CfnTransformJobMixinProps

class aws_cdk.cfn_property_mixins.aws_sagemaker.CfnTransformJobMixinProps(*, batch_strategy=None, data_capture_config=None, data_processing=None, environment=None, experiment_config=None, max_concurrent_transforms=None, max_payload_in_mb=None, model_client_config=None, model_name=None, tags=None, transform_input=None, transform_output=None, transform_resources=None)

Bases: object

Properties for CfnTransformJobPropsMixin.

Parameters:

batch_strategy (Optional[str]) – Specifies the number of records to include in a mini-batch for an HTTP inference request.
data_capture_config (Union[IResolvable, DataCaptureConfigProperty, Dict[str, Any], None]) – Configuration to control how SageMaker captures inference data.
data_processing (Union[IResolvable, DataProcessingProperty, Dict[str, Any], None]) – The data structure used to specify the data to be used for inference in a batch transform job.
environment (Union[IResolvable, Mapping[str, str], None]) – The environment variables to set in the Docker container.
experiment_config (Union[IResolvable, ExperimentConfigProperty, Dict[str, Any], None]) – Associates a SageMaker job as a trial component with an experiment and trial.
max_concurrent_transforms (Union[int, float, None]) – The maximum number of parallel requests that can be sent to each instance in a transform job.
max_payload_in_mb (Union[int, float, None]) – The maximum allowed size of the payload, in MB.
model_client_config (Union[IResolvable, ModelClientConfigProperty, Dict[str, Any], None]) – Configures the timeout and maximum number of retries for processing a transform job invocation.
model_name (Optional[str]) – The name of the model that you want to use for the transform job.
tags (Optional[Sequence[Union[TagsItemsProperty, Dict[str, Any]]]]) – An array of key-value pairs.
transform_input (Union[IResolvable, TransformInputProperty, Dict[str, Any], None]) – Describes the input source and the way the transform job consumes it.
transform_output (Union[IResolvable, TransformOutputProperty, Dict[str, Any], None]) – Describes the results of the transform job.
transform_resources (Union[IResolvable, TransformResourcesProperty, Dict[str, Any], None]) – Describes the resources, including ML instance types and ML instance count, to use for the transform job.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-transformjob.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker

cfn_transform_job_mixin_props = sagemaker.CfnTransformJobMixinProps(
    batch_strategy="batchStrategy",
    data_capture_config=sagemaker.CfnTransformJobPropsMixin.DataCaptureConfigProperty(
        destination_s3_uri="destinationS3Uri",
        generate_inference_id=False,
        kms_key_id="kmsKeyId"
    ),
    data_processing=sagemaker.CfnTransformJobPropsMixin.DataProcessingProperty(
        input_filter="inputFilter",
        join_source="joinSource",
        output_filter="outputFilter"
    ),
    environment={
        "environment_key": "environment"
    },
    experiment_config=sagemaker.CfnTransformJobPropsMixin.ExperimentConfigProperty(
        experiment_name="experimentName",
        trial_component_display_name="trialComponentDisplayName",
        trial_name="trialName"
    ),
    max_concurrent_transforms=123,
    max_payload_in_mb=123,
    model_client_config=sagemaker.CfnTransformJobPropsMixin.ModelClientConfigProperty(
        invocations_max_retries=123,
        invocations_timeout_in_seconds=123
    ),
    model_name="modelName",
    tags=[sagemaker.CfnTransformJobPropsMixin.TagsItemsProperty(
        key="key",
        value="value"
    )],
    transform_input=sagemaker.CfnTransformJobPropsMixin.TransformInputProperty(
        compression_type="compressionType",
        content_type="contentType",
        data_source=sagemaker.CfnTransformJobPropsMixin.DataSourceProperty(
            s3_data_source=sagemaker.CfnTransformJobPropsMixin.S3DataSourceProperty(
                s3_data_type="s3DataType",
                s3_uri="s3Uri"
            )
        ),
        split_type="splitType"
    ),
    transform_output=sagemaker.CfnTransformJobPropsMixin.TransformOutputProperty(
        accept="accept",
        assemble_with="assembleWith",
        kms_key_id="kmsKeyId",
        s3_output_path="s3OutputPath"
    ),
    transform_resources=sagemaker.CfnTransformJobPropsMixin.TransformResourcesProperty(
        instance_count=123,
        instance_type="instanceType",
        volume_kms_key_id="volumeKmsKeyId"
    )
)