mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 12:54:11 +08:00
0674ab7e33
According to the [APL documentation](https://developer.arm.com/documentation/101004/2404/General-information/Arm-Performance-Libraries-example-programs), libraries ending with _mp are OpenMP multi-threaded libraries. When a project is compiled with MSVC and the -openmp flag, the vcomp library (Visual C++ implementation of OpenMP) is used for runtime calls. However, the current APL implementation uses the libomp.dll (LLVM) variant. As a result, there are unexpected behaviors at runtime. --- For Example: ```python import torch # Create a sparse tensor # Input (Sparse Tensor): # [[0, 1], # [1, 0]] indices = torch.tensor([[0, 1], [1, 0]]) values = torch.tensor([1, 1], dtype=torch.float32) size = torch.Size([2, 2]) sparse_tensor = torch.sparse_coo_tensor(indices, values, size) # Convert sparse tensor to dense tensor dense_tensor = sparse_tensor.to_dense() # Expected Output (Dense Tensor): # [[0, 1], # [1, 0]] print("\nDense Tensor:") print(dense_tensor) ``` However, it prints unexpected outputs such as: ```python # [[0, 11], # [10, 0]] ``` The issue arises because the following code does not function as expected at runtime: https://github.com/pytorch/pytorch/blob/main/aten/src/ATen/ParallelOpenMP.h#L30 ```c++ // returns 1 , however since OpenMP is enabled it should return total number of threads int64_t num_threads = omp_get_num_threads(); ``` --- In the runtime, loading multiple OpenMP libraries (in this case `libomp` and `vcomp`) is causing unexpected behaviours. So, we've changed libraries from `_mp` to non `_mp` versions and we used `vcomp` for OpenMP calls. Pull Request resolved: https://github.com/pytorch/pytorch/pull/145215 Approved by: https://github.com/ozanMSFT, https://github.com/malfet Co-authored-by: Ozan Aydin <148207261+ozanMSFT@users.noreply.github.com>