Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42249
Main change is to bring Caffe2's superior error messages for cuda initialization into c10 and use them in all code paths.
Basic logic:
| Case | Call to device_count() | init_cuda, e.g. allocating tensor |
| -- | -- | -- |
| all good | non-zero | just works |
| no gpus | 0, no warning | throw exception with good message |
| driver issues | 0, produce warning | throw exception with good message |
| out of memory with ASAN | 0, produce warning| throw exception with ASAN message |
Previously, the error thrown from init_cuda was very generic and the ASAN warning (if any) was buried in the logs.
Other clean up changes:
* cache device_count() always in a static variable
* move all asan macros in c10
Test Plan:
Hard to unittest because of build modes. Verified manually that the behavior from the table above holds by running the following script in different modes (ASAN/no-ASAN, CUDA_VISIBLE_DEVICES=):
```
print('before import')
import torch
print('after import')
print('devices: ', torch.cuda.device_count())
x = torch.tensor([1,2,3])
print('tensor creation')
x = x.cuda()
print('moved to cuda')
```
Reviewed By: ngimel
Differential Revision: D22824329
fbshipit-source-id: 5314007313a3897fc955b02f8b21b661ae35fdf5
Summary:
* Make c10::cuda functions regular non-inlined functions
* Add driver_version() and device_synchronize() functions
With this change I don't see anymore direct calls to CUDA API when look at Modules.cpp.obj
FYI malfet
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42251
Reviewed By: malfet
Differential Revision: D22826505
Pulled By: ziab
fbshipit-source-id: 8dc2f3e209d3710e2ce78411982a10e8c727573c
Summary:
This is to workaround an issue in hipclang wrt templated kernel name arguments to hipLaunchKernelGGL.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/41022
Differential Revision: D22404183
Pulled By: ngimel
fbshipit-source-id: 63135ccb9e087f4c8e8663ed383979f7e2c1ba06
Summary:
Changes in PR https://github.com/pytorch/pytorch/issues/39759 broke HIP caffe2.
hipify for caffe2 renames CUDA to HIP; torch does not.
If caffe2 calls into torch, it needs to use CUDA-named functions.
CC ezyang xw285cornell sunway513 houseroad dzhulgakov
Pull Request resolved: https://github.com/pytorch/pytorch/pull/39801
Differential Revision: D21982493
Pulled By: xw285cornell
fbshipit-source-id: 8e88e0fb80c71f0342e23ef0214a42d5542bdc70
Summary:
Gets rid of some in-kernel asserts where they can be replaced with static_asserts
Replaces bare in-kernel `assert` in one case with `CUDA_KERNEL_ASSERT` where necessary
replaces host code `assert`s with `TORCH_INTERNAL_ASSERT`
Another group of asserts is in fractional max pooling kernels which should be fixed regardless https://github.com/pytorch/pytorch/issues/39044, the problems there are not just asserts.
I've audited remaining cases of in-kernel asserts, and they are more like `TORCH_INTERNAL_ASSERT`, so they should not happen with invalid user data. I think it's ok to leave them as is.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/39047
Differential Revision: D21750392
Pulled By: ngimel
fbshipit-source-id: e9417523a2c672284de3515933cb7ed166e56719
Summary:
CC ezyang xw285cornell
HIP from ROCm 3.5 renames `hipOccupancyMaxActiveBlocksPerMultiprocessor` to `hipModuleOccupancyMaxActiveBlocksPerMultiprocessor`. In addition, the API parameter types now match CUDA. Add these changes in a backwards-compatible manner.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38551
Differential Revision: D21721832
Pulled By: ezyang
fbshipit-source-id: 6fc971845e363d7495d8be9550e76d0f082c3062
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35615
Python 2 has reached end-of-life and is no longer supported by PyTorch.
Now we can clean up a lot of cruft that we put in place to support it.
These changes were all done manually, and I skipped anything that seemed
like it would take more than a few seconds, so I think it makes sense to
review it manually as well (though using side-by-side view and ignoring
whitespace change might be helpful).
Test Plan: CI
Differential Revision: D20842886
Pulled By: dreiss
fbshipit-source-id: 8cad4e87c45895e7ce3938a88e61157a79504aed
Summary:
This enables cpp_extensions.load/load_inline. This works by hipify-ing cuda sources.
Also enable tests.
CuDNN/MIOpen extensions aren't yet supported, I propose to not do this in this PR.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35897
Differential Revision: D20983279
Pulled By: ezyang
fbshipit-source-id: a5d0f5ac592d04488a6a46522c58e2ee0a6fd57c
Summary:
This pull request has changes for:
1. Enabling a torch module with HIP code to be compiled by cpp_extensions.py
2. Fixes for hipify module to be able to be used by a torch extension
cc: ezyang iotamudelta jeffdaily
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32669
Differential Revision: D20033893
Pulled By: zou3519
fbshipit-source-id: fd6ddc8cdcd3930f41008636bb2bc9dd26cdb008
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31151
same as title. I am not sure why this was not added in the first place.
Test Plan: wait for build to succeed.
Reviewed By: bddppq, xw285cornell
Differential Revision: D18880216
fbshipit-source-id: 8b17d4fbd5dd08c28c52df8b1da77b69d56d65dc
Summary:
According to https://github.com/pytorch/pytorch/issues/27285 , seems we do not intend to use shebang as an indication of Python version, thus
we enable EXE001 flake8 check.
For violations, we either remove shebang from non-executable Python scripts or grant them executable permission.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/27560
Differential Revision: D17831782
Pulled By: ezyang
fbshipit-source-id: 6282fd3617b25676a6d959af0d318faf05c09b26
