com.amazonaws.services.sagemaker.model.ModelPackageContainerDefinition 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;
/**
*
* Describes the Docker container for the model package.
*
*
* @see AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class ModelPackageContainerDefinition implements Serializable, Cloneable, StructuredPojo {
/**
*
* The DNS host name for the Docker container.
*
*/
private String containerHostname;
/**
*
* The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
*
*
* If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must
* meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and
* registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon
* SageMaker.
*
*/
private String image;
/**
*
* An MD5 hash of the training algorithm that identifies the Docker image used for training.
*
*/
private String imageDigest;
/**
*
* The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point
* to a single gzip compressed tar archive (.tar.gz suffix).
*
*
*
* The model artifacts must be in an S3 bucket that is in the same region as the model package.
*
*
*/
private String modelDataUrl;
/**
*
* Specifies the location of ML model data to deploy during endpoint creation.
*
*/
private ModelDataSource modelDataSource;
/**
*
* The Amazon Web Services Marketplace product ID of the model package.
*
*/
private String productId;
/**
*
* The environment variables to set in the Docker container. Each key and value in the Environment
* string to string map can have length of up to 1024. We support up to 16 entries in the map.
*
*/
private java.util.Map environment;
/**
*
* A structure with Model Input details.
*
*/
private ModelInput modelInput;
/**
*
* The machine learning framework of the model package container image.
*
*/
private String framework;
/**
*
* The framework version of the Model Package Container Image.
*
*/
private String frameworkVersion;
/**
*
* The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that
* matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
*
*/
private String nearestModelName;
/**
*
* The additional data source that is used during inference in the Docker container for your model package.
*
*/
private AdditionalS3DataSource additionalS3DataSource;
/**
*
* The DNS host name for the Docker container.
*
*
* @param containerHostname
* The DNS host name for the Docker container.
*/
public void setContainerHostname(String containerHostname) {
this.containerHostname = containerHostname;
}
/**
*
* The DNS host name for the Docker container.
*
*
* @return The DNS host name for the Docker container.
*/
public String getContainerHostname() {
return this.containerHostname;
}
/**
*
* The DNS host name for the Docker container.
*
*
* @param containerHostname
* The DNS host name for the Docker container.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withContainerHostname(String containerHostname) {
setContainerHostname(containerHostname);
return this;
}
/**
*
* The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
*
*
* If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must
* meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and
* registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon
* SageMaker.
*
*
* @param image
* The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
*
* If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference
* code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and
* registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with
* Amazon SageMaker.
*/
public void setImage(String image) {
this.image = image;
}
/**
*
* The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
*
*
* If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must
* meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and
* registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon
* SageMaker.
*
*
* @return The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
*
* If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference
* code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and
* registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms
* with Amazon SageMaker.
*/
public String getImage() {
return this.image;
}
/**
*
* The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
*
*
* If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must
* meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and
* registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon
* SageMaker.
*
*
* @param image
* The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
*
* If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference
* code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and
* registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with
* Amazon SageMaker.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withImage(String image) {
setImage(image);
return this;
}
/**
*
* An MD5 hash of the training algorithm that identifies the Docker image used for training.
*
*
* @param imageDigest
* An MD5 hash of the training algorithm that identifies the Docker image used for training.
*/
public void setImageDigest(String imageDigest) {
this.imageDigest = imageDigest;
}
/**
*
* An MD5 hash of the training algorithm that identifies the Docker image used for training.
*
*
* @return An MD5 hash of the training algorithm that identifies the Docker image used for training.
*/
public String getImageDigest() {
return this.imageDigest;
}
/**
*
* An MD5 hash of the training algorithm that identifies the Docker image used for training.
*
*
* @param imageDigest
* An MD5 hash of the training algorithm that identifies the Docker image used for training.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withImageDigest(String imageDigest) {
setImageDigest(imageDigest);
return this;
}
/**
*
* The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point
* to a single gzip compressed tar archive (.tar.gz suffix).
*
*
*
* The model artifacts must be in an S3 bucket that is in the same region as the model package.
*
*
*
* @param modelDataUrl
* The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must
* point to a single gzip compressed tar archive (.tar.gz suffix).
*
* The model artifacts must be in an S3 bucket that is in the same region as the model package.
*
*/
public void setModelDataUrl(String modelDataUrl) {
this.modelDataUrl = modelDataUrl;
}
/**
*
* The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point
* to a single gzip compressed tar archive (.tar.gz suffix).
