Fix PyTorch matmul device placement

[FlorianPfaff]

Summary

• Preserve an existing non-CPU PyTorch tensor device when matmul receives mixed CPU/accelerator operands.
• Keep raw pyrecest._backend.pytorch.matmul and the active public PyTorch backend facade synchronized.
• Preserve existing dtype promotion before delegating to torch.matmul.

Bug fixed

matmul converted operands independently and then delegated to torch.matmul. A CPU tensor or array-like left operand paired with a CUDA/meta right operand could therefore run on or return a CPU tensor instead of preserving the existing accelerator operand.

Validation

• Syntax-checked the updated backend-support module locally with py_compile.
• Smoke-checked the wrapper logic locally with CPU-left/meta-right tensors.
• Full repository test suite not run in this connector session.

[github-actions]

✅MegaLinter analysis: Success

Descriptor	Linter	Files	Fixed	Errors	Warnings	Elapsed time
✅ COPYPASTE	jscpd	yes		no	no	70.99s
✅ JSON	prettier	7	0	0	0	1.0s
✅ JSON	v8r	7		0	0	5.04s
✅ MARKDOWN	markdownlint	68	0	0	0	1.72s
✅ MARKDOWN	markdown-table-formatter	68	0	0	0	0.82s
✅ PYTHON	black	1184	29	0	0	57.54s
✅ PYTHON	isort	1184	52	0	0	3.29s
✅ REPOSITORY	checkov	yes		no	no	45.95s
✅ REPOSITORY	gitleaks	yes		no	no	11.78s
✅ REPOSITORY	git_diff	yes		no	no	0.17s
✅ REPOSITORY	secretlint	yes		no	no	44.04s
✅ REPOSITORY	syft	yes		no	no	4.6s
✅ REPOSITORY	trivy-sbom	yes		no	no	5.12s
✅ REPOSITORY	trufflehog	yes		no	no	17.34s
✅ YAML	prettier	11	0	0	0	0.74s
✅ YAML	v8r	11		0	0	10.85s
✅ YAML	yamllint	11		0	0	0.47s

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