Benchmarks result in INTERNAL ASSERT FAILED when run with device mps

[apullin]

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)

[rusty1s]

Sorry for late reply. Our custom kernels currently do not support mps backend at the moment.

[apullin]

Darn. Sadly, it looks like Apple does not provide any kind of GPU BLAS.
Does this mean the sparse ops kernels would have to be manually implemented as Metal shaders?

[rusty1s]

I haven't looked at the detailed backend code required for mps yet, but yeah, it would mean we need to register MPS as a backend for torch-sparse and then implement this functionality in Metal.

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