@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class CreateModelRequest extends AmazonWebServiceRequest implements Serializable, Cloneable
NOOP
Constructor and Description |
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CreateModelRequest() |
Modifier and Type | Method and Description |
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CreateModelRequest |
clone()
Creates a shallow clone of this object for all fields except the handler context.
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boolean |
equals(Object obj) |
List<ContainerDefinition> |
getContainers()
Specifies the containers in the inference pipeline.
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Boolean |
getEnableNetworkIsolation()
Isolates the model container.
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String |
getExecutionRoleArn()
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker
image for deployment on ML compute instances or for batch transform jobs.
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InferenceExecutionConfig |
getInferenceExecutionConfig()
Specifies details of how containers in a multi-container endpoint are called.
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String |
getModelName()
The name of the new model.
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ContainerDefinition |
getPrimaryContainer()
The location of the primary docker image containing inference code, associated artifacts, and custom environment
map that the inference code uses when the model is deployed for predictions.
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List<Tag> |
getTags()
An array of key-value pairs.
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VpcConfig |
getVpcConfig()
A VpcConfig object
that specifies the VPC that you want your model to connect to.
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int |
hashCode() |
Boolean |
isEnableNetworkIsolation()
Isolates the model container.
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void |
setContainers(Collection<ContainerDefinition> containers)
Specifies the containers in the inference pipeline.
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void |
setEnableNetworkIsolation(Boolean enableNetworkIsolation)
Isolates the model container.
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void |
setExecutionRoleArn(String executionRoleArn)
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker
image for deployment on ML compute instances or for batch transform jobs.
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void |
setInferenceExecutionConfig(InferenceExecutionConfig inferenceExecutionConfig)
Specifies details of how containers in a multi-container endpoint are called.
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void |
setModelName(String modelName)
The name of the new model.
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void |
setPrimaryContainer(ContainerDefinition primaryContainer)
The location of the primary docker image containing inference code, associated artifacts, and custom environment
map that the inference code uses when the model is deployed for predictions.
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void |
setTags(Collection<Tag> tags)
An array of key-value pairs.
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void |
setVpcConfig(VpcConfig vpcConfig)
A VpcConfig object
that specifies the VPC that you want your model to connect to.
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String |
toString()
Returns a string representation of this object.
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CreateModelRequest |
withContainers(Collection<ContainerDefinition> containers)
Specifies the containers in the inference pipeline.
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CreateModelRequest |
withContainers(ContainerDefinition... containers)
Specifies the containers in the inference pipeline.
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CreateModelRequest |
withEnableNetworkIsolation(Boolean enableNetworkIsolation)
Isolates the model container.
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CreateModelRequest |
withExecutionRoleArn(String executionRoleArn)
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker
image for deployment on ML compute instances or for batch transform jobs.
|
CreateModelRequest |
withInferenceExecutionConfig(InferenceExecutionConfig inferenceExecutionConfig)
Specifies details of how containers in a multi-container endpoint are called.
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CreateModelRequest |
withModelName(String modelName)
The name of the new model.
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CreateModelRequest |
withPrimaryContainer(ContainerDefinition primaryContainer)
The location of the primary docker image containing inference code, associated artifacts, and custom environment
map that the inference code uses when the model is deployed for predictions.
|
CreateModelRequest |
withTags(Collection<Tag> tags)
An array of key-value pairs.
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CreateModelRequest |
withTags(Tag... tags)
An array of key-value pairs.
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CreateModelRequest |
withVpcConfig(VpcConfig vpcConfig)
A VpcConfig object
that specifies the VPC that you want your model to connect to.
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addHandlerContext, getCloneRoot, getCloneSource, getCustomQueryParameters, getCustomRequestHeaders, getGeneralProgressListener, getHandlerContext, getReadLimit, getRequestClientOptions, getRequestCredentials, getRequestCredentialsProvider, getRequestMetricCollector, getSdkClientExecutionTimeout, getSdkRequestTimeout, putCustomQueryParameter, putCustomRequestHeader, setGeneralProgressListener, setRequestCredentials, setRequestCredentialsProvider, setRequestMetricCollector, setSdkClientExecutionTimeout, setSdkRequestTimeout, withGeneralProgressListener, withRequestCredentialsProvider, withRequestMetricCollector, withSdkClientExecutionTimeout, withSdkRequestTimeout
public void setModelName(String modelName)
The name of the new model.
modelName
- The name of the new model.public String getModelName()
The name of the new model.
public CreateModelRequest withModelName(String modelName)
The name of the new model.
modelName
- The name of the new model.public void setPrimaryContainer(ContainerDefinition primaryContainer)
The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
primaryContainer
- The location of the primary docker image containing inference code, associated artifacts, and custom
environment map that the inference code uses when the model is deployed for predictions.public ContainerDefinition getPrimaryContainer()
The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
public CreateModelRequest withPrimaryContainer(ContainerDefinition primaryContainer)
The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
primaryContainer
- The location of the primary docker image containing inference code, associated artifacts, and custom
environment map that the inference code uses when the model is deployed for predictions.public List<ContainerDefinition> getContainers()
Specifies the containers in the inference pipeline.
public void setContainers(Collection<ContainerDefinition> containers)
Specifies the containers in the inference pipeline.
containers
- Specifies the containers in the inference pipeline.public CreateModelRequest withContainers(ContainerDefinition... containers)
Specifies the containers in the inference pipeline.
