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Class: Aws::SageMaker::Types::AlgorithmValidationProfile
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::AlgorithmValidationProfile
- Defined in:
- (unknown)
Overview
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: {
"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",
},
},
}
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
-
#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).
#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.