### What this PR does / why we need it?
This PR introduces a caching mechanism for CPU-based `torch.Generator`
objects in the `_random_sample_310p` function to optimize sampling
performance. It includes unit tests for cache persistence and state
recovery. Feedback highlights a critical bug where keying the cache by
batch index instead of generator ID can break RNG reproducibility during
request re-scheduling, and notes a potential memory leak in the global
cache.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Tested via new unit tests in `tests/ut/_310p/sample/test_sampler_310.py`
verifying cache logic and error handling.
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Signed-off-by: csoulnd <daidaicurry@foxmail.com>
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