Fix PyTorch triangular-index NumPy contract

[FlorianPfaff]

Summary

Fixes tril_indices and triu_indices on the PyTorch backend so they follow the NumPy-shaped backend API instead of exposing torch.tril_indices/torch.triu_indices directly.

Before this change:

• backend.tril_indices(3) raises because Torch requires both row and col.
• Supplying Torch-style dimensions returns one 2 x N tensor instead of NumPy's (rows, cols) tuple.
• Negative dimensions raise in Torch although NumPy returns empty index arrays.

The compatibility hook now:

• accepts (n, k=0, m=None),
• returns a tuple of 1-D tensors,
• matches NumPy for square/rectangular, offset, and negative-dimension cases,
• preserves optional Torch dtype, device, and layout keywords for raw-backend callers.

Regression tests cover both the public PyTorch backend and the raw PyTorch backend when NumPy is the selected public backend.

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Max errors	Warnings	Elapsed time
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✅ JSON	prettier	7	0	0		0	0.92s
✅ JSON	v8r	7		0		0	4.44s
✅ MARKDOWN	markdownlint	68	0	0		0	1.85s
✅ MARKDOWN	markdown-table-formatter	68	0	0		0	0.41s
✅ PYTHON	black	2007	23	0		0	58.89s
✅ PYTHON	isort	2007	39	0		0	2.86s
✅ REPOSITORY	betterleaks	yes		no		no	1.16s
✅ REPOSITORY	checkov	yes		no		no	34.04s
✅ REPOSITORY	git_diff	yes		no		no	0.1s
✅ REPOSITORY	secretlint	yes		no		no	101.32s
✅ REPOSITORY	syft	yes		no		no	2.96s
✅ REPOSITORY	trivy-sbom	yes		no		no	2.64s
✅ YAML	prettier	11	0	0		0	0.52s
✅ YAML	v8r	11		0		0	16.06s
✅ YAML	yamllint	11		0		0	0.85s

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