*
*
*
* The model artifacts must be in an S3 bucket that is in the same region as the model package.
*
*
*
* @return The Amazon S3 path where the model artifacts, which result from model training, are stored. This path
* must point to a single gzip compressed tar archive (.tar.gz suffix).
*
* The model artifacts must be in an S3 bucket that is in the same region as the model package.
*
*/
public String getModelDataUrl() {
return this.modelDataUrl;
}
/**
*
* The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point
* to a single gzip compressed tar archive (.tar.gz suffix).
*
*
*
* The model artifacts must be in an S3 bucket that is in the same region as the model package.
*
*
*
* @param modelDataUrl
* The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must
* point to a single gzip compressed tar archive (.tar.gz suffix).
*
* The model artifacts must be in an S3 bucket that is in the same region as the model package.
*
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withModelDataUrl(String modelDataUrl) {
setModelDataUrl(modelDataUrl);
return this;
}
/**
*
* Specifies the location of ML model data to deploy during endpoint creation.
*
*
* @param modelDataSource
* Specifies the location of ML model data to deploy during endpoint creation.
*/
public void setModelDataSource(ModelDataSource modelDataSource) {
this.modelDataSource = modelDataSource;
}
/**
*
* Specifies the location of ML model data to deploy during endpoint creation.
*
*
* @return Specifies the location of ML model data to deploy during endpoint creation.
*/
public ModelDataSource getModelDataSource() {
return this.modelDataSource;
}
/**
*
* Specifies the location of ML model data to deploy during endpoint creation.
*
*
* @param modelDataSource
* Specifies the location of ML model data to deploy during endpoint creation.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withModelDataSource(ModelDataSource modelDataSource) {
setModelDataSource(modelDataSource);
return this;
}
/**
*
* The Amazon Web Services Marketplace product ID of the model package.
*
*
* @param productId
* The Amazon Web Services Marketplace product ID of the model package.
*/
public void setProductId(String productId) {
this.productId = productId;
}
/**
*
* The Amazon Web Services Marketplace product ID of the model package.
*
*
* @return The Amazon Web Services Marketplace product ID of the model package.
*/
public String getProductId() {
return this.productId;
}
/**
*
* The Amazon Web Services Marketplace product ID of the model package.
*
*
* @param productId
* The Amazon Web Services Marketplace product ID of the model package.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withProductId(String productId) {
setProductId(productId);
return this;
}
/**
*
* The environment variables to set in the Docker container. Each key and value in the Environment
* string to string map can have length of up to 1024. We support up to 16 entries in the map.
*
*
* @return The environment variables to set in the Docker container. Each key and value in the
* Environment string to string map can have length of up to 1024. We support up to 16 entries
* in the map.
*/
public java.util.Map getEnvironment() {
return environment;
}
/**
*
* The environment variables to set in the Docker container. Each key and value in the Environment
* string to string map can have length of up to 1024. We support up to 16 entries in the map.
*
*
* @param environment
* The environment variables to set in the Docker container. Each key and value in the
* Environment string to string map can have length of up to 1024. We support up to 16 entries
* in the map.
*/
public void setEnvironment(java.util.Map environment) {
this.environment = environment;
}
/**
*
* The environment variables to set in the Docker container. Each key and value in the Environment
* string to string map can have length of up to 1024. We support up to 16 entries in the map.
*
*
* @param environment
* The environment variables to set in the Docker container. Each key and value in the
* Environment string to string map can have length of up to 1024. We support up to 16 entries
* in the map.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withEnvironment(java.util.Map environment) {
setEnvironment(environment);
return this;
}
/**
* Add a single Environment entry
*
* @see ModelPackageContainerDefinition#withEnvironment
* @returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition addEnvironmentEntry(String key, String value) {
if (null == this.environment) {
this.environment = new java.util.HashMap();
}
if (this.environment.containsKey(key))
throw new IllegalArgumentException("Duplicated keys (" + key.toString() + ") are provided.");
this.environment.put(key, value);
return this;
}
/**
* Removes all the entries added into Environment.
*
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition clearEnvironmentEntries() {
this.environment = null;
return this;
}
/**
*
* A structure with Model Input details.
*
*
* @param modelInput
* A structure with Model Input details.
*/
public void setModelInput(ModelInput modelInput) {
this.modelInput = modelInput;
}
/**
*
* A structure with Model Input details.
