Struct aws_sdk_sagemaker::model::ModelPackageContainerDefinition [−][src]
#[non_exhaustive]pub struct ModelPackageContainerDefinition {
pub container_hostname: Option<String>,
pub image: Option<String>,
pub image_digest: Option<String>,
pub model_data_url: Option<String>,
pub product_id: Option<String>,
pub environment: Option<HashMap<String, String>>,
}
Expand description
Describes the Docker container for the model package.
Fields (Non-exhaustive)
This struct is marked as non-exhaustive
Struct { .. }
syntax; cannot be matched against without a wildcard ..
; and struct update syntax will not work.container_hostname: Option<String>
The DNS host name for the Docker container.
image: Option<String>
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by Amazon SageMaker,
the inference code must meet Amazon SageMaker requirements. Amazon SageMaker supports both
registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon
SageMaker.
image_digest: Option<String>
An MD5 hash of the training algorithm that identifies the Docker image used for training.
model_data_url: Option<String>
The Amazon 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 model artifacts must be in an S3 bucket that is in the same region as the model package.
product_id: Option<String>
The Amazon Web Services Marketplace product ID of the model package.
environment: Option<HashMap<String, String>>
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.
Implementations
The DNS host name for the Docker container.
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
If you are using your own custom algorithm instead of an algorithm provided by Amazon SageMaker,
the inference code must meet Amazon SageMaker requirements. Amazon SageMaker supports both
registry/repository[:tag]
and registry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon
SageMaker.
An MD5 hash of the training algorithm that identifies the Docker image used for training.
The Amazon 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 model artifacts must be in an S3 bucket that is in the same region as the model package.
The Amazon Web Services Marketplace product ID of the model package.
Creates a new builder-style object to manufacture ModelPackageContainerDefinition
Trait Implementations
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
This method tests for !=
.
Auto Trait Implementations
impl Send for ModelPackageContainerDefinition
impl Sync for ModelPackageContainerDefinition
impl Unpin for ModelPackageContainerDefinition
Blanket Implementations
Mutably borrows from an owned value. Read more
Attaches the provided Subscriber
to this type, returning a
WithDispatch
wrapper. Read more
Attaches the current default Subscriber
to this type, returning a
WithDispatch
wrapper. Read more