python - Azure ML：将文件上传到 Step Run 的输出 - 身份验证错误
问题描述
在 Azure ML 管道中的 PythonScriptStep 期间，我将模型作为 joblib pickle 转储保存到 Azure Blob 存储中的 Blob 容器中的目录，该目录是我在设置 Azure ML 工作区期间创建的。之后，我尝试使用将此模型文件上传到步骤运行的输出目录
Run.upload_file (name, path_or_stream)
前段时间，当我使用 azureml-sdk 版本 1.18.0 创建脚本时，一切正常。现在，我已经更新了脚本的功能，并在此过程中将 azureml-sdk 升级到了 1.33.0 版本，上传功能现在遇到以下错误：
Traceback (most recent call last):
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_file_utils/upload.py", line 64, in upload_blob_from_stream
validate_content=True)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/clientbase.py", line 93, in execute_func_with_reset
return ClientBase._execute_func_internal(backoff, retries, module_logger, func, reset_func, *args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/clientbase.py", line 367, in _execute_func_internal
left_retry = cls._handle_retry(back_off, left_retry, total_retry, error, logger, func)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/clientbase.py", line 399, in _handle_retry
raise error
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/clientbase.py", line 358, in _execute_func_internal
response = func(*args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/blob/blockblobservice.py", line 614, in create_blob_from_stream
initialization_vector=iv
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/blob/_upload_chunking.py", line 98, in _upload_blob_chunks
range_ids = [f.result() for f in futures]
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/blob/_upload_chunking.py", line 98, in <listcomp>
range_ids = [f.result() for f in futures]
File "/opt/miniconda/lib/python3.7/concurrent/futures/_base.py", line 435, in result
return self.__get_result()
File "/opt/miniconda/lib/python3.7/concurrent/futures/_base.py", line 384, in __get_result
raise self._exception
File "/opt/miniconda/lib/python3.7/concurrent/futures/thread.py", line 57, in run
result = self.fn(*self.args, **self.kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/blob/_upload_chunking.py", line 210, in process_chunk
return self._upload_chunk_with_progress(chunk_offset, chunk_bytes)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/blob/_upload_chunking.py", line 224, in _upload_chunk_with_progress
range_id = self._upload_chunk(chunk_offset, chunk_data)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/blob/_upload_chunking.py", line 269, in _upload_chunk
timeout=self.timeout,
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/blob/blockblobservice.py", line 1013, in _put_block
self._perform_request(request)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/common/storageclient.py", line 432, in _perform_request
raise ex
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/common/storageclient.py", line 357, in _perform_request
raise ex
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/common/storageclient.py", line 343, in _perform_request
HTTPError(response.status, response.message, response.headers, response.body))
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_vendor/azure_storage/common/_error.py", line 115, in _http_error_handler
raise ex
azure.common.AzureHttpError: Server failed to authenticate the request. Make sure the value of Authorization header is formed correctly including the signature. ErrorCode: AuthenticationFailed
<?xml version="1.0" encoding="utf-8"?><Error><Code>AuthenticationFailed</Code><Message>Server failed to authenticate the request. Make sure the value of Authorization header is formed correctly including the signature.
RequestId:5d4e1b7e-c01e-0070-0d47-9bf8a0000000
Time:2021-08-27T13:30:02.2685991Z</Message><AuthenticationErrorDetail>Signature did not match. String to sign used was rcw
2021-08-27T13:19:56Z
2021-08-28T13:29:56Z
/blob/mystorage/azureml/ExperimentRun/dcid.98d11a7b-2aac-4bc0-bd64-bb4d72e0e0be/outputs/models/Model.pkl
2019-07-07
b
</AuthenticationErrorDetail></Error>
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/mnt/batch/tasks/shared/LS_root/jobs/.../azureml-setup/context_manager_injector.py", line 243, in execute_with_context
runpy.run_path(sys.argv[0], globals(), run_name="__main__")
File "/opt/miniconda/lib/python3.7/runpy.py", line 263, in run_path
pkg_name=pkg_name, script_name=fname)
File "/opt/miniconda/lib/python3.7/runpy.py", line 96, in _run_module_code
mod_name, mod_spec, pkg_name, script_name)
File "/opt/miniconda/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "401_AML_Pipeline_Time_Series_Model_Training_Azure_ML_CPU.py", line 318, in <module>
main()
File "401_AML_Pipeline_Time_Series_Model_Training_Azure_ML_CPU.py", line 286, in main
path_or_stream=model_path)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/core/run.py", line 53, in wrapped
return func(self, *args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/core/run.py", line 1989, in upload_file
datastore_name=datastore_name)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 114, in upload_artifact
return self.upload_artifact_from_path(artifact, *args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 107, in upload_artifact_from_path
return self.upload_artifact_from_stream(stream, *args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 99, in upload_artifact_from_stream
content_type=content_type, session=session)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 88, in upload_stream_to_existing_artifact
timeout=TIMEOUT, backoff=BACKOFF_START, retries=RETRY_LIMIT)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_file_utils/upload.py", line 71, in upload_blob_from_stream
raise AzureMLException._with_error(azureml_error, inner_exception=e)
azureml._common.exceptions.AzureMLException: AzureMLException:
Message: Encountered authorization error while uploading to blob storage. Please check the storage account attached to your workspace. Make sure that the current user is authorized to access the storage account and that the request is not blocked by a firewall, virtual network, or other security setting.
