[BUG] - Broken Links In `tutorials/intermediate_source /fx_conv_bn_fuser.py`

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Introduction

In this article, we will be discussing a broken link in the PyTorch tutorials repository. The link in question is located in the tutorials/intermediate_source /fx_conv_bn_fuser.py file and is causing issues for users who are trying to access the correct webpage. We will be providing information on how to reproduce the bug, the environment in which it was encountered, and potential solutions to resolve the issue.

The Bug

The broken link is located at the following URL: https://github.com/pytorch/tutorials/blob/155f386a1fc656f607f1ef83d019077c85d7c03b/intermediate_source/fx_conv_bn_fuser.py#L201

When trying to access this link, users are met with an error message indicating that the URL is not valid. This is a significant issue for users who are trying to learn from the PyTorch tutorials and rely on the accuracy of the information provided.

Reproducing the Bug

To reproduce the bug, users can follow these steps:

  1. Clone the PyTorch tutorials repository using the following command: git clone https://github.com/pytorch/tutorials.git
  2. Navigate to the intermediate_source directory within the repository: cd tutorials/intermediate_source
  3. Open the fx_conv_bn_fuser.py file in a text editor or IDE: nano fx_conv_bn_fuser.py
  4. Locate line 201 of the file and try to access the link: https://github.com/pytorch/tutorials/blob/155f386a1fc656f607f1ef83d019077c85d7c03b/intermediate_source/fx_conv_bn_fuser.py#L201

Environment

The bug was encountered in the following environment:

  • PyTorch version: 2.6.0+cu124
  • Is debug build: False
  • CUDA used to build PyTorch: 12.4
  • ROCM used to build PyTorch: N/A
  • OS: Ubuntu 22.04.3 LTS (x86_64)
  • GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
  • Clang version: Could not collect
  • CMake version: version 3.22.1
  • Libc version: glibc-2.35
  • Python version: 3.10.12 (main, Feb 4 2025, 14:57:36) [GCC 11.4.0] (64-bit runtime)
  • Python platform: Linux-5.15.133.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
  • Is CUDA available: True
  • CUDA runtime version: Could not collect
  • CUDA_MODULE_LOADING set to: LAZY
  • GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3050 4GB Laptop GPU
  • Nvidia driver version: 565.90
  • cuDNN version: Could not collect
  • HIP runtime version: N/A
  • MIOpen runtime version: N/A
  • Is XNNPACK available: True

Versions of Relevant Libraries

The following versions of relevant libraries were used:

  • [pip3] lightning==2.5.0.post0
  • [pip3] lightning-utilities==0.11.7
  • [pip3] mypy-extensions==1.0.0
  • [pip3] numpy==1.26.4
  • [pip3] onnx==1.16.2
  • [pip3] onnx_graphsurgeon==0.5.6
  • [pip3] onnxconverter-common==1.14.0
  • [pip3] onnxmltools==1.13.0
  • [pip3] onnxruntime==1.21.0
  • [pip3] onnxruntime-gpu==1.20.2
  • [pip3] onnxruntime-training==1.19.2
  • [pip3] onnxscript==0.2.2
  • [pip3] pytorch-lightning==2.4.0
  • [pip3] torch==2.6.0
  • [pip3] torch_tensorrt==2.6.0
  • [pip3] torchao==0.5.0
  • [pip3] torchaudio==2.2.1+cu121
  • [pip3] torchmetrics==1.6.2
  • [pip3] torchprofile==0.0.4
  • [pip3] torchvision==0.21.0
  • [pip3] triton==3.2.0
  • [conda] Could not collect

Potential Solutions

There are several potential solutions to resolve the issue:

  1. Update the PyTorch tutorials repository: The first step is to update the PyTorch tutorials repository to the latest version. This can be done by running the following command: git pull origin master
  2. Check the link: The link in question may be outdated or incorrect. It is possible that the link has been changed or removed. In this case, the user can try to find the correct link or contact the PyTorch team for assistance.
  3. Use a different version of PyTorch: If the issue is specific to a particular version of PyTorch, the user can try using a different version of PyTorch. This can be done by installing a different version of PyTorch using pip: pip install torch==2.7.0
  4. Contact the PyTorch team: If none of the above solutions work, the user can contact the PyTorch team for assistance. They can provide more information about the issue and the team can help to resolve it.

