Move quantization to training

[RdoubleA]

Context

What is the purpose of this PR? Is it to

• add a new feature
• fix a bug
• update tests and/or documentation
• other (please add here)

Motivation for moving files out of utils is extensively discussed in #1421. Here, we move quantization.py to training/quantization.py and update all callsites, configs.

This means torchtune.utils.quantization -> torchtune.training.quantization

Test plan

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• run pre-commit hooks and linters (make sure you've first installed via pre-commit install)
• 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

If your function changed a public API, please add a dummy example of what the user experience will look like when calling it.
Example of docstring:

torchtune/torchtune/modules/vision_transformer.py

Line 285 in 6a7951f

Examples:

Example in our docs: https://pytorch.org/torchtune/main/tutorials/qat_finetune.html#applying-qat-to-llama3-models

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

[pytorch-bot]

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