After I do a change in a .py code or Python virtual environment package that the notebook uses, they are not reflected in the notebook and need to close the VSCode and open it again to have them reflected #8767
Labels
bug
Issue identified by VS Code Team member as probable bug
So, whenever I change my ViT.py code or install a new package in my Python Virtual Environment, those changes are not picked up by the Jupyter notebook that I am running inside the VSCode. The only way that I am currently able to get them reflected is to close VSCode and open it again which is quite a lot of overhead given I am using SSH to connect to local machine. Is there a way to make these changes seamless ideally?
For example, in the image above, you see even after installing the Python package that is requested, it is still not recognized.
Environment data
VS Code version: XXX
![Screen Shot 2022-01-21 at 7 05 03 PM](https://user-images.githubusercontent.com/1892917/150615254-a4ce113a-345b-4c27-a914-38ce3586ff7a.png)
Jupyter Extension version (available under the Extensions sidebar): XXX
![Screen Shot 2022-01-21 at 7 05 46 PM](https://user-images.githubusercontent.com/1892917/150615298-873781f7-d50d-4f6e-94f7-7e073eb7b2e1.png)
Python Extension version (available under the Extensions sidebar): XXX
![Screen Shot 2022-01-21 at 7 06 22 PM](https://user-images.githubusercontent.com/1892917/150615335-6cc17470-4710-4fee-a60e-8064ff3cf79e.png)
OS (Windows | Mac | Linux distro) and version: XXX
![Screen Shot 2022-01-21 at 7 06 50 PM](https://user-images.githubusercontent.com/1892917/150615364-586ffc8e-13fe-4d60-a8b0-cc95a2592fd1.png)
Local:
remote:
Native Python virtual environment on remote machine (name of virt env: dpcc)
Remote
Expected behaviour
After I closed and opened the VScode (and reconnect to remote host), this is what the expected behavior should be (progress bar for training):
This is regarding cell #25 here https://github.com/lucidrains/vit-pytorch/blob/main/examples/cats_and_dogs.ipynb
Actual behaviour
XXX
Steps to reproduce:
[NOTE: Self-contained, minimal reproducing code samples are extremely helpful and will expedite addressing your issue]
Logs
Output for
Jupyter
in theOutput
panel (View
→Output
, change the drop-down the upper-right of theOutput
panel toJupyter
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