ContainerDefinition
- class aws_cdk.aws_sagemaker_alpha.ContainerDefinition(*, image, container_hostname=None, environment=None, model_data=None)
Bases:
object
(experimental) Describes the container, as part of model definition.
- Parameters:
image (
ContainerImage
) – (experimental) The image used to start a container.container_hostname (
Optional
[str
]) – (experimental) Hostname of the container within an inference pipeline. For single container models, this field is ignored. When specifying a hostname for one ContainerDefinition in a pipeline, hostnames must be specified for all other ContainerDefinitions in that pipeline. Default: - Amazon SageMaker will automatically assign a unique name based on the position of this ContainerDefinition in an inference pipeline.environment (
Optional
[Mapping
[str
,str
]]) – (experimental) A map of environment variables to pass into the container. Default: - nonemodel_data (
Optional
[ModelData
]) – (experimental) S3 path to the model artifacts. Default: - none
- Stability:
experimental
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_sagemaker_alpha as sagemaker_alpha # container_image: sagemaker_alpha.ContainerImage # model_data: sagemaker_alpha.ModelData container_definition = sagemaker_alpha.ContainerDefinition( image=container_image, # the properties below are optional container_hostname="containerHostname", environment={ "environment_key": "environment" }, model_data=model_data )
Attributes
- container_hostname
(experimental) Hostname of the container within an inference pipeline.
For single container models, this field is ignored. When specifying a hostname for one ContainerDefinition in a pipeline, hostnames must be specified for all other ContainerDefinitions in that pipeline.
- Default:
Amazon SageMaker will automatically assign a unique name based on the position of
this ContainerDefinition in an inference pipeline.
- environment
(experimental) A map of environment variables to pass into the container.
- Default:
none
- Stability:
experimental
- image
(experimental) The image used to start a container.
- Stability:
experimental
- model_data
(experimental) S3 path to the model artifacts.
- Default:
none
- Stability:
experimental