class Aws::SageMaker::Types::CreateModelPackageInput
@note When making an API call, you may pass CreateModelPackageInput
data as a hash: { model_package_name: "EntityName", model_package_group_name: "EntityName", model_package_description: "EntityDescription", inference_specification: { containers: [ # required { container_hostname: "ContainerHostname", image: "ContainerImage", # required image_digest: "ImageDigest", model_data_url: "Url", product_id: "ProductId", environment: { "EnvironmentKey" => "EnvironmentValue", }, }, ], supported_transform_instance_types: ["ml.m4.xlarge"], # 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 supported_realtime_inference_instance_types: ["ml.t2.medium"], # accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, 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.m5d.large, ml.m5d.xlarge, ml.m5d.2xlarge, ml.m5d.4xlarge, ml.m5d.12xlarge, ml.m5d.24xlarge, ml.c4.large, 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.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.large, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.12xlarge, ml.r5.24xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.12xlarge, ml.r5d.24xlarge, ml.inf1.xlarge, ml.inf1.2xlarge, ml.inf1.6xlarge, ml.inf1.24xlarge supported_content_types: ["ContentType"], # required supported_response_mime_types: ["ResponseMIMEType"], # required }, validation_specification: { validation_role: "RoleArn", # required validation_profiles: [ # required { profile_name: "EntityName", # required transform_job_definition: { # required 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", }, }, }, ], }, source_algorithm_specification: { source_algorithms: [ # required { model_data_url: "Url", algorithm_name: "ArnOrName", # required }, ], }, certify_for_marketplace: false, tags: [ { key: "TagKey", # required value: "TagValue", # required }, ], model_approval_status: "Approved", # accepts Approved, Rejected, PendingManualApproval metadata_properties: { commit_id: "MetadataPropertyValue", repository: "MetadataPropertyValue", generated_by: "MetadataPropertyValue", project_id: "MetadataPropertyValue", }, model_metrics: { model_quality: { statistics: { content_type: "ContentType", # required content_digest: "ContentDigest", s3_uri: "S3Uri", # required }, constraints: { content_type: "ContentType", # required content_digest: "ContentDigest", s3_uri: "S3Uri", # required }, }, model_data_quality: { statistics: { content_type: "ContentType", # required content_digest: "ContentDigest", s3_uri: "S3Uri", # required }, constraints: { content_type: "ContentType", # required content_digest: "ContentDigest", s3_uri: "S3Uri", # required }, }, bias: { report: { content_type: "ContentType", # required content_digest: "ContentDigest", s3_uri: "S3Uri", # required }, }, explainability: { report: { content_type: "ContentType", # required content_digest: "ContentDigest", s3_uri: "S3Uri", # required }, }, }, client_token: "ClientToken", }
@!attribute [rw] model_package_name
The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen). This parameter is required for unversioned models. It is not applicable to versioned models. @return [String]
@!attribute [rw] model_package_group_name
The name of the model group that this model version belongs to. This parameter is required for versioned models, and does not apply to unversioned models. @return [String]
@!attribute [rw] model_package_description
A description of the model package. @return [String]
@!attribute [rw] inference_specification
Specifies details about inference jobs that can be run with models based on this model package, including the following: * The Amazon ECR paths of containers that contain the inference code and model artifacts. * The instance types that the model package supports for transform jobs and real-time endpoints used for inference. * The input and output content formats that the model package supports for inference. @return [Types::InferenceSpecification]
@!attribute [rw] validation_specification
Specifies configurations for one or more transform jobs that Amazon SageMaker runs to test the model package. @return [Types::ModelPackageValidationSpecification]
@!attribute [rw] source_algorithm_specification
Details about the algorithm that was used to create the model package. @return [Types::SourceAlgorithmSpecification]
@!attribute [rw] certify_for_marketplace
Whether to certify the model package for listing on Amazon Web Services Marketplace. This parameter is optional for unversioned models, and does not apply to versioned models. @return [Boolean]
@!attribute [rw] tags
A list of key value pairs associated with the model. For more information, see [Tagging Amazon Web Services resources][1] in the *Amazon Web Services General Reference Guide*. [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html @return [Array<Types::Tag>]
@!attribute [rw] model_approval_status
Whether the model is approved for deployment. This parameter is optional for versioned models, and does not apply to unversioned models. For versioned models, the value of this parameter must be set to `Approved` to deploy the model. @return [String]
@!attribute [rw] metadata_properties
Metadata properties of the tracking entity, trial, or trial component. @return [Types::MetadataProperties]
@!attribute [rw] model_metrics
A structure that contains model metrics reports. @return [Types::ModelMetrics]
@!attribute [rw] client_token
A unique token that guarantees that the call to this API is idempotent. **A suitable default value is auto-generated.** You should normally not need to pass this option. @return [String]
@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackageInput AWS API Documentation
Constants
- SENSITIVE