Conclusion

In conclusion, the broken link in the PyTorch tutorials repository is a significant issue that needs to be resolved. The user can try updating the repository, checking the link, using a different version of PyTorch, or contacting the PyTorch team for assistance. By following these steps, the user can resolve the issue and continue to learn from the PyTorch tutorials.

Introduction

In our previous article, we discussed a broken link in the PyTorch tutorials repository. The link in question is located in the tutorials/intermediate_source /fx_conv_bn_fuser.py file and is causing issues for users who are trying to access the correct webpage. In this article, we will be providing a Q&A section to help users understand the issue and potential solutions.

Q&A

Q: What is the broken link in the PyTorch tutorials repository?

A: The broken link is located at the following URL: https://github.com/pytorch/tutorials/blob/155f386a1fc656f607f1ef83d019077c85d7c03b/intermediate_source/fx_conv_bn_fuser.py#L201

Q: What is the issue with the link?

A: The link is not valid and is causing an error message when users try to access it.

Q: How can I reproduce the bug?

A: To reproduce the bug, users can follow these steps:

  1. Clone the PyTorch tutorials repository using the following command: git clone https://github.com/pytorch/tutorials.git
  2. Navigate to the intermediate_source directory within the repository: cd tutorials/intermediate_source
  3. Open the fx_conv_bn_fuser.py file in a text editor or IDE: nano fx_conv_bn_fuser.py
  4. Locate line 201 of the file and try to access the link: https://github.com/pytorch/tutorials/blob/155f386a1fc656f607f1ef83d019077c85d7c03b/intermediate_source/fx_conv_bn_fuser.py#L201

Q: What are the potential solutions to resolve the issue?

A: There are several potential solutions to resolve the issue:

  1. Update the PyTorch tutorials repository: The first step is to update the PyTorch tutorials repository to the latest version. This can be done by running the following command: git pull origin master
  2. Check the link: The link in question may be outdated or incorrect. It is possible that the link has been changed or removed. In this case, the user can try to find the correct link or contact the PyTorch team for assistance.
  3. Use a different version of PyTorch: If the issue is specific to a particular version of PyTorch, the user can try using a different version of PyTorch. This can be done by installing a different version of PyTorch using pip: pip install torch==2.7.0
  4. Contact the PyTorch team: If none of the above solutions work, the user can contact the PyTorch team for assistance. They can provide more information about the issue and the team can help to resolve it.

Q: How can I prevent this issue in the future?

A: To prevent this issue in the future, users can:

  1. Regularly update the PyTorch tutorials repository: By regularly updating the repository, users can ensure that they have the latest version of the code and avoid issues with outdated links.
  2. Verify links before accessing them: Before accessing a link, users can verify that it is valid and up-to-date.
  3. Use a version control system: By using a version control system such as Git, users can track changes to the code and avoid issues with outdated links.

Q: What is the best way to contact the PyTorch team for assistance?

A: The best way to contact the PyTorch team for assistance is to:

  1. Check the PyTorch documentation: The PyTorch documentation provides a wealth of information on how to use the library and troubleshoot common issues.
  2. Search online forums: Online forums such as Reddit and Stack Overflow often have active communities of users who can provide assistance and guidance.
  3. Contact the PyTorch team directly: If none of the above options work, users can contact the PyTorch team directly through their website or email.

Conclusion

In conclusion, the broken link in the PyTorch tutorials repository is a significant issue that needs to be resolved. By following the steps outlined in this article, users can reproduce the bug, understand the potential solutions, and prevent this issue in the future. If users are still experiencing issues, they can contact the PyTorch team for assistance.