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Class: Aws::SageMaker::Types::AlgorithmValidationProfile

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

Overview

Note:

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

{
  profile_name: "EntityName", # required
  training_job_definition: { # required
    training_input_mode: "Pipe", # required, accepts Pipe, File
    hyper_parameters: {
      "ParameterKey" => "ParameterValue",
    },
    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.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.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge
      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",
    },
  },
}

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 AWS Marketplace.

Instance Attribute Summary collapse

Instance Attribute Details

#profile_nameString

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).

Returns:

  • (String)

    The name of the profile for the algorithm.

#training_job_definitionTypes::TrainingJobDefinition

The TrainingJobDefinition object that describes the training job that Amazon SageMaker runs to validate your algorithm.

Returns:

  • (Types::TrainingJobDefinition)

    The TrainingJobDefinition object that describes the training job that Amazon SageMaker runs to validate your algorithm.

#transform_job_definitionTypes::TransformJobDefinition

The TransformJobDefinition object that describes the transform job that Amazon SageMaker runs to validate your algorithm.

Returns:

  • (Types::TransformJobDefinition)

    The TransformJobDefinition object that describes the transform job that Amazon SageMaker runs to validate your algorithm.