Fix PyTorch randint array-valued bounds

[FlorianPfaff]

Summary

• add NumPy-compatible handling for array-valued/broadcasted low and high bounds in the PyTorch random backend's randint
• preserve scalar-bound behavior by continuing to delegate to torch.randint
• add regression tests for broadcasted bounds, array-only high, incompatible sizes, and invalid bounds

Validation

• Not run locally against the full repository because the execution environment cannot clone GitHub. The patch is covered by focused regression tests added in this PR.

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	49.41s
✅ JSON	prettier	7	0	0	0	0.8s
✅ JSON	v8r	7		0	0	4.61s
✅ MARKDOWN	markdownlint	66	0	0	0	1.63s
✅ MARKDOWN	markdown-table-formatter	66	0	0	0	0.73s
✅ PYTHON	black	786	0	0	0	36.46s
✅ PYTHON	isort	786	0	0	0	7.3s
✅ REPOSITORY	checkov	yes		no	no	42.8s
✅ REPOSITORY	gitleaks	yes		no	no	12.64s
✅ REPOSITORY	git_diff	yes		no	no	0.12s
✅ REPOSITORY	secretlint	yes		no	no	24.8s
✅ REPOSITORY	syft	yes		no	no	3.98s
✅ REPOSITORY	trivy-sbom	yes		no	no	5.29s
✅ REPOSITORY	trufflehog	yes		no	no	22.09s
✅ YAML	prettier	11	0	0	0	0.7s
✅ YAML	v8r	11		0	0	10.36s
✅ YAML	yamllint	11		0	0	0.45s

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