create_image `async` ¶

create_image(
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
    description: Optional[ImageDescription] = None,
    display_name: Optional[ImageDisplayName] = None,
    image_name: Optional[ImageName] = None,
    role_arn: Optional[RoleArn] = None,
    tags: Optional[TagList] = None,
) -> CreateImageResponse

Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see Bring your own SageMaker AI image.

Parameters:

description (Optional[ImageDescription], default: None ) –

The description of the image.
display_name (Optional[ImageDisplayName], default: None ) –

The display name of the image. If not provided, ImageName is displayed.
image_name (Optional[ImageName], default: None ) –

The name of the image. Must be unique to your account.
role_arn (Optional[RoleArn], default: None ) –

The ARN of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
tags (Optional[TagList], default: None ) –

A list of tags to apply to the image.

Raises:

ResourceInUse –

Resource being accessed is in use.
ResourceLimitExceeded –

You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_sagemaker/_services/async_sage_maker.py

async def create_image(
    self,
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
    description: Optional[
        "capo_sagemaker.types.image_description.ImageDescription"
    ] = None,
    display_name: Optional[
        "capo_sagemaker.types.image_display_name.ImageDisplayName"
    ] = None,
    image_name: Optional["capo_sagemaker.types.image_name.ImageName"] = None,
    role_arn: Optional["capo_sagemaker.types.role_arn.RoleArn"] = None,
    tags: Optional["capo_sagemaker.types.tag_list.TagList"] = None,
) -> "capo_sagemaker.types.create_image_response.CreateImageResponse":
    """<p>Creates a custom SageMaker AI image. A SageMaker AI image is a set of image versions. Each image version represents a container image stored in Amazon ECR. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/studio-byoi.html">Bring your own SageMaker AI image</a>.</p>

    Args:
        description: <p>The description of the image.</p>
        display_name: <p>The display name of the image. If not provided, <code>ImageName</code> is displayed.</p>
        image_name: <p>The name of the image. Must be unique to your account.</p>
        role_arn: <p>The ARN of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.</p>
        tags: <p>A list of tags to apply to the image.</p>

    Raises:
        capo_sagemaker.errors.resource_in_use.ResourceInUse: <p>Resource being accessed is in use.</p>
        capo_sagemaker.errors.resource_limit_exceeded.ResourceLimitExceeded: <p> You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. </p>
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_sagemaker.types.create_image_request.CreateImageRequest]",
    ) -> AsyncOperationResponse[
        "capo_sagemaker.types.create_image_response.CreateImageResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.create_image

        (
            output,
            http_response,
        ) = await capo_sagemaker._operations.sage_maker.create_image.async_create_image(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CreateImage")
    )
    input_: capo_sagemaker.types.create_image_request.CreateImageRequest = {}
    if description is not None:
        input_["description"] = description
    if display_name is not None:
        input_["display_name"] = display_name
    if image_name is not None:
        input_["image_name"] = image_name
    if role_arn is not None:
        input_["role_arn"] = role_arn
    if tags is not None:
        input_["tags"] = tags

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output

create_image async ¶

create_image `async` ¶