Azure Machine Learning for Visual Studio Code, previously called Visual Studio Code Tools for AI, is an extension to easily build, train, and deploy machine learning models to the cloud or the edge with Azure Machine Learning service.
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Launching VS Code from AML puts users in an unexpected directory/path #1462
Launching edit in VS Code from AzureML, I expect to find myself in the same directory/path that I'm in when in AzureML.
Actual Behavior
Currently, launching in VS Code puts you two directories above where you are in AzureML. This is confusing for users. It also doesn't appear to be consistent with launching Jupyter/Jupyterlab from AML.
Steps to Reproduce the Problem
In an Azure Machine Learning workspace, with compute instance running
Navigate to Notebooks
Launch a terminal in AML, and note current working directory
In the global toolbars, click "Edit in VS Code"
Once in VS Code, launch terminal and notice working directory (2 directories above where you expect to be)
For comparison, launch Jupyter and Jupyterlab, and notice working directory
Expected Behavior
Launching edit in VS Code from AzureML, I expect to find myself in the same directory/path that I'm in when in AzureML.
Actual Behavior
Currently, launching in VS Code puts you two directories above where you are in AzureML. This is confusing for users. It also doesn't appear to be consistent with launching Jupyter/Jupyterlab from AML.
Steps to Reproduce the Problem
In an Azure Machine Learning workspace, with compute instance running
Navigate to Notebooks
Launch a terminal in AML, and note current working directory
In the global toolbars, click "Edit in VS Code"
Once in VS Code, launch terminal and notice working directory (2 directories above where you expect to be)
For comparison, launch Jupyter and Jupyterlab, and notice working directory
Specifications