本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。
更新模型版本的詳細資訊
您可以使用 AWS SDK for Python (Boto3) 或 Amazon SageMaker Studio 主控台來檢視和更新特定模型版本的詳細資訊。
重要
Amazon 將模型卡 SageMaker 整合到模型登錄檔中。在模型登錄檔中註冊的模型套件包含簡化的模型卡作為模型套件的元件。如需詳細資訊，請參閱模型套件模型卡結構描述 （Studio）。
檢視和更新模型版本的詳細資訊 （Boto3）
若要使用 Boto3 檢視模型版本的詳細資訊，請完成下列步驟。
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呼叫
list_model_packagesAPI操作以檢視模型群組中的模型版本。sm_client.list_model_packages(ModelPackageGroupName="ModelGroup1")系統會回應模型套件摘要的清單。您可以從此清單中取得模型版本的 Amazon Resource Name （ARN）。
{'ModelPackageSummaryList': [{'ModelPackageGroupName': 'AbaloneMPG-16039329888329896', 'ModelPackageVersion': 1, 'ModelPackageArn': 'arn:aws:sagemaker:us-east-2:123456789012:model-package/ModelGroup1/1', 'ModelPackageDescription': 'TestMe', 'CreationTime': datetime.datetime(2020, 10, 29, 1, 27, 46, 46000, tzinfo=tzlocal()), 'ModelPackageStatus': 'Completed', 'ModelApprovalStatus': 'Approved'}], 'ResponseMetadata': {'RequestId': '12345678-abcd-1234-abcd-aabbccddeeff', 'HTTPStatusCode': 200, 'HTTPHeaders': {'x-amzn-requestid': '12345678-abcd-1234-abcd-aabbccddeeff', 'content-type': 'application/x-amz-json-1.1', 'content-length': '349', 'date': 'Mon, 23 Nov 2020 04:56:50 GMT'}, 'RetryAttempts': 0}} -
呼叫
describe_model_package以查看模型版本的詳細資訊。您可以將您在呼叫輸出中取得的ARN模型版本的 傳遞給list_model_packages。sm_client.describe_model_package(ModelPackageName="arn:aws:sagemaker:us-east-2:123456789012:model-package/ModelGroup1/1")此呼叫的輸出是具有模型版本詳細資訊的JSON物件。
{'ModelPackageGroupName': 'ModelGroup1', 'ModelPackageVersion': 1, 'ModelPackageArn': 'arn:aws:sagemaker:us-east-2:123456789012:model-package/ModelGroup/1', 'ModelPackageDescription': 'Test Model', 'CreationTime': datetime.datetime(2020, 10, 29, 1, 27, 46, 46000, tzinfo=tzlocal()), 'InferenceSpecification': {'Containers': [{'Image': '257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:1.0-1-cpu-py3', 'ImageDigest': 'sha256:99fa602cff19aee33297a5926f8497ca7bcd2a391b7d600300204eef803bca66', 'ModelDataUrl': 's3://sagemaker-us-east-2-123456789012/ModelGroup1/pipelines-0gdonccek7o9-AbaloneTrain-stmiylhtIR/output/model.tar.gz'}], 'SupportedTransformInstanceTypes': ['ml.m5.xlarge'], 'SupportedRealtimeInferenceInstanceTypes': ['ml.t2.medium', 'ml.m5.xlarge'], 'SupportedContentTypes': ['text/csv'], 'SupportedResponseMIMETypes': ['text/csv']}, 'ModelPackageStatus': 'Completed', 'ModelPackageStatusDetails': {'ValidationStatuses': [], 'ImageScanStatuses': []}, 'CertifyForMarketplace': False, 'ModelApprovalStatus': 'PendingManualApproval', 'LastModifiedTime': datetime.datetime(2020, 10, 29, 1, 28, 0, 438000, tzinfo=tzlocal()), 'ResponseMetadata': {'RequestId': '12345678-abcd-1234-abcd-aabbccddeeff', 'HTTPStatusCode': 200, 'HTTPHeaders': {'x-amzn-requestid': '212345678-abcd-1234-abcd-aabbccddeeff', 'content-type': 'application/x-amz-json-1.1', 'content-length': '1038', 'date': 'Mon, 23 Nov 2020 04:59:38 GMT'}, 'RetryAttempts': 0}}
模型套件模型卡結構描述 （Studio）
與模型版本相關的所有詳細資訊都封裝在模型套件的模型卡中。模型套件的模型卡是 Amazon SageMaker 模型卡的特殊用途，其結構描述也經過簡化。模型套件模型卡結構描述顯示在下列可擴展下拉式清單中。
{ "title": "SageMakerModelCardSchema", "description": "Schema of a model package’s model card.", "version": "0.1.0", "type": "object", "additionalProperties": false, "properties": { "model_overview": { "description": "Overview about the model.", "type": "object", "additionalProperties": false, "properties": { "model_creator": { "description": "Creator of model.", "type": "string", "maxLength": 1024 }, "model_artifact": { "description": "Location of the model artifact.", "type": "array", "maxContains": 15, "items": { "type": "string", "maxLength": 1024 } } } }, "intended_uses": { "description": "Intended usage of model.", "type": "object", "additionalProperties": false, "properties": { "purpose_of_model": { "description": "Reason the model was developed.", "type": "string", "maxLength": 2048 }, "intended_uses": { "description": "Intended use cases.", "type": "string", "maxLength": 2048 }, "factors_affecting_model_efficiency": { "type": "string", "maxLength": 2048 }, "risk_rating": { "description": "Risk rating for model card.", "$ref": "#/definitions/risk_rating" }, "explanations_for_risk_rating": { "type": "string", "maxLength": 2048 } } }, "business_details": { "description": "Business details of