@Generated(value="software.amazon.awssdk:codegen") public final class ContainerDefinition extends Object implements SdkPojo, Serializable, ToCopyableBuilder<ContainerDefinition.Builder,ContainerDefinition>
Describes the container, as part of model definition.
| Modifier and Type | Class and Description |
|---|---|
static interface |
ContainerDefinition.Builder |
| Modifier and Type | Method and Description |
|---|---|
static ContainerDefinition.Builder |
builder() |
String |
containerHostname()
This parameter is ignored for models that contain only a
PrimaryContainer. |
Map<String,String> |
environment()
The environment variables to set in the Docker container.
|
boolean |
equals(Object obj) |
boolean |
equalsBySdkFields(Object obj) |
<T> Optional<T> |
getValueForField(String fieldName,
Class<T> clazz) |
boolean |
hasEnvironment()
For responses, this returns true if the service returned a value for the Environment property.
|
int |
hashCode() |
String |
image()
The path where inference code is stored.
|
ImageConfig |
imageConfig()
Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon
Virtual Private Cloud (VPC).
|
String |
inferenceSpecificationName()
The inference specification name in the model package version.
|
ContainerMode |
mode()
Whether the container hosts a single model or multiple models.
|
String |
modeAsString()
Whether the container hosts a single model or multiple models.
|
String |
modelDataUrl()
The S3 path where the model artifacts, which result from model training, are stored.
|
String |
modelPackageName()
The name or Amazon Resource Name (ARN) of the model package to use to create the model.
|
MultiModelConfig |
multiModelConfig()
Specifies additional configuration for multi-model endpoints.
|
List<SdkField<?>> |
sdkFields() |
static Class<? extends ContainerDefinition.Builder> |
serializableBuilderClass() |
ContainerDefinition.Builder |
toBuilder() |
String |
toString()
Returns a string representation of this object.
|
clone, finalize, getClass, notify, notifyAll, wait, wait, waitcopypublic final String containerHostname()
This parameter is ignored for models that contain only a PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely
identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics
to Monitor an Inference Pipeline. If you don't specify a value for this parameter for a
ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned
based on the position of the ContainerDefinition in the pipeline. If you specify a value for the
ContainerHostName for any ContainerDefinition that is part of an inference pipeline,
you must specify a value for the ContainerHostName parameter of every
ContainerDefinition in that pipeline.
PrimaryContainer.
When a ContainerDefinition is part of an inference pipeline, the value of the parameter
uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and
Metrics to Monitor an Inference Pipeline. If you don't specify a value for this parameter for a
ContainerDefinition that is part of an inference pipeline, a unique name is automatically
assigned based on the position of the ContainerDefinition in the pipeline. If you specify a
value for the ContainerHostName for any ContainerDefinition that is part of an
inference pipeline, you must specify a value for the ContainerHostName parameter of every
ContainerDefinition in that pipeline.
public final String image()
The path where inference code is stored. This can be either in Amazon EC2 Container Registry or in a Docker
registry that is accessible from the same VPC that you configure for your endpoint. 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
registry/repository[:tag] and
registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms
with Amazon SageMakerpublic final ImageConfig imageConfig()
Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC). For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers
public final ContainerMode mode()
Whether the container hosts a single model or multiple models.
If the service returns an enum value that is not available in the current SDK version, mode will return
ContainerMode.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from
modeAsString().
ContainerModepublic final String modeAsString()
Whether the container hosts a single model or multiple models.
If the service returns an enum value that is not available in the current SDK version, mode will return
ContainerMode.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from
modeAsString().
ContainerModepublic final String modelDataUrl()
The 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 S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model
artifacts in ModelDataUrl.
The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.
If you provide a value for this parameter, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provide. Amazon Web Services STS is activated in your Amazon Web Services account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the
model artifacts in ModelDataUrl.
public final boolean hasEnvironment()
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 Map<String,String> 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.
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 hasEnvironment() method.
Environment string to string map can have length of up to 1024. We support up to 16 entries
in the map.public final String modelPackageName()
The name or Amazon Resource Name (ARN) of the model package to use to create the model.
public final String inferenceSpecificationName()
The inference specification name in the model package version.
public final MultiModelConfig multiModelConfig()
Specifies additional configuration for multi-model endpoints.
public ContainerDefinition.Builder toBuilder()
toBuilder in interface ToCopyableBuilder<ContainerDefinition.Builder,ContainerDefinition>public static ContainerDefinition.Builder builder()
public static Class<? extends ContainerDefinition.Builder> serializableBuilderClass()
public final boolean equalsBySdkFields(Object obj)
equalsBySdkFields in interface SdkPojopublic final String toString()
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