class Aws::SageMaker::Types::CreateTransformJobRequest
@note When making an API call, you may pass CreateTransformJobRequest
data as a hash: { transform_job_name: "TransformJobName", # required model_name: "ModelName", # required max_concurrent_transforms: 1, model_client_config: { invocations_timeout_in_seconds: 1, invocations_max_retries: 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, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge instance_count: 1, # required volume_kms_key_id: "KmsKeyId", }, data_processing: { input_filter: "JsonPath", output_filter: "JsonPath", join_source: "Input", # accepts Input, None }, tags: [ { key: "TagKey", # required value: "TagValue", # required }, ], experiment_config: { experiment_name: "ExperimentEntityName", trial_name: "ExperimentEntityName", trial_component_display_name: "ExperimentEntityName", }, }
@!attribute [rw] transform_job_name
The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account. @return [String]
@!attribute [rw] model_name
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 Amazon Web Services Region in an Amazon Web Services account. @return [String]
@!attribute [rw] max_concurrent_transforms
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 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][1]. For built-in algorithms, you don't need to set a value for `MaxConcurrentTransforms`. [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests @return [Integer]
@!attribute [rw] model_client_config
Configures the timeout and maximum number of retries for processing a transform job invocation. @return [Types::ModelClientConfig]
@!attribute [rw] max_payload_in_mb
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. @return [Integer]
@!attribute [rw] batch_strategy
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 the `SplitType` property 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`. @return [String]
@!attribute [rw] environment
The environment variables to set in the Docker container. We support up to 16 key and values entries in the map. @return [Hash<String,String>]
@!attribute [rw] transform_input
Describes the input source and the way the transform job consumes it. @return [Types::TransformInput]
@!attribute [rw] transform_output
Describes the results of the transform job. @return [Types::TransformOutput]
@!attribute [rw] transform_resources
Describes the resources, including ML instance types and ML instance count, to use for the transform job. @return [Types::TransformResources]
@!attribute [rw] data_processing
The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see [Associate Prediction Results with their Corresponding Input Records][1]. [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html @return [Types::DataProcessing]
@!attribute [rw] tags
(Optional) An array of key-value pairs. For more information, see [Using Cost Allocation Tags][1] in the *Amazon Web Services Billing and Cost Management User Guide*. [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what @return [Array<Types::Tag>]
@!attribute [rw] experiment_config
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs: * CreateProcessingJob * CreateTrainingJob * CreateTransformJob @return [Types::ExperimentConfig]
@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTransformJobRequest AWS API Documentation
Constants
- SENSITIVE