StorageAccount: mystorage
ContainerName: azureml
StatusCode: 403
InnerException Server failed to authenticate the request. Make sure the value of Authorization header is formed correctly including the signature. ErrorCode: AuthenticationFailed
<?xml version="1.0" encoding="utf-8"?><Error><Code>AuthenticationFailed</Code><Message>Server failed to authenticate the request. Make sure the value of Authorization header is formed correctly including the signature.
RequestId:5d4e1b7e-c01e-0070-0d47-9bf8a0000000
Time:2021-08-27T13:30:02.2685991Z</Message><AuthenticationErrorDetail>Signature did not match. String to sign used was rcw
2021-08-27T13:19:56Z
2021-08-28T13:29:56Z
/blob/mystorage/azureml/ExperimentRun/dcid.98d11a7b-2aac-4bc0-bd64-bb4d72e0e0be/outputs/models/Model.pkl
2019-07-07
b
</AuthenticationErrorDetail></Error>
ErrorResponse
{
"error": {
"code": "UserError",
"message": "Encountered authorization error while uploading to blob storage. Please check the storage account attached to your workspace. Make sure that the current user is authorized to access the storage account and that the request is not blocked by a firewall, virtual network, or other security setting.\n\tStorageAccount: mystorage\n\tContainerName: azureml\n\tStatusCode: 403",
"inner_error": {
"code": "Auth",
"inner_error": {
"code": "Authorization"
}
}
}
}
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "401_AML_Pipeline_Time_Series_Model_Training_Azure_ML_CPU.py", line 318, in <module>
main()
File "401_AML_Pipeline_Time_Series_Model_Training_Azure_ML_CPU.py", line 286, in main
path_or_stream=model_path)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/core/run.py", line 53, in wrapped
return func(self, *args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/core/run.py", line 1989, in upload_file
datastore_name=datastore_name)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 114, in upload_artifact
return self.upload_artifact_from_path(artifact, *args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 107, in upload_artifact_from_path
return self.upload_artifact_from_stream(stream, *args, **kwargs)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 99, in upload_artifact_from_stream
content_type=content_type, session=session)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_restclient/artifacts_client.py", line 88, in upload_stream_to_existing_artifact
timeout=TIMEOUT, backoff=BACKOFF_START, retries=RETRY_LIMIT)
File "/opt/miniconda/lib/python3.7/site-packages/azureml/_file_utils/upload.py", line 71, in upload_blob_from_stream
raise AzureMLException._with_error(azureml_error, inner_exception=e)
UserScriptException: UserScriptException:
Message: Encountered authorization error while uploading to blob storage. Please check the storage account attached to your workspace. Make sure that the current user is authorized to access the storage account and that the request is not blocked by a firewall, virtual network, or other security setting.
StorageAccount: mystorage
ContainerName: azureml
StatusCode: 403
InnerException AzureMLException:
Message: Encountered authorization error while uploading to blob storage. Please check the storage account attached to your workspace. Make sure that the current user is authorized to access the storage account and that the request is not blocked by a firewall, virtual network, or other security setting.
StorageAccount: mystorage
ContainerName: azureml
StatusCode: 403
InnerException Server failed to authenticate the request. Make sure the value of Authorization header is formed correctly including the signature. ErrorCode: AuthenticationFailed
<?xml version="1.0" encoding="utf-8"?><Error><Code>AuthenticationFailed</Code><Message>Server failed to authenticate the request. Make sure the value of Authorization header is formed correctly including the signature.
RequestId:5d4e1b7e-c01e-0070-0d47-9bf8a0000000
Time:2021-08-27T13:30:02.2685991Z</Message><AuthenticationErrorDetail>Signature did not match. String to sign used was rcw
2021-08-27T13:19:56Z
2021-08-28T13:29:56Z
/blob/mystorage/azureml/ExperimentRun/dcid.98d11a7b-2aac-4bc0-bd64-bb4d72e0e0be/outputs/models/Model.pkl
2019-07-07
b
</AuthenticationErrorDetail></Error>
ErrorResponse
{
"error": {
"code": "UserError",
"message": "Encountered authorization error while uploading to blob storage. Please check the storage account attached to your workspace. Make sure that the current user is authorized to access the storage account and that the request is not blocked by a firewall, virtual network, or other security setting.\n\tStorageAccount: verovisionstorage\n\tContainerName: azureml\n\tStatusCode: 403",
"inner_error": {
"code": "Auth",
"inner_error": {
"code": "Authorization"
}
}
}
}
ErrorResponse
{
"error": {
"code": "UserError",
"message": "Encountered authorization error while uploading to blob storage. Please check the storage account attached to your workspace. Make sure that the current user is authorized to access the storage account and that the request is not blocked by a firewall, virtual network, or other security setting.\n\tStorageAccount: mystorage\n\tContainerName: azureml\n\tStatusCode: 403"
}
}
据我从 azureml.core.Run 类的代码和随后的函数调用中可以看出，Run 对象尝试使用 SAS-Token-Authentication 将文件上传到步骤运行的输出目录（失败）。此文档文章在代码中链接（但我不知道这是否与问题有关）：https ://docs.microsoft.com/en-us/rest/api/storageservices/create-service-sas#service -sas-示例
有没有人也遇到过这个错误并且知道是什么原因造成的或者如何解决？
最好的，乔纳斯
解决方案
我们以前看过，很烦人。我认为答案是转到 AML Studio UI 的数据存储页面并再次手动输入存储帐户密钥。