Add squeeze/unsqueeze support to IntQuantTensor

[mumallaeng]

Reason for this PR

QuantTensor had no squeeze/unsqueeze, so torch.squeeze/torch.unsqueeze (and the .squeeze()/.unsqueeze() methods) either raised or silently dropped quantization metadata (scale/zero_point/bit_width) for IntQuantTensor.

Closes #891.

Changes Made in this PR

Added squeeze/unsqueeze to IntMixin in base_quant_tensor.py, following the same pattern already used by transpose/permute: per-channel metadata (same rank as the value tensor) is squeezed/unsqueezed alongside the value, per-tensor (lower-rank) metadata is left untouched. Registered torch.squeeze/torch.unsqueeze handlers in torch_handler.py so the free-function form dispatches correctly too.

FloatQuantTensor is intentionally left out of scope, per the prior PR #941 discussion - a follow-up can extend this once FloatQuantTensor's metadata shape handling is worked out separately.

Testing Summary

Added test_quant_tensor_squeeze and test_quant_tensor_unsqueeze to tests/brevitas/quant_tensor/test_quant_tensor.py, covering both per-tensor and per-channel scale. Ran the full test_quant_tensor.py file locally (30/30 pass). Confirmed the new tests fail with AttributeError against the pre-change source and pass after. isort/yapf (pinned versions from .pre-commit-config.yaml) show no diff on the changed files.

Risk Highlight

• This PR includes code from another work (please detail).
• This PR contains API-breaking changes.
• This PR depends on work in another PR (please provide links/details).
• This PR introduces new dependencies (please detail).
• There are coverage gaps not covered by tests.
• Documentation updates required in subsequent PR.

Checklist

• Code comments added to any hard-to-understand areas, if applicable.
• Changes generate no new warnings.
• Updated any relevant tests, if applicable.
• No conflicts with destination master branch.
• I reviewed my own code changes.
• Initial CI/CD passing.
• 1+ reviews given, and any review issues addressed and approved.
• Post-review full CI/CD passing.

[Giuseppe5]

Hey, thanks for opening this PR. Unless this is causing some issues for you, we might want to skip this change for now.

We are planning major changes around QuantTensor #1579, and we might want to merge that before applying other changes to QuantTensor.

[mumallaeng]

@Giuseppe5 Thanks for the heads-up, that makes sense. I'll convert this to a draft and hold it until #1579 lands, then re-check whether squeeze/unsqueeze is still needed on top of the tensor-subclass QuantTensor.