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

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::AlgorithmValidationProfile

Includes:

Aws::Structure

Defined in:

lib/aws-sdk-sagemaker/types.rb

Overview

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: {
      "ParameterKey" => "ParameterValue",
    },
    input_data_config: [ # required
      {
        channel_name: "ChannelName", # required
        data_source: { # required
          s3_data_source: { # required
            s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile
            s3_uri: "S3Uri", # required
            s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key
            attribute_names: ["AttributeName"],
          },
        },
        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.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,
    },
  },
  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.

See Also:

• AWS API Documentation

Instance Attribute Summary

• #profile_name ⇒ String

  The name of the profile for the algorithm.

• #training_job_definition ⇒ Types::TrainingJobDefinition

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

• #transform_job_definition ⇒ Types::TransformJobDefinition

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

Instance Attribute Details

#profile_name ⇒ String

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)

# File 'lib/aws-sdk-sagemaker/types.rb', line 321

class AlgorithmValidationProfile < Struct.new(
  :profile_name,
  :training_job_definition,
  :transform_job_definition)
  include Aws::Structure
end

#training_job_definition ⇒ Types::TrainingJobDefinition

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

Returns:

• (Types::TrainingJobDefinition)

# File 'lib/aws-sdk-sagemaker/types.rb', line 321

class AlgorithmValidationProfile < Struct.new(
  :profile_name,
  :training_job_definition,
  :transform_job_definition)
  include Aws::Structure
end

#transform_job_definition ⇒ Types::TransformJobDefinition

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

Returns:

• (Types::TransformJobDefinition)

# File 'lib/aws-sdk-sagemaker/types.rb', line 321

class AlgorithmValidationProfile < Struct.new(
  :profile_name,
  :training_job_definition,
  :transform_job_definition)
  include Aws::Structure
end