com.amazonaws.services.sagemaker.model.HyperParameterTuningInstanceConfig Maven / Gradle / Ivy
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/*
* Copyright 2019-2024 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 com.amazonaws.services.sagemaker.model;
import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;
/**
*
* The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These
* resources include compute instances and storage volumes. Specify one or more compute instance configurations and
* allocation strategies to select resources (optional).
*
*
* @see AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class HyperParameterTuningInstanceConfig implements Serializable, Cloneable, StructuredPojo {
/**
*
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs)
* instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types:
* ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type
* descriptions.
*
*/
private String instanceType;
/**
*
* The number of instances of the type specified by InstanceType. Choose an instance count larger than
* 1 for distributed training algorithms. See Step 2: Launch a SageMaker
* Distributed Training Job Using the SageMaker Python SDK for more information.
*
*/
private Integer instanceCount;
/**
*
* The volume size in GB of the data to be processed for hyperparameter optimization (optional).
*
*/
private Integer volumeSizeInGB;
/**
*
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs)
* instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types:
* ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type
* descriptions.
*
*
* @param instanceType
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no
* GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs)
* instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance
* type descriptions.
* @see TrainingInstanceType
*/
public void setInstanceType(String instanceType) {
this.instanceType = instanceType;
}
/**
*
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs)
* instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types:
* ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type
* descriptions.
*
*
* @return The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose
* (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs)
* instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance
* type descriptions.
* @see TrainingInstanceType
*/
public String getInstanceType() {
return this.instanceType;
}
/**
*
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs)
* instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types:
* ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type
* descriptions.
*
*
* @param instanceType
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no
* GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs)
* instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance
* type descriptions.
* @return Returns a reference to this object so that method calls can be chained together.
* @see TrainingInstanceType
*/
public HyperParameterTuningInstanceConfig withInstanceType(String instanceType) {
setInstanceType(instanceType);
return this;
}
/**
*
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs)
* instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types:
* ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type
* descriptions.
*
*
* @param instanceType
* The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no
* GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs)
* instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance
* type descriptions.
* @return Returns a reference to this object so that method calls can be chained together.
* @see TrainingInstanceType
*/
public HyperParameterTuningInstanceConfig withInstanceType(TrainingInstanceType instanceType) {
this.instanceType = instanceType.toString();
return this;
}
/**
*
* The number of instances of the type specified by InstanceType. Choose an instance count larger than
* 1 for distributed training algorithms. See Step 2: Launch a SageMaker
* Distributed Training Job Using the SageMaker Python SDK for more information.
*
*
* @param instanceCount
* The number of instances of the type specified by InstanceType. Choose an instance count
* larger than 1 for distributed training algorithms. See Step 2: Launch a
* SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
*/
public void setInstanceCount(Integer instanceCount) {
this.instanceCount = instanceCount;
}
/**
*
* The number of instances of the type specified by InstanceType. Choose an instance count larger than
* 1 for distributed training algorithms. See Step 2: Launch a SageMaker
* Distributed Training Job Using the SageMaker Python SDK for more information.
*
*
* @return The number of instances of the type specified by InstanceType. Choose an instance count
* larger than 1 for distributed training algorithms. See Step 2: Launch a
* SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
*/
public Integer getInstanceCount() {
return this.instanceCount;
}
/**
*
* The number of instances of the type specified by InstanceType. Choose an instance count larger than
* 1 for distributed training algorithms. See Step 2: Launch a SageMaker
* Distributed Training Job Using the SageMaker Python SDK for more information.
*
*
* @param instanceCount
* The number of instances of the type specified by InstanceType. Choose an instance count
* larger than 1 for distributed training algorithms. See Step 2: Launch a
* SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public HyperParameterTuningInstanceConfig withInstanceCount(Integer instanceCount) {
setInstanceCount(instanceCount);
return this;
}
/**
*
* The volume size in GB of the data to be processed for hyperparameter optimization (optional).
*
*
* @param volumeSizeInGB
* The volume size in GB of the data to be processed for hyperparameter optimization (optional).
*/
public void setVolumeSizeInGB(Integer volumeSizeInGB) {
this.volumeSizeInGB = volumeSizeInGB;
}
/**
*
* The volume size in GB of the data to be processed for hyperparameter optimization (optional).
*
*
* @return The volume size in GB of the data to be processed for hyperparameter optimization (optional).
*/
public Integer getVolumeSizeInGB() {
return this.volumeSizeInGB;
}
/**
*
* The volume size in GB of the data to be processed for hyperparameter optimization (optional).
*
*
* @param volumeSizeInGB
* The volume size in GB of the data to be processed for hyperparameter optimization (optional).
* @return Returns a reference to this object so that method calls can be chained together.
*/
public HyperParameterTuningInstanceConfig withVolumeSizeInGB(Integer volumeSizeInGB) {
setVolumeSizeInGB(volumeSizeInGB);
return this;
}
/**
* 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.
*
* @return A string representation of this object.
*
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append("{");
if (getInstanceType() != null)
sb.append("InstanceType: ").append(getInstanceType()).append(",");
if (getInstanceCount() != null)
sb.append("InstanceCount: ").append(getInstanceCount()).append(",");
if (getVolumeSizeInGB() != null)
sb.append("VolumeSizeInGB: ").append(getVolumeSizeInGB());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof HyperParameterTuningInstanceConfig == false)
return false;
HyperParameterTuningInstanceConfig other = (HyperParameterTuningInstanceConfig) obj;
if (other.getInstanceType() == null ^ this.getInstanceType() == null)
return false;
if (other.getInstanceType() != null && other.getInstanceType().equals(this.getInstanceType()) == false)
return false;
if (other.getInstanceCount() == null ^ this.getInstanceCount() == null)
return false;
if (other.getInstanceCount() != null && other.getInstanceCount().equals(this.getInstanceCount()) == false)
return false;
if (other.getVolumeSizeInGB() == null ^ this.getVolumeSizeInGB() == null)
return false;
if (other.getVolumeSizeInGB() != null && other.getVolumeSizeInGB().equals(this.getVolumeSizeInGB()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getInstanceType() == null) ? 0 : getInstanceType().hashCode());
hashCode = prime * hashCode + ((getInstanceCount() == null) ? 0 : getInstanceCount().hashCode());
hashCode = prime * hashCode + ((getVolumeSizeInGB() == null) ? 0 : getVolumeSizeInGB().hashCode());
return hashCode;
}
@Override
public HyperParameterTuningInstanceConfig clone() {
try {
return (HyperParameterTuningInstanceConfig) super.clone();
} catch (CloneNotSupportedException e) {
throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e);
}
}
@com.amazonaws.annotation.SdkInternalApi
@Override
public void marshall(ProtocolMarshaller protocolMarshaller) {
com.amazonaws.services.sagemaker.model.transform.HyperParameterTuningInstanceConfigMarshaller.getInstance().marshall(this, protocolMarshaller);
}
}