class Aws::SageMaker::Types::AlgorithmValidationProfile

Defines a training job and a batch transform job that Amazon SageMaker runs to validate your algorithm.

The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace.

@note When making an API call, you may pass AlgorithmValidationProfile

data as a hash:

    {
      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, 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",
        },
      },
    }

@!attribute [rw] profile_name

The name of the profile for the algorithm. The name must have 1 to
63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
@return [String]

@!attribute [rw] training_job_definition

The `TrainingJobDefinition` object that describes the training job
that Amazon SageMaker runs to validate your algorithm.
@return [Types::TrainingJobDefinition]

@!attribute [rw] transform_job_definition

The `TransformJobDefinition` object that describes the transform job
that Amazon SageMaker runs to validate your algorithm.
@return [Types::TransformJobDefinition]

@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AlgorithmValidationProfile AWS API Documentation

Constants

SENSITIVE