## What does this PR do?
**Type of change:** Refator; Minor new feature
**Overview:** ?
1. Refactored AutoQuantizeSearcher to _AutoQuantizeBaseSearcher &
AutoQuantizeGradientSearcher - Prepares architecture for additional
search methods.
2. seperated quant modules and score modules - separate quantization
modules from scoring modules, enabling auto-quantization to measure
sensitivity at parent layers (e.g., MLP output for MoE experts) rather
than individual ops.
3. Also see https://github.com/NVIDIA/TensorRT-Model-Optimizer/pull/592
and https://github.com/NVIDIA/TensorRT-Model-Optimizer/pull/588
## Testing
See unittests; `tests/unit/torch/quantization/test_autoquant.py` and
`tests/unit/torch/quantization/plugins/test_huggingface.py`
## Before your PR is "*Ready for review*"
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- **Make sure you read and follow [Contributor
guidelines](https://github.com/NVIDIA/TensorRT-Model-Optimizer/blob/main/CONTRIBUTING.md)**
and your commits are signed.
- **Is this change backward compatible?**: Yes
- **Did you write any new necessary tests?**: Yes
- **Did you add or update any necessary documentation?**: Yes
- **Did you update
[Changelog](https://github.com/NVIDIA/TensorRT-Model-Optimizer/blob/main/CHANGELOG.rst)?**:
Not Required
## Additional Information
<!-- E.g. related issue. -->
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Summary by CodeRabbit
* **New Features**
* Added support for score modules in quantization workflows.
* Added optional naming for quantization recipes.
* **Bug Fixes**
* Improved quantization grouping rules documentation with clearer
configuration examples.
* **Refactor**
* Renamed quantization module parameters for improved clarity.
* Enhanced quantization search architecture for better scalability.
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
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---------
Signed-off-by: realAsma <akuriparambi@nvidia.com>
Co-authored-by: Asma Kuriparambil Thekkumpate <akuriparambi@akuriparambi-mlt.client.nvidia.com>
