Fix multinomial CUDA misalignment and non-deterministic behavior (#55364)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/46702
- fails on probability distribution with odd items
- trying to access an `acc_type` (`float`) in a `scalar_t` (`float16`) aligned memory
- produce unrepeatable result for large input tensor
- parallel cumsum not monotonic at some positions
### Fixes
- computing cumsum on `acc_type` (`float`) instead of using `scalar_t` (`float16`) fixed both issues
- the non-monotonic behavior may happen even using `float`, though
- in these cases, deterministic behavior may be achieved by eliminating the race condition when writing the result, using the atomic function `atomicMax`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55364
Reviewed By: mruberry
Differential Revision: D28031666
Pulled By: ngimel
fbshipit-source-id: 0fc6289e0b9ea2d31ef3771e7ca370de8f5c02de
