[AWQ] Support accumulation for reduced memory usage (#1435)

> [!NOTE]  
> @brian-dellabetta updated summary here (took over this PR from
@kylesayrs )

### Summary
This update removes the `Catcher` logic ported from AutoAWQ, instead
using the SequentialPipeline features and a couple hooks to cache args
into module forward passes, as needed to run AWQ. Should cause no
significant change in results, but this should be a more accurate
implementation because kwargs are cached for each parent layer, rather
than re-using those of the first module.

Leveraging `IntermediatesCache` for cached values, this also exposes a
new `offload_cache` bool value on `AWQModifier`, if set to True it will
offload cached values at the expense of slower runtime. With
`meta-llama/Llama-2-7b-hf`, offloading decreases max GPU memory from
~27GB to ~20GB, at the cost of `apply_smoothing` taking ~17 seconds per
iteration as opposed to ~5 seconds. Because of this, I am leaving the
default to not offload, just noting in the docstring to toggle this if
users encounter OOM errors.

### Test Plan
Confirmed that these changes don't significantly alter PPL scores
relative to current implementation on main.

- `meta-llama/Llama-3.2-3B-Instruct`
  - PPL 14.1523 on main, 14.081 on this branch
- `Qwen/Qwen2.5-7B-Instruct`
  - PPL 10.411 on main, 10.736 on this branch
- `meta-llama/Llama-2-7b-hf`
  - PPL 9.5075 on main, 9.503 on this branch

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Signed-off-by: Brian Dellabetta <[email protected]>
Co-authored-by: Brian Dellabetta <[email protected]>

Author: kylesayrs