ContainerDefinition(*, container_host_name=None, environment_variables=None, image=None, mode=None, model_package_name=None, model_s3_location=None)¶
(experimental) Describes the container, as part of model definition.
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
TaskInput]) – (experimental) The environment variables to set in the Docker container. Default: - No variables
DockerImage]) – (experimental) The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored. Default: - None
Mode]) – (experimental) Defines how many models the container hosts. Default: - Mode.SINGLE_MODEL
str]) – (experimental) The name or Amazon Resource Name (ARN) of the model package to use to create the model. Default: - None
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