Fix PyTorch random.choice population handling

[FlorianPfaff]

Summary

• normalize PyTorch random.choice populations so Python integer and list inputs match the NumPy/JAX backend contract
• continue supporting tensor populations and tensor/list probabilities by moving probability inputs to the sampled tensor device
• add backend-random regression coverage for Python list and integer populations

Rationale

The NumPy and JAX backend random.choice helpers accept NumPy-compatible populations such as 5 and [10, 20, 30]. The PyTorch backend previously asserted that a was already a tensor, so otherwise portable code failed only under PyTorch.

Validation

• connector compare confirms the branch is ahead of main by two commits, behind by zero, and changes only src/pyrecest/_backend/pytorch/random.py and tests/test_backend_random.py
• local PyTorch smoke test of the patched choice logic with list, integer, and tensor populations
• local repository checkout/pytest execution was not possible here because the execution sandbox could not resolve github.com; PR CI should run the backend test matrix

[github-actions]

✅⚠️MegaLinter analysis: Success with warnings

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	53.88s
✅ JSON	prettier	7	0	0	0	0.81s
✅ JSON	v8r	7		0	0	5.72s
⚠️ MARKDOWN	markdownlint	66	0	1	0	1.78s
✅ MARKDOWN	markdown-table-formatter	66	0	0	0	0.67s
✅ PYTHON	black	755	6	0	0	40.67s
✅ PYTHON	isort	755	6	0	0	3.3s
✅ REPOSITORY	checkov	yes		no	no	38.11s
✅ REPOSITORY	gitleaks	yes		no	no	14.98s
✅ REPOSITORY	git_diff	yes		no	no	0.11s
✅ REPOSITORY	secretlint	yes		no	no	23.88s
✅ REPOSITORY	syft	yes		no	no	3.89s
✅ REPOSITORY	trivy-sbom	yes		no	no	6.85s
✅ REPOSITORY	trufflehog	yes		no	no	22.92s
✅ YAML	prettier	10	0	0	0	0.72s
✅ YAML	v8r	10		0	0	12.52s
✅ YAML	yamllint	10		0	0	0.5s

Detailed Issues

⚠️ MARKDOWN / markdownlint - 1 error

.github/pull_request_template.md:1 error MD041/first-line-heading/first-line-h1 First line in a file should be a top-level heading [Context: "## Summary"]

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