Class: Aws::SageMaker::Types::AlgorithmValidationSpecification

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::AlgorithmValidationSpecification

Defined in:

(unknown)

Overview

Note:

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

{
  validation_role: "RoleArn", # required
  validation_profiles: [ # required
    {
      profile_name: "EntityName", # required
      training_job_definition: { # required
        training_input_mode: "Pipe", # required, accepts Pipe, File
        hyper_parameters: {
          "HyperParameterKey" => "HyperParameterValue",
        },
        input_data_config: [ # required
          {
            channel_name: "ChannelName", # required
            data_source: { # required
              s3_data_source: {
                s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile
                s3_uri: "S3Uri", # required
                s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key
                attribute_names: ["AttributeName"],
              },
              file_system_data_source: {
                file_system_id: "FileSystemId", # required
                file_system_access_mode: "rw", # required, accepts rw, ro
                file_system_type: "EFS", # required, accepts EFS, FSxLustre
                directory_path: "DirectoryPath", # required
              },
            },
            content_type: "ContentType",
            compression_type: "None", # accepts None, Gzip
            record_wrapper_type: "None", # accepts None, RecordIO
            input_mode: "Pipe", # accepts Pipe, File
            shuffle_config: {
              seed: 1, # required
            },
          },
        ],
        output_data_config: { # required
          kms_key_id: "KmsKeyId",
          s3_output_path: "S3Uri", # required
        },
        resource_config: { # required
          instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, 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.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge
          instance_count: 1, # required
          volume_size_in_gb: 1, # required
          volume_kms_key_id: "KmsKeyId",
        },
        stopping_condition: { # required
          max_runtime_in_seconds: 1,
          max_wait_time_in_seconds: 1,
        },
      },
      transform_job_definition: {
        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",
        },
      },
    },
  ],
}

Specifies configurations for one or more training jobs that Amazon SageMaker runs to test the algorithm.

Returned by:

• CreateAlgorithmInput#validation_specification
• DescribeAlgorithmOutput#validation_specification

See Also:

• AWS API Documentation

Instance Attribute Summary

• #validation_profiles ⇒ Array<Types::AlgorithmValidationProfile>

  An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that Amazon SageMaker runs to validate your algorithm.

• #validation_role ⇒ String

  The IAM roles that Amazon SageMaker uses to run the training jobs.

Instance Attribute Details

#validation_profiles ⇒ Array<Types::AlgorithmValidationProfile>

An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that Amazon SageMaker runs to validate your algorithm.

Returns:

• (Array<Types::AlgorithmValidationProfile>) —

  An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that Amazon SageMaker runs to validate your algorithm.

#validation_role ⇒ String

The IAM roles that Amazon SageMaker uses to run the training jobs.

Returns:

• (String) —

  The IAM roles that Amazon SageMaker uses to run the training jobs.