标签: yandexcloud

我正在使用 mlflow 来注册我的模型。当工件从本地加载到 S3 存储桶时，我尝试使用“场景 4”。

1. 将 S3 存储桶的凭证添加到 .aws/credentials

2. 设置端点和 mlflow URI：

   os.environ["MLFLOW_S3_ENDPOINT_URL"]='https://storage.yandexcloud.net' os.environ["MLFLOW_TRACKING_URI"]='http://:8000'

3. 通过 mlflow 将模型记录到 S3：

   导入mlflow导入mlflow.sklearn mlflow.set_experiment（“我的”）... mlflow.sklearn.log_model（模型，artifact_path =“models_mlflow”）

但得到错误：

MlflowException: API request to http://<IP>:8000/api/2.0/mlflow-artifacts/artifacts/6/95972bcc493c4a8cbd8432fea4cc8bac/artifacts/models_mlflow/model.pkl failed with exception HTTPConnectionPool(host='62.84.121.234', port=8000): Max retries exceeded with url: /api/2.0/mlflow-artifacts/artifacts/6/95972bcc493c4a8cbd8432fea4cc8bac/artifacts/models_mlflow/model.pkl (Caused by ResponseError('too many 503 error responses'))

有来自 yandex 云的 s3 https://cloud.yandex.com/docs/storage/tools/?utm_source=console&utm_medium=empty-page&utm_campaign=storage

我如何配置 django 来使用它？