Validate PyTorch repeat count dimensions

[FlorianPfaff]

Summary

• reject nested PyTorch repeat count arrays/tensors before calling torch.repeat_interleave
• align the PyTorch backend repeat wrapper with NumPy/PyRecEst repeat-count shape validation by raising ValueError for repeat counts deeper than 1-D
• add regression coverage for nested NumPy-style and tensor repeat-count inputs

Bug fixed

backend.repeat(..., repeats=[[...]]) under PYRECEST_BACKEND=pytorch allowed nested repeat counts to reach Torch directly. Torch then raised a low-level RuntimeError (repeats must be 0-dim or 1-dim tensor) instead of the backend rejecting the invalid NumPy-style repeat-count shape itself.

Testing

• Added tests/backend_support/test_pytorch_repeat_count_validation.py
• Reproduced the contract mismatch locally with NumPy 2.3.5 and Torch 2.10.0+cpu
• Full repository test suite was not run in this connector environment

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	63.57s
✅ JSON	prettier	7	0	0	0	1.1s
✅ JSON	v8r	7		0	0	4.65s
✅ MARKDOWN	markdownlint	68	0	0	0	1.81s
✅ MARKDOWN	markdown-table-formatter	68	0	0	0	0.81s
✅ PYTHON	black	1122	10	0	0	53.46s
✅ PYTHON	isort	1122	15	0	0	2.88s
✅ REPOSITORY	checkov	yes		no	no	44.62s
✅ REPOSITORY	gitleaks	yes		no	no	11.52s
✅ REPOSITORY	git_diff	yes		no	no	0.12s
✅ REPOSITORY	secretlint	yes		no	no	33.96s
✅ REPOSITORY	syft	yes		no	no	2.74s
✅ REPOSITORY	trivy-sbom	yes		no	no	11.1s
✅ REPOSITORY	trufflehog	yes		no	no	16.54s
✅ YAML	prettier	11	0	0	0	0.71s
✅ YAML	v8r	11		0	0	10.39s
✅ YAML	yamllint	11		0	0	0.47s

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