*
*
* @return A structure with Model Input details.
*/
public ModelInput getModelInput() {
return this.modelInput;
}
/**
*
* A structure with Model Input details.
*
*
* @param modelInput
* A structure with Model Input details.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withModelInput(ModelInput modelInput) {
setModelInput(modelInput);
return this;
}
/**
*
* The machine learning framework of the model package container image.
*
*
* @param framework
* The machine learning framework of the model package container image.
*/
public void setFramework(String framework) {
this.framework = framework;
}
/**
*
* The machine learning framework of the model package container image.
*
*
* @return The machine learning framework of the model package container image.
*/
public String getFramework() {
return this.framework;
}
/**
*
* The machine learning framework of the model package container image.
*
*
* @param framework
* The machine learning framework of the model package container image.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withFramework(String framework) {
setFramework(framework);
return this;
}
/**
*
* The framework version of the Model Package Container Image.
*
*
* @param frameworkVersion
* The framework version of the Model Package Container Image.
*/
public void setFrameworkVersion(String frameworkVersion) {
this.frameworkVersion = frameworkVersion;
}
/**
*
* The framework version of the Model Package Container Image.
*
*
* @return The framework version of the Model Package Container Image.
*/
public String getFrameworkVersion() {
return this.frameworkVersion;
}
/**
*
* The framework version of the Model Package Container Image.
*
*
* @param frameworkVersion
* The framework version of the Model Package Container Image.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withFrameworkVersion(String frameworkVersion) {
setFrameworkVersion(frameworkVersion);
return this;
}
/**
*
* The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that
* matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
*
*
* @param nearestModelName
* The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model
* that matches your model. You can find a list of benchmarked models by calling
* ListModelMetadata.
*/
public void setNearestModelName(String nearestModelName) {
this.nearestModelName = nearestModelName;
}
/**
*
* The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that
* matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
*
*
* @return The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model
* that matches your model. You can find a list of benchmarked models by calling
* ListModelMetadata.
*/
public String getNearestModelName() {
return this.nearestModelName;
}
/**
*
* The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that
* matches your model. You can find a list of benchmarked models by calling ListModelMetadata.
*
*
* @param nearestModelName
* The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model
* that matches your model. You can find a list of benchmarked models by calling
* ListModelMetadata.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withNearestModelName(String nearestModelName) {
setNearestModelName(nearestModelName);
return this;
}
/**
*
* The additional data source that is used during inference in the Docker container for your model package.
*
*
* @param additionalS3DataSource
* The additional data source that is used during inference in the Docker container for your model package.
*/
public void setAdditionalS3DataSource(AdditionalS3DataSource additionalS3DataSource) {
this.additionalS3DataSource = additionalS3DataSource;
}
/**
*
* The additional data source that is used during inference in the Docker container for your model package.
*
*
* @return The additional data source that is used during inference in the Docker container for your model package.
*/
public AdditionalS3DataSource getAdditionalS3DataSource() {
return this.additionalS3DataSource;
}
/**
*
* The additional data source that is used during inference in the Docker container for your model package.
