ContainerDefinitionOptions

class aws_cdk.aws_stepfunctions_tasks.ContainerDefinitionOptions(*, container_host_name=None, environment_variables=None, image=None, mode=None, model_package_name=None, model_s3_location=None)

Bases: object

(experimental) Properties to define a ContainerDefinition.

Parameters
  • container_host_name (Optional[str]) – (experimental) 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. Default: - None

  • environment_variables (Optional[TaskInput]) – (experimental) The environment variables to set in the Docker container. Default: - No variables

  • image (Optional[DockerImage]) – (experimental) The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored. Default: - None

  • mode (Optional[Mode]) – (experimental) Defines how many models the container hosts. Default: - Mode.SINGLE_MODEL

  • model_package_name (Optional[str]) – (experimental) The name or Amazon Resource Name (ARN) of the model package to use to create the model. Default: - None

  • model_s3_location (Optional[S3Location]) – (experimental) 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 Amazon SageMaker built-in algorithms, but not if you use your own algorithms. Default: - None

See

https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html

Stability

experimental

Attributes

container_host_name

(experimental) 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.

Default
  • None

Stability

experimental

Return type

Optional[str]

environment_variables

(experimental) The environment variables to set in the Docker container.

Default
  • No variables

Stability

experimental

Return type

Optional[TaskInput]

image

(experimental) The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.

Default
  • None

Stability

experimental

Return type

Optional[DockerImage]

mode

(experimental) Defines how many models the container hosts.

Default
  • Mode.SINGLE_MODEL

Stability

experimental

Return type

Optional[Mode]

model_package_name

(experimental) The name or Amazon Resource Name (ARN) of the model package to use to create the model.

Default
  • None

Stability

experimental

Return type

Optional[str]

model_s3_location

(experimental) 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 Amazon SageMaker built-in algorithms, but not if you use your own algorithms.

Default
  • None

Stability

experimental

Return type

Optional[S3Location]