文件 AWS 開發套件範例 GitHub 儲存庫中有更多可用的 AWS SDK 範例
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。
DescribeModel
搭配 AWS SDK 使用
下列程式碼範例示範如何使用 DescribeModel
。
如需詳細資訊,請參閱檢視模型。
- Python
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- SDK for Python (Boto3)
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注意
GitHub 上提供更多範例。尋找完整範例,並了解如何在 AWS 程式碼範例儲存庫
中設定和執行。 class Models: @staticmethod def describe_model(lookoutvision_client, project_name, model_version): """ Shows the performance metrics for a trained model. :param lookoutvision_client: A Boto3 Amazon Lookout for Vision client. :param project_name: The name of the project that contains the desired model. :param model_version: The version of the model. """ response = lookoutvision_client.describe_model( ProjectName=project_name, ModelVersion=model_version ) model_description = response["ModelDescription"] print(f"\tModel version: {model_description['ModelVersion']}") print(f"\tARN: {model_description['ModelArn']}") if "Description" in model_description: print(f"\tDescription: {model_description['Description']}") print(f"\tStatus: {model_description['Status']}") print(f"\tMessage: {model_description['StatusMessage']}") print(f"\tCreated: {str(model_description['CreationTimestamp'])}") if model_description["Status"] in ("TRAINED", "HOSTED"): training_start = model_description["CreationTimestamp"] training_end = model_description["EvaluationEndTimestamp"] duration = training_end - training_start print(f"\tTraining duration: {duration}") print("\n\tPerformance metrics\n\t-------------------") print(f"\tRecall: {model_description['Performance']['Recall']}") print(f"\tPrecision: {model_description['Performance']['Precision']}") print(f"\tF1: {model_description['Performance']['F1Score']}") training_output_bucket = model_description["OutputConfig"]["S3Location"][ "Bucket" ] prefix = model_description["OutputConfig"]["S3Location"]["Prefix"] print(f"\tTraining output: s3://{training_output_bucket}/{prefix}")
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如需 API 詳細資訊,請參閱 SDK AWS for Python (Boto3) API 參考中的 DescribeModel。
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DescribeDataset
DetectAnomalies