Fix GPTQ Hessian coordinates after AWQ smoothing.

[sarahpardo]

What does this PR do?

Type of change: Bug fix

GPTQ previously bypassed disabled input quantizers while collecting
Hessians. Weight-only AWQ disables input quantization but retains a
pre-quant scale that transforms inputs before the linear operation.
Consequently, an AWQ→GPTQ chain collected the Hessian in the original
input coordinates while GPTQ operated on AWQ-smoothed weights.

This change always passes Hessian inputs through the input quantizer when
one exists. A disabled quantizer without transforms remains an identity,
while AWQ pre-quant scaling is now correctly represented.

Usage

No API changes.

Testing

Added an end-to-end AWQ→GPTQ regression test that verifies the Hessian
matches the transformed input coordinates and differs from the raw-input
Hessian.

Tested with:
pytest tests/gpu/torch/quantization/test_gptq.py

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• Is this change backward compatible?: ✅
• If you copied code from any other sources or added a new PIP dependency, did you follow guidance in CONTRIBUTING.md: N/A
• Did you write any new necessary tests?: ✅
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