Put sparse all reduce results to input tensors (#32226)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32226
right now if users call torch.dist.all_reduce() on dense tensors, outputs are put in input tensors. but if users call torch.dist.all_reduce() on sparse tensors, outputs are neither returned explicitly to users nor are put in input tensors.
To make torch.dist.all_reduce() API have same behavior on both dense tensors and sparse tensors, this diff is made to make torch.dist.all_reduce() on sparse tensors to put output in input tensors as well. This is acheived by simply calling input_sparse.copy_(output_sparse), see PR https://github.com/pytorch/pytorch/pull/9005 that implemented copy_ for sparse tensors.
close #31413
ghstack-source-id: 96984228
Test Plan: unit test
Differential Revision: D19192952
fbshipit-source-id: 2dd31dc057f20cc42b44b9e55df864afa2918c33