*
*
* @param additionalS3DataSource
* The additional data source that is used during inference in the Docker container for your model package.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public ModelPackageContainerDefinition withAdditionalS3DataSource(AdditionalS3DataSource additionalS3DataSource) {
setAdditionalS3DataSource(additionalS3DataSource);
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 (getContainerHostname() != null)
sb.append("ContainerHostname: ").append(getContainerHostname()).append(",");
if (getImage() != null)
sb.append("Image: ").append(getImage()).append(",");
if (getImageDigest() != null)
sb.append("ImageDigest: ").append(getImageDigest()).append(",");
if (getModelDataUrl() != null)
sb.append("ModelDataUrl: ").append(getModelDataUrl()).append(",");
if (getModelDataSource() != null)
sb.append("ModelDataSource: ").append(getModelDataSource()).append(",");
if (getProductId() != null)
sb.append("ProductId: ").append(getProductId()).append(",");
if (getEnvironment() != null)
sb.append("Environment: ").append(getEnvironment()).append(",");
if (getModelInput() != null)
sb.append("ModelInput: ").append(getModelInput()).append(",");
if (getFramework() != null)
sb.append("Framework: ").append(getFramework()).append(",");
if (getFrameworkVersion() != null)
sb.append("FrameworkVersion: ").append(getFrameworkVersion()).append(",");
if (getNearestModelName() != null)
sb.append("NearestModelName: ").append(getNearestModelName()).append(",");
if (getAdditionalS3DataSource() != null)
sb.append("AdditionalS3DataSource: ").append(getAdditionalS3DataSource());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof ModelPackageContainerDefinition == false)
return false;
ModelPackageContainerDefinition other = (ModelPackageContainerDefinition) obj;
if (other.getContainerHostname() == null ^ this.getContainerHostname() == null)
return false;
if (other.getContainerHostname() != null && other.getContainerHostname().equals(this.getContainerHostname()) == false)
return false;
if (other.getImage() == null ^ this.getImage() == null)
return false;
if (other.getImage() != null && other.getImage().equals(this.getImage()) == false)
return false;
if (other.getImageDigest() == null ^ this.getImageDigest() == null)
return false;
if (other.getImageDigest() != null && other.getImageDigest().equals(this.getImageDigest()) == false)
return false;
if (other.getModelDataUrl() == null ^ this.getModelDataUrl() == null)
return false;
if (other.getModelDataUrl() != null && other.getModelDataUrl().equals(this.getModelDataUrl()) == false)
return false;
if (other.getModelDataSource() == null ^ this.getModelDataSource() == null)
return false;
if (other.getModelDataSource() != null && other.getModelDataSource().equals(this.getModelDataSource()) == false)
return false;
if (other.getProductId() == null ^ this.getProductId() == null)
return false;
if (other.getProductId() != null && other.getProductId().equals(this.getProductId()) == false)
return false;
if (other.getEnvironment() == null ^ this.getEnvironment() == null)
return false;
if (other.getEnvironment() != null && other.getEnvironment().equals(this.getEnvironment()) == false)
return false;
if (other.getModelInput() == null ^ this.getModelInput() == null)
return false;
if (other.getModelInput() != null && other.getModelInput().equals(this.getModelInput()) == false)
return false;
if (other.getFramework() == null ^ this.getFramework() == null)
return false;
if (other.getFramework() != null && other.getFramework().equals(this.getFramework()) == false)
return false;
if (other.getFrameworkVersion() == null ^ this.getFrameworkVersion() == null)
return false;
if (other.getFrameworkVersion() != null && other.getFrameworkVersion().equals(this.getFrameworkVersion()) == false)
return false;
if (other.getNearestModelName() == null ^ this.getNearestModelName() == null)
return false;
if (other.getNearestModelName() != null && other.getNearestModelName().equals(this.getNearestModelName()) == false)
return false;
if (other.getAdditionalS3DataSource() == null ^ this.getAdditionalS3DataSource() == null)
return false;
if (other.getAdditionalS3DataSource() != null && other.getAdditionalS3DataSource().equals(this.getAdditionalS3DataSource()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getContainerHostname() == null) ? 0 : getContainerHostname().hashCode());
hashCode = prime * hashCode + ((getImage() == null) ? 0 : getImage().hashCode());
hashCode = prime * hashCode + ((getImageDigest() == null) ? 0 : getImageDigest().hashCode());
hashCode = prime * hashCode + ((getModelDataUrl() == null) ? 0 : getModelDataUrl().hashCode());
hashCode = prime * hashCode + ((getModelDataSource() == null) ? 0 : getModelDataSource().hashCode());
hashCode = prime * hashCode + ((getProductId() == null) ? 0 : getProductId().hashCode());
hashCode = prime * hashCode + ((getEnvironment() == null) ? 0 : getEnvironment().hashCode());
hashCode = prime * hashCode + ((getModelInput() == null) ? 0 : getModelInput().hashCode());
hashCode = prime * hashCode + ((getFramework() == null) ? 0 : getFramework().hashCode());
hashCode = prime * hashCode + ((getFrameworkVersion() == null) ? 0 : getFrameworkVersion().hashCode());
hashCode = prime * hashCode + ((getNearestModelName() == null) ? 0 : getNearestModelName().hashCode());
hashCode = prime * hashCode + ((getAdditionalS3DataSource() == null) ? 0 : getAdditionalS3DataSource().hashCode());
return hashCode;
}
@Override
public ModelPackageContainerDefinition clone() {
try {
return (ModelPackageContainerDefinition) 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.ModelPackageContainerDefinitionMarshaller.getInstance().marshall(this, protocolMarshaller);
}
}