switch triton kernels hash to v3.5.1 for gpt oss notebooks

[mmathew23]

update triton kernels in notebooks to match triton 3.5

[gemini-code-assist]

Summary of Changes

Hello @mmathew23, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on updating the Triton kernel dependency across several GPT OSS notebooks and their corresponding Python scripts. The primary goal is to ensure that these resources are compatible with Triton version 3.5 by referencing a newer, appropriate commit hash for the Triton kernels repository. This update is crucial for maintaining the functionality and performance of the machine learning workflows defined in these files.

Highlights

• Triton Kernel Version Update: The git commit hash for the Triton kernels dependency has been updated across all affected notebooks and Python scripts to ensure compatibility with Triton version 3.5.
• Dependency Alignment: This change aligns the Triton kernel version used in the GPT OSS notebooks and scripts with the specified Triton 3.5 version requirement.

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[gemini-code-assist]

Code Review

This pull request updates the Triton kernel's commit hash across a large number of notebooks and scripts. The change itself is a straightforward dependency update. However, the fact that this change needs to be applied to dozens of files indicates a code duplication and maintainability issue. All these files contain a hardcoded installation command. I've left a comment on update_all_notebooks.py, which seems to be the script used for these updates, suggesting a way to centralize the dependency string to make future updates easier. A better long-term solution would be to manage dependencies in a shared requirements file.

[gemini-code-assist]

This pull request highlights a maintainability issue: the Triton commit hash is hardcoded in many files. While this script helps automate the update, the hash is still hardcoded within this script's multiline string. To make future updates easier and less error-prone, consider defining the Triton dependency string as a constant at the top of this file and referencing it here.

For example:

# At the top of the file
TRITON_COMMIT_HASH = "0add68262ab0a2e33b84524346cb27cbb2787356"
TRITON_PIP_URL = f"git+https://github.com/triton-lang/triton.git@{TRITON_COMMIT_HASH}#subdirectory=python/triton_kernels"

# ... then in the pip_install_block string, you can use an f-string and reference it:
pip_install_block = f"""...\
        {TRITON_PIP_URL}
..."""

A more robust long-term solution would be to have all notebooks install dependencies from a central requirements.txt file.