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(Porting most of #161008) Hooking SymmetricMemory Allocator to MemPool so that user can create symmetric tensors with regular `torch.zeros`, `torch.arange` etc factories. Also so that our ops can have functional variants that create `out` tensors on symmetric memory. To end users, this PR supports a python UI as follows: ``` allocator = symm_mem.get_mempool_allocator(device) mempool = torch.cuda.MemPool(allocator) with torch.cuda.use_mem_pool(mempool): tensor = torch.arange(numel, dtype=dtype, device=device) ``` Added tests for both use cases above. Pull Request resolved: https://github.com/pytorch/pytorch/pull/161471 Approved by: https://github.com/ngimel ghstack dependencies: #161470 |
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