategy(RetryStrategy.BuilderImpl retryStrategy) {
this.retryStrategy = retryStrategy != null ? retryStrategy.build() : null;
}
@Override
public final Builder retryStrategy(RetryStrategy retryStrategy) {
this.retryStrategy = retryStrategy;
return this;
}
public final RemoteDebugConfig.Builder getRemoteDebugConfig() {
return remoteDebugConfig != null ? remoteDebugConfig.toBuilder() : null;
}
public final void setRemoteDebugConfig(RemoteDebugConfig.BuilderImpl remoteDebugConfig) {
this.remoteDebugConfig = remoteDebugConfig != null ? remoteDebugConfig.build() : null;
}
@Override
public final Builder remoteDebugConfig(RemoteDebugConfig remoteDebugConfig) {
this.remoteDebugConfig = remoteDebugConfig;
return this;
}
public final InfraCheckConfig.Builder getInfraCheckConfig() {
return infraCheckConfig != null ? infraCheckConfig.toBuilder() : null;
}
public final void setInfraCheckConfig(InfraCheckConfig.BuilderImpl infraCheckConfig) {
this.infraCheckConfig = infraCheckConfig != null ? infraCheckConfig.build() : null;
}
@Override
public final Builder infraCheckConfig(InfraCheckConfig infraCheckConfig) {
this.infraCheckConfig = infraCheckConfig;
return this;
}
public final SessionChainingConfig.Builder getSessionChainingConfig() {
return sessionChainingConfig != null ? sessionChainingConfig.toBuilder() : null;
}
public final void setSessionChainingConfig(SessionChainingConfig.BuilderImpl sessionChainingConfig) {
this.sessionChainingConfig = sessionChainingConfig != null ? sessionChainingConfig.build() : null;
}
@Override
public final Builder sessionChainingConfig(SessionChainingConfig sessionChainingConfig) {
this.sessionChainingConfig = sessionChainingConfig;
return this;
}
@Override
public Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) {
super.overrideConfiguration(overrideConfiguration);
return this;
}
@Override
public Builder overrideConfiguration(Consumer builderConsumer) {
super.overrideConfiguration(builderConsumer);
return this;
}
@Override
public CreateTrainingJobRequest build() {
return new CreateTrainingJobRequest(this);
}
@Override
public List> sdkFields() {
return SDK_FIELDS;
}
}
}