NOTE: This method appends the values to the existing list (if any). Use
setContainers(java.util.Collection)
or withContainers(java.util.Collection)
if you want to
override the existing values.
containers
- Specifies the containers in the inference pipeline.public CreateModelRequest withContainers(Collection<ContainerDefinition> containers)
Specifies the containers in the inference pipeline.
containers
- Specifies the containers in the inference pipeline.public void setInferenceExecutionConfig(InferenceExecutionConfig inferenceExecutionConfig)
Specifies details of how containers in a multi-container endpoint are called.
inferenceExecutionConfig
- Specifies details of how containers in a multi-container endpoint are called.public InferenceExecutionConfig getInferenceExecutionConfig()
Specifies details of how containers in a multi-container endpoint are called.
public CreateModelRequest withInferenceExecutionConfig(InferenceExecutionConfig inferenceExecutionConfig)
Specifies details of how containers in a multi-container endpoint are called.
inferenceExecutionConfig
- Specifies details of how containers in a multi-container endpoint are called.public void setExecutionRoleArn(String executionRoleArn)
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. 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.
executionRoleArn
- The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and
docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute
instances is part of model hosting. 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 String getExecutionRoleArn()
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. 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.
To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole
permission.
public CreateModelRequest withExecutionRoleArn(String executionRoleArn)
The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute instances is part of model hosting. 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.
executionRoleArn
- The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and
docker image for deployment on ML compute instances or for batch transform jobs. Deploying on ML compute
instances is part of model hosting. 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 List<Tag> getTags()
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 void setTags(Collection<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.
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.public CreateModelRequest withTags(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.
NOTE: This method appends the values to the existing list (if any). Use
setTags(java.util.Collection)
or withTags(java.util.Collection)
if you want to override the
existing values.
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.public CreateModelRequest withTags(Collection<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.
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.public void setVpcConfig(VpcConfig vpcConfig)
A VpcConfig object
that specifies the VPC that you want your model to connect to. Control access to and from your model container by
configuring the VPC. VpcConfig
is used in hosting services and in batch transform. For more
information, see Protect Endpoints by
Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by
Using an Amazon Virtual Private Cloud.
vpcConfig
- A VpcConfig
object that specifies the VPC that you want your model to connect to. Control access to and from your
model container by configuring the VPC. VpcConfig
is used in hosting services and in batch
transform. For more information, see Protect Endpoints by Using an Amazon
Virtual Private Cloud and Protect Data in Batch Transform Jobs
by Using an Amazon Virtual Private Cloud.public VpcConfig getVpcConfig()
A VpcConfig object
that specifies the VPC that you want your model to connect to. Control access to and from your model container by
configuring the VPC. VpcConfig
is used in hosting services and in batch transform. For more
information, see Protect Endpoints by
Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by
Using an Amazon Virtual Private Cloud.
VpcConfig
is used in hosting services and in batch
transform. For more information, see Protect Endpoints by Using an Amazon
Virtual Private Cloud and Protect Data in Batch Transform
Jobs by Using an Amazon Virtual Private Cloud.public CreateModelRequest withVpcConfig(VpcConfig vpcConfig)
A VpcConfig object
that specifies the VPC that you want your model to connect to. Control access to and from your model container by
configuring the VPC. VpcConfig
is used in hosting services and in batch transform. For more
information, see Protect Endpoints by
Using an Amazon Virtual Private Cloud and Protect Data in Batch Transform Jobs by
Using an Amazon Virtual Private Cloud.
vpcConfig
- A VpcConfig
object that specifies the VPC that you want your model to connect to. Control access to and from your
model container by configuring the VPC. VpcConfig
is used in hosting services and in batch
transform. For more information, see Protect Endpoints by Using an Amazon
Virtual Private Cloud and Protect Data in Batch Transform Jobs
by Using an Amazon Virtual Private Cloud.public void setEnableNetworkIsolation(Boolean enableNetworkIsolation)
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
enableNetworkIsolation
- Isolates the model container. No inbound or outbound network calls can be made to or from the model
container.public Boolean getEnableNetworkIsolation()
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
public CreateModelRequest withEnableNetworkIsolation(Boolean enableNetworkIsolation)
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
enableNetworkIsolation
- Isolates the model container. No inbound or outbound network calls can be made to or from the model
container.public Boolean isEnableNetworkIsolation()
Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
public String toString()
toString
in class Object
Object.toString()
public CreateModelRequest clone()
AmazonWebServiceRequest
clone
in class AmazonWebServiceRequest
Object.clone()