Adds clip_grad_norm to all recipe config that supports it

[thomasjpfan]

Context

What is the purpose of this PR? Is it to

• [ ] add a new feature
• [ ] fix a bug
• [ ] update tests and/or documentation
• [x] other (Updates config)

Fixes https://github.com/pytorch/torchtune/issues/1993

I ran the following script to find the recipes the support clip_grad_norm and update the yaml files.

from torchtune._recipe_registry import get_all_recipes
import torchtune
import os
from pathlib import Path

recipes = get_all_recipes()
recipes_dir = Path(torchtune.__path__[0]).parent / "recipes"
config_dir = recipes_dir / "configs"

support_clip_grads = [
    recipe
    for recipe in recipes
    if "clip_grad_norm" in (recipes_dir / recipe.file_path).read_text()
]

for recipe in recipes:
    for config in recipe.configs:
        if config.file_path.startswith("dev"):
            yaml_config = recipes_dir / config.file_path
        else:
            yaml_config = config_dir / config.file_path

        assert yaml_config.exists(), yaml_config

        yaml_text = yaml_config.read_text()

        if "loss" not in yaml_text:
            continue

        if "clip_grad_norm" in yaml_text:
            continue

        assert "compile" in yaml_text

        text = yaml_text.split(os.linesep)

        compile_idx = None
        for idx, line in enumerate(text):
            if line.startswith("compile"):
                compile_idx = idx
                break
        assert compile_idx is not None

        text.insert(compile_idx, "clip_grad_norm: null")

        result = os.linesep.join(text)
        with yaml_config.open("w") as f:
            f.write(result)

Changelog

What are the changes made in this PR?

• Adds clip_grad_norm to all recipes that support it.

Test plan

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• [ ] add unit tests for any new functionality
• [ ] update docstrings for any new or updated methods or classes
• [ ] run unit tests via pytest tests
• [ ] run recipe tests via pytest tests -m integration_test
• [ ] manually run any new or modified recipes with sufficient proof of correctness
• [ ] include relevant commands and any other artifacts in this summary (pastes of loss curves, eval results, etc.)

UX

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• [x] I did not change any public API
• [ ] I have added an example to docs or docstrings

[pytorch-bot[bot]]

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[ebsmothers]

Maybe I am missing something but I don't see gradient clipping support in DPO, PPO, or distributed KD recipes. Can we remove the clip_grad_norm fields from those configs? (Separately we should probably enable for KD at the very least but can likely do that separately)

[thomasjpfan]

@ebsmothers Thanks for catching this! There was a bug in my script for finding the recipes that support gradient clipping. I updated this PR to fix the issue.