Preserve Gauss-von-Mises single-point autograd

[FlorianPfaff]

Bug

GaussVonMisesDistribution.pdf(...) kept backend-native values for batched evaluation, but the single-point path returned float(p[0]).

On the PyTorch backend, a query tensor with requires_grad=True therefore produced a Python float. The conversion silently detached the density from the computation graph, so callers could not differentiate a single-point likelihood even though the equivalent batched path remained differentiable.

Fix

Return the backend scalar p[0] directly for single-point evaluation instead of converting it to Python float.

This preserves the existing numerical value while keeping the active backend's dtype, device, and autograd history.

Regression coverage

Add a PyTorch-backend regression that evaluates a single Gauss-von-Mises point with requires_grad=True and verifies:

• the result is a scalar PyTorch tensor;
• dtype and device match the query;
• the density is finite and positive;
• backpropagation reaches both query coordinates with finite, nonzero gradients.

Validation

• independently confirmed that converting a differentiable PyTorch scalar with float(...) returns a plain Python float and loses autograd;
• final production diff is one line;
• branch is based directly on current main (f196ec41d1d8681e279936db9f1a0a3abfa276e7) and is 2 commits ahead / 0 behind;
• GitHub Actions is authoritative for the full backend, lint, packaging, documentation, and integration matrix.

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Max errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no		no	7.69s
✅ JSON	prettier	7	0	0		0	0.6s
✅ JSON	v8r	7		0		0	4.7s
✅ MARKDOWN	markdownlint	68	0	0		0	2.05s
✅ MARKDOWN	markdown-table-formatter	68	0	0		0	0.5s
✅ PYTHON	black	1876	91	0		0	72.32s
✅ PYTHON	isort	1876	150	0		0	2.88s
✅ REPOSITORY	betterleaks	yes		no		no	1.13s
✅ REPOSITORY	checkov	yes		no		no	36.77s
✅ REPOSITORY	git_diff	yes		no		no	0.25s
✅ REPOSITORY	secretlint	yes		no		no	103.95s
✅ REPOSITORY	syft	yes		no		no	2.98s
✅ REPOSITORY	trivy-sbom	yes		no		no	2.42s
✅ YAML	prettier	11	0	0		0	0.76s
✅ YAML	v8r	11		0		0	17.8s
✅ YAML	yamllint	11		0		0	1.08s

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