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Class: Aws::SageMaker::Types::CreateTransformJobRequest

Inherits:
Struct
  • Object
show all
Defined in:
(unknown)

Overview

Note:

When passing CreateTransformJobRequest as input to an Aws::Client method, you can use a vanilla Hash:

{
  transform_job_name: "TransformJobName", # required
  model_name: "ModelName", # required
  max_concurrent_transforms: 1,
  max_payload_in_mb: 1,
  batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord
  environment: {
    "TransformEnvironmentKey" => "TransformEnvironmentValue",
  },
  transform_input: { # required
    data_source: { # required
      s3_data_source: { # required
        s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile
        s3_uri: "S3Uri", # required
      },
    },
    content_type: "ContentType",
    compression_type: "None", # accepts None, Gzip
    split_type: "None", # accepts None, Line, RecordIO, TFRecord
  },
  transform_output: { # required
    s3_output_path: "S3Uri", # required
    accept: "Accept",
    assemble_with: "None", # accepts None, Line
    kms_key_id: "KmsKeyId",
  },
  transform_resources: { # required
    instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge
    instance_count: 1, # required
    volume_kms_key_id: "KmsKeyId",
  },
  tags: [
    {
      key: "TagKey", # required
      value: "TagValue", # required
    },
  ],
}

Instance Attribute Summary collapse

Instance Attribute Details

#batch_strategyString

Specifies the number of records to include in a mini-batch for an HTTP inference request. A record ** is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.

To enable the batch strategy, you must set SplitType to Line, RecordIO, or TFRecord.

To use only one record when making an HTTP invocation request to a container, set BatchStrategy to SingleRecord and SplitType to Line.

To fit as many records in a mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to MultiRecord and SplitType to Line.

Possible values:

  • MultiRecord
  • SingleRecord

Returns:

  • (String)

    Specifies the number of records to include in a mini-batch for an HTTP inference request.

#environmentHash<String,String>

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

Returns:

  • (Hash<String,String>)

    The environment variables to set in the Docker container.

#max_concurrent_transformsInteger

The maximum number of parallel requests that can be sent to each instance in a transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon SageMaker checks the optional execution-parameters to determine the optimal settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1. For more information on execution-parameters, see How Containers Serve Requests. For built-in algorithms, you don\'t need to set a value for MaxConcurrentTransforms.

Returns:

  • (Integer)

    The maximum number of parallel requests that can be sent to each instance in a transform job.

#max_payload_in_mbInteger

The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in MaxPayloadInMB must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB.

For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.

Returns:

  • (Integer)

    The maximum allowed size of the payload, in MB.

#model_nameString

The name of the model that you want to use for the transform job. ModelName must be the name of an existing Amazon SageMaker model within an AWS Region in an AWS account.

Returns:

  • (String)

    The name of the model that you want to use for the transform job.

#tagsArray<Types::Tag>

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

Returns:

  • (Array<Types::Tag>)

    (Optional) An array of key-value pairs.

#transform_inputTypes::TransformInput

Describes the input source and the way the transform job consumes it.

Returns:

#transform_job_nameString

The name of the transform job. The name must be unique within an AWS Region in an AWS account.

Returns:

  • (String)

    The name of the transform job.

#transform_outputTypes::TransformOutput

Describes the results of the transform job.

Returns:

#transform_resourcesTypes::TransformResources

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

Returns:

  • (Types::TransformResources)

    Describes the resources, including ML instance types and ML instance count, to use for the transform job.