fix(pruning): validate multidimensional tensor in channel-structured pruning (#107)

[rohith500]

Closes #107.

Validates that ChannelStructured magnitude pruning is applied to tensors with at least 2 dimensions, raising a descriptive ValueError for 1D tensors instead of crashing with ATen RuntimeError: selected index k out of range. Also adds unit test coverage for 1D tensor validation across positive and negative channel axes.

[rohith500]

Hi @u-simha,

Per your feedback and confirmation on #107, I've updated PR #108 to enforce multidimensional tensor validation:

1. Validation Check: In _compute_channel_mask, added if weight.ndim < 2: raise ValueError(...) requiring $\ge 2$ dimensions and directing users to Unstructured pruning for 1D tensors.
2. Early Dispatch: In compute_mask, ChannelStructured is dispatched to _compute_channel_mask so structural constraints are validated upfront even if schedule sparsity is 0.0.
3. Automated Tests: Updated tests/pruning/test_magnitude_pruner.py with tests verifying ValueError is raised for 1D and 0-D tensors with ChannelStructured across multiple axes and sparsities, and confirming that Unstructured() properly prunes 1D parameters.
4. Quality Gates: All 26 checks in make check pass cleanly, commit is cryptographically signed, and the Towncrier fragment is updated.

Ready for your review!