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Description
Running the benchmarks main.py targeting device mps results in an assertion failure:
Traceback (most recent call last):
File "/Users/apullin/personal/pyg/pytorch_sparse/benchmark/main.py", line 174, in <module>
correctness(dataset)
File "/Users/apullin/anaconda3/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/Users/apullin/personal/pyg/pytorch_sparse/benchmark/main.py", line 43, in correctness
mat.fill_cache_()
File "/Users/apullin/anaconda3/lib/python3.10/site-packages/torch_sparse-0.6.18-py3.10-macosx-11.0-arm64.egg/torch_sparse/tensor.py", line 286, in fill_cache_
self.storage.fill_cache_()
File "/Users/apullin/anaconda3/lib/python3.10/site-packages/torch_sparse-0.6.18-py3.10-macosx-11.0-arm64.egg/torch_sparse/storage.py", line 470, in fill_cache_
self.rowptr()
File "/Users/apullin/anaconda3/lib/python3.10/site-packages/torch_sparse-0.6.18-py3.10-macosx-11.0-arm64.egg/torch_sparse/storage.py", line 209, in rowptr
rowptr = torch.ops.torch_sparse.ind2ptr(row, self._sparse_sizes[0])
File "/Users/apullin/anaconda3/lib/python3.10/site-packages/torch/_ops.py", line 692, in __call__
return self._op(*args, **kwargs or {})
RuntimeError: ind.device().is_cpu() INTERNAL ASSERT FAILED at "/Users/apullin/personal/pyg/pytorch_sparse/csrc/cpu/convert_cpu.cpp":8, please report a bug to PyTorch. ind must be CPU tensor
Invocation was:
python main.py --device=mps
notably, I also had to comment out lines 66 and 84, with import torch.mps, to get this to run - those imports should not be needed?
A similar error occurs when trying to do an applied problem using mps as the device, e.g. a GCN that uses a sparse adjacency matrix.
(this came up in coursework - I will have to recreate a minimum working example so I don't post a solution)
running:
torch==2.1.0
torch-scatter==2.1.2
torch-sparse==0.6.18
torch_geometric==2.4.0
on python 3.10
on Apple Silicon (M2 Max)
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