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