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AJV-7655 avatar image
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AJV-7655 asked ramr-msft answered

"PermissionError: [Errno 13] Permission denied" when trying to access a local file for a conda environment

After Azure ML Studio blocking me from using any compute due to an as-of-yet unresolved authentication error, I moved to using a Jupyter Notebook on my local workstation to try to configure my experiments locally then send the job to an Azure compute cluster. I have two lines of Python that tries to create an environment class by accessing a .yml file on my local computer:

yml_path = r"C:\Users\me\Desktop\azure_training\training_env"
pytorch_env = Environment.from_conda_specification(name='pytorch-1.11-gpu', file_path=yml_path)

This causes the following error:

PermissionError: [Errno 13] Permission denied: 'C:\\Users\\me\\Desktop\\azure_training\\training_env'

I am unsure of what is causing this. When the file doesn't need to be private, I have solved permission denied issues in the past that resulted from locally run tools such as PostgreSQL by going to the file's properties>>security and adding the user "Everyone" with full control. I tried doing that in this case, but it had no impact. I still get permission denied even though "Everyone" has full control over the file.

azure-machine-learning
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1 Answer

ramr-msft avatar image
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ramr-msft answered

@AJV-7655 Thanks for the question. if you don't want to "bake" your personal access token (essentially a password) into your Conda environment file, is to follow Use private Python packages - Azure Machine Learning | Microsoft Docs and connect the authenticated feed with your workspace.


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