model.", "type": "object", "additionalProperties": false, "properties": { "business_problem": { "description": "Business problem solved by the model.", "type": "string", "maxLength": 2048 }, "business_stakeholders": { "description": "Business stakeholders.", "type": "string", "maxLength": 2048 }, "line_of_business": { "type": "string", "maxLength": 2048 } } }, "training_details": { "description": "Overview about the training.", "type": "object", "additionalProperties": false, "properties": { "objective_function": { "description": "The objective function for which the model is optimized.", "function": { "$ref": "#/definitions/objective_function" }, "notes": { "type": "string", "maxLength": 1024 } }, "training_observations": { "type": "string", "maxLength": 1024 }, "training_job_details": { "type": "object", "additionalProperties": false, "properties": { "training_arn": { "description": "SageMaker Training job ARN.", "type": "string", "maxLength": 1024 }, "training_datasets": { "description": "Location of the model datasets.", "type": "array", "maxContains": 15, "items": { "type": "string", "maxLength": 1024 } }, "training_environment": { "type": "object", "additionalProperties": false, "properties": { "container_image": { "description": "SageMaker training image URI.", "type": "array", "maxContains": 15, "items": { "type": "string", "maxLength": 1024 } } } }, "training_metrics": { "type": "array", "items": { "maxItems": 50, "$ref": "#/definitions/training_metric" } }, "user_provided_training_metrics": { "type": "array", "items": { "maxItems": 50, "$ref": "#/definitions/training_metric" } }, "hyper_parameters": { "type": "array", "items": { "maxItems": 100, "$ref": "#/definitions/training_hyper_parameter" } }, "user_provided_hyper_parameters": { "type": "array", "items": { "maxItems": 100, "$ref": "#/definitions/training_hyper_parameter" } } } } } }, "evaluation_details": { "type": "array", "default": [], "items": { "type": "object", "required": [ "name" ], "additionalProperties": false, "properties": { "name": { "type": "string", "pattern": ".{1,63}" }, "evaluation_observation": { "type": "string", "maxLength": 2096 }, "evaluation_job_arn": { "type": "string", "maxLength": 256 }, "datasets": { "type": "array", "items": { "type": "string", "maxLength": 1024 }, "maxItems": 10 }, "metadata": { "description": "Additional attributes associated with the evaluation results.", "type": "object", "additionalProperties": { "type": "string", "maxLength": 1024 } }, "metric_groups": { "type": "array", "default": [], "items": { "type": "object", "required": [ "name", "metric_data" ], "properties": { "name": { "type": "string", "pattern": ".{1,63}" }, "metric_data": { "type": "array", "items": { "anyOf": [ { "$ref": "#/definitions/simple_metric" }, { "$ref": "#/definitions/linear_graph_metric" }, { "$ref": "#/definitions/bar_chart_metric" }, { "$ref": "#/definitions/matrix_metric" } ] } } } } } } } }, "additional_information": { "additionalProperties": false, "type": "object", "properties": { "ethical_considerations": { "description": "Ethical considerations for model users.", "type": "string", "maxLength": 2048 }, "caveats_and_recommendations": { "description": "Caveats and recommendations for model users.", "type": "string", "maxLength": 2048 }, "custom_details": { "type": "object", "additionalProperties": { "$ref": "#/definitions/custom_property" } } } } }, "definitions": { "source_algorithms": { "type": "array", "minContains": 1, "maxContains": 1, "items": { "type": "object", "additionalProperties": false, "required": [ "algorithm_name" ], "properties": { "algorithm_name": { "description": "The name of the algorithm used to create the model package. The algorithm must be either an algorithm resource in your SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.", "type": "string", "maxLength": 170 }, "model_data_url": { "description": "Amazon S3 path where the model artifacts, which result from model training, are stored.", "type": "string", "maxLength": 1024 } } } }, "inference_specification": { "type": "object", "additionalProperties": false, "required": [ "containers" ], "properties": { "containers": { "description": "Contains inference related information used to create model package.", "type": "array", "minContains": 1, "maxContains": 15, "items": { "type": "object", "additionalProperties": false, "required": [ "image" ], "properties": { "model_data_url": { "description": "Amazon S3 path where the model artifacts, which result from model training, are stored.", "type": "string", "maxLength": 1024 }, "image": { "description": "Inference environment path. The Amazon Elastic Container Registry (Amazon ECR) path where inference code is stored.", "type": "string", "maxLength": 255 }, "nearest_model_name": { "description": "The name of a pre-trained machine learning benchmarked by an Amazon SageMaker Inference Recommender model that matches your model.", "type": "string" } } } } } }, "risk_rating": { "description": "Risk rating of model.", "type": "string", "enum": [ "High", "Medium", "Low", "Unknown" ] }, "custom_property": { "description": "Additional property.", "type": "string", "maxLength": 1024 }, "objective_function": { "description": "Objective function for which the training job is optimized.", "additionalProperties": false, "properties": { "function": { "type": "string", "enum": [ "Maximize", "Minimize" ] }, "facet": { "type": "string", "maxLength": 63 }, "condition": { "type": "string", "maxLength": 63 } } }, "training_metric": { "description": "Training metric data.", "type": "object", "required": [ "name", "value" ], "additionalProperties": false, "properties": { "name": { "type": "string", "pattern": ".{1,255}" }, "notes": { "type": "string", "maxLength": 1024 }, "value": { "type": "number" } } }, "training_hyper_parameter": { "description": "Training hyperparameter.", "type": "object", "required": [ "name", "value" ], "additionalProperties": false, "properties": { "name": { "type": "string", "pattern": ".{1,255}" }, "value": { "type": "string", "pattern": ".{1,255}" } } }, "linear_graph_metric": { "type": "object", "required": [ "name", "type", "value" ], "additionalProperties": false, "properties": { "name": { "type": "string", "pattern": ".{1,255}" }, "notes": { "type": "string", "maxLength": 1024 }, "type": { "type": "string", "enum": [ "linear_graph" ] }, "value": { "anyOf": [ { "type": "array", "items": { "type": "array", "items": { "type": "number" }, "minItems": 2, "maxItems": 2 }, "minItems": 1 } ] }, "x_axis_name": { "$ref": "#/definitions/axis_name_string" }, "y_axis_name": { "$ref": "#/definitions/axis_name_string" } } }, "bar_chart_metric": { "type": "object", "required": [ "name", "type", "value" ], "additionalProperties": false, "properties": { "name": { "type": "string", "pattern": ".{1,255}" }, "notes": { "type": "string", "maxLength": 1024 }, "type": { "type": "string", "enum": [ "bar_chart" ] }, "value": { "anyOf": [ { "type": "array", "items": { "type": "number" }, "minItems": 1 } ] }, "x_axis_name": { "$ref": "#/definitions/axis_name_array" }, "y_axis_name": { "$ref": "#/definitions/axis_name_string" } } }, "matrix_metric": { "type": "object", "required": [ "name", "type", "value" ], "additionalProperties": false, "properties": { "name": { "type": "string", "pattern": ".{1,255}" }, "notes": { "type": "string", "maxLength": 1024 }, "type": { "type": "string", "enum": [ "matrix" ] }, "value": { "anyOf": [ { "type": "array", "items": { "type": "array", "items": { "type": "number" }, "minItems": 1, "maxItems": 20 }, "minItems": 1, "maxItems": 20 } ] }, "x_axis_name": { "$ref": "#/definitions/axis_name_array" }, "y_axis_name": { "$ref": "#/definitions/axis_name_array" } } }, "simple_metric": { "description": "Metric data.", "type": "object", "required": [ "name", "type", "value" ], "additionalProperties": false, "properties": { "name": { "type": "string", "pattern": ".{1,255}" }, "notes": { "type": "string", "maxLength": 1024 }, "type": { "type": "string", "enum": [ "number", "string", "boolean" ] }, "value": { "anyOf": [ { "type": "number" }, { "type": "string", "maxLength": 63 }, { "type": "boolean" } ] }, "x_axis_name": { "$ref": "#/definitions/axis_name_string" }, "y_axis_name": { "$ref": "#/definitions/axis_name_string" } } }, "axis_name_array": { "type": "array", "items": { "type": "string", "maxLength": 63 } }, "axis_name_string": { "type": "string", "maxLength": 63 } } }
檢視和更新模型版本的詳細資訊 （Studio 或 Studio Classic）
若要檢視和更新模型版本的詳細資訊，請根據您是否使用 Studio 或 Studio Classic 完成下列步驟。在 Studio Classic 中，您可以更新模型版本的核准狀態。如需詳細資訊，請參閱 更新模型的核准狀態。另一方面，在 Studio 中為模型套件 SageMaker 建立模型卡，而模型版本 UI 提供更新模型卡中詳細資訊的選項。
