Fix mixed INT8 FakeTensor output metadata

[tandede]

Summary

• make the mixed INT8 FakeTensor implementation return subA with the same shape and dtype contract as eager execution
• keep subA two-dimensional when there are zero outlier columns, including when outlier_cols is omitted
• add CPU and MPS operation checks for non-empty, empty, and omitted outlier-column inputs

Root cause

The fake implementation created subA as a fresh one-dimensional int64 tensor. Eager execution instead returns the selected input columns, which are two-dimensional and inherit the input dtype. This caused torch.library.opcheck to fail with mismatched output metadata. The eager no-outlier branch also returned a one-dimensional empty tensor, making the output rank depend on input data.

Impact

The custom operation now has stable output metadata for FakeTensor and graph-capture consumers. The numerical mixed INT8 result is unchanged.

Tests

• pytest -q tests/test_ops.py (649 passed, 69 skipped, 60 xfailed)
• focused mixed INT8 operation checks on CPU and MPS (4 passed)
• full-graph Linear8bitLt compile checks with threshold 6.0 on CPU and MPS (2 passed)
• pre-commit run --files bitsandbytes/_ops.py bitsandbytes/backends/default/ops.py tests/test_ops.py