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@albanD, could you please approve the workflow run for this draft PR?

The current commit intentionally contains only the new Lintrunner check. The job is expected to fail with 14 diagnostics across the 10 tutorials documented in #3946, which will validate that the check detects the existing issues.

Once that run is recorded, I’ll push a second commit fixing those violations. This will preserve both the detection run and the final passing run in the PR history. Thank you!

Hey @albanD, bumping this up!

Sorry, I don't really have a lot of time to review things here. What is this one about?

14 Colabs created from the tutorials have indentation problems, adding a Lintrunner check for that.

Why is it not fixing these notebooks?

I don't just want to fix these issues. But I also want to add a check that stops these issues from occurring in any new tutorials as well.

If we run the workflow now, the workflow job fails with 14 diagnostics across the 10 tutorials documented in #3946, which will validate that the Lintrunner detects the existing issues, and there is value in having the Lintrunner check being added to this repo.

After that I'll push a second commit to this PR fixing these issues, the lintrunner will pass then. This will preserve both the detection run and the final passing run in the PR history.

1. USB Semi-Supervised Learning

Tutorial: https://docs.pytorch.org/tutorials/advanced/usb_semisup_learn.html

Fixed content: the list of functions imported from semilearn in the Use USB to Train FreeMatch/SoftMatch on CIFAR-10 with only 40 labels section.

Colab - https://colab.research.google.com/drive/1pLl7Z1-vo22Z_d9wKxoBsPM6zv9pnpZz?usp=sharing

2. Automatic Differentiation with torch.autograd

Tutorial: https://docs.pytorch.org/tutorials/beginner/basics/autogradqs_tutorial.html

Fixed content:

• the list in the note explaining gradient availability; and
• the list of reasons for disabling gradient tracking.

Colab - https://colab.research.google.com/drive/106DTdB7xXC7ICHb4kv4cvY9GvPFooH3n?usp=sharing

3. Datasets & DataLoaders

Tutorial: https://docs.pytorch.org/tutorials/beginner/basics/data_tutorial.html

Fixed content: the FashionMNIST parameter list in the Loading a Dataset section.

Colab - https://colab.research.google.com/drive/1Ryu6JY2FgQJqdqwzn5UPSuqz5RoPi2mY?usp=sharing

4. Neural Networks

Tutorial: https://docs.pytorch.org/tutorials/beginner/blitz/neural_networks_tutorial.html

Fixed content: the lists under Recap, At this point, we covered, and Still Left.

Colab - https://colab.research.google.com/drive/1kOz58dE3EyV2BzFO_0bJZeh9-ZQ3S2VC?usp=sharing

5. What is torch.nn really?

Tutorial: https://docs.pytorch.org/tutorials/beginner/nn_tutorial.html

Fixed content: the list of assumptions in the Wrapping DataLoader section.

Colab - https://colab.research.google.com/drive/15YAO3JGZueMIJRPydokTHfpv8gNa0nDX?usp=sharing

6. Optimizer Step in Backward

Tutorial: https://docs.pytorch.org/tutorials/intermediate/optimizer_step_in_backward_tutorial.html

Fixed content: the numbered list following Several major observations.

Colab - https://colab.research.google.com/drive/1ZYB3KAJUllybwpv6XoYQgvi_DI1j-zDQ?usp=sharing

7. PyTorch Profiler

Tutorial: https://docs.pytorch.org/tutorials/recipes/recipes/profiler_recipe.html

Fixed content: the nested activity types under the activities profiler parameter in the Using profiler to analyze execution time section.

Colab - https://colab.research.google.com/drive/153edt0JVmGtAkl-C4_Mtbq8xFRlRwd4h?usp=sharing

8. Timer Quick Start

Tutorial: https://docs.pytorch.org/tutorials/recipes/recipes/timer_quick_start.html

Fixed content: the Contents list near the beginning of the tutorial.

Colab - https://colab.research.google.com/drive/1kjvktsPU5fUun1WURCT5nrOfCaAQ7Zdm?usp=sharing

9. Changing the Compilation Stance

Tutorial: https://docs.pytorch.org/tutorials/recipes/torch_compiler_set_stance_tutorial.html

Fixed content: the list following Other stances include.

Colab - https://colab.research.google.com/drive/1Qz2BziA-WoU5A511VkPTSfOnFKI-28zE?usp=sharing

10. GPU Direct Storage

Tutorial: https://docs.pytorch.org/tutorials/unstable/gpu_direct_storage.html

Fixed content: the list following The steps involved in the process are as follows.

Colab - https://colab.research.google.com/drive/1XZDmHG-fy7LhldeIFwIODijuT9fKRdrt?usp=sharing

Built all 10 with -

GALLERY_PATTERN='(?:^|/)(?:usb_semisup_learn|autogradqs_tutorial|data_tutorial|neural_networks_tutorial|nn_tutorial|optimizer_step_in_backward_tutorial|profiler_recipe|timer_quick_start|
  torch_compiler_set_stance_tutorial|gpu_direct_storage)\.py$' \
  sphinx-build -E -D plot_gallery=0 -b html . _build/html

@albanD the notebooks are fixed now, and the lintrunner will ensure this exact issue shouldn't re-occur.

Please run the workflows. Thanks!

Hey @albanD, bumping this up!

@albanD gentle reminder.

@albanD gentle bump!

Sorry I didn't have time to look at this.
I'm trying to find more maintainers to help here but it's hard.

No worries @albanD . Can you run the workflow? Also I can help if you want. Not sure I am eligible with just 2 hanges though.

@albanD the linkChecker was failing for 2 unrelated links, have fixed them in the last commit. Can you rerun the workflow?

@albanD gentle reminder.