Fixes#115331.
This is a temporary fix to increase the compile time number of GPUs to 120 until #119639 can be merged. Changing the parameter to 128 leads to annoying errors, as some checks would be tautological (`int8_t` is always < 128).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/121076
Approved by: https://github.com/albanD
Fixes#115331.
This PR increases the number of valid GPU devices to 512 (from 64) in order to future-proof PyTorch for providers that offer [single nodes with a large device count](https://www.tensorwave.com/). Until now, `DeviceIndex` was an `int8_t`, thus multiple changes were necessary:
- `DeviceIndex` changed to `int16_t`. Updated consumers that assume it to be an `int8_t`.
- Updated bounds checking for `torch.device()` in the Python frontend. Right now, we allow funny things like `torch.device('cpu', 200).index == -56`, which is undefined behavior. I inserted some checks to only allow values between 0 and `c10::Device::MAX_NUM_DEVICES - 1`.
- Updated the `ArgumentInfo` struct as it hardcodes the device index as 8 bit field [^1]. Might be a breaking change, not sure if users rely on this.
- Introduced `c10::Device::MAX_NUM_DEVICES` as a replacement for the old `C10_COMPILE_TIME_MAX_GPUS`
[^1]: This field was unsigned, so I guess this has also been undef behavior the whole time? Our default device index is -1, so this always wrapped around to 255 when written to the `ArgumentInfo` struct. When I switched the `DeviceIndex` to `int16_t`, it actually stayed 255 after unpacking from `ArgumentInfo` again, as the `DeviceIndex` was now wide enough that it didn't wrap back to -1.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/119639
Approved by: https://github.com/cyyever, https://github.com/albanD, https://github.com/huydhn
Fixes#115331.
This PR increases the number of valid GPU devices to 512 (from 64) in order to future-proof PyTorch for providers that offer [single nodes with a large device count](https://www.tensorwave.com/). Until now, `DeviceIndex` was an `int8_t`, thus multiple changes were necessary:
- `DeviceIndex` changed to `int16_t`. Updated consumers that assume it to be an `int8_t`.
- Updated bounds checking for `torch.device()` in the Python frontend. Right now, we allow funny things like `torch.device('cpu', 200).index == -56`, which is undefined behavior. I inserted some checks to only allow values between 0 and `c10::Device::MAX_NUM_DEVICES - 1`.
- Updated the `ArgumentInfo` struct as it hardcodes the device index as 8 bit field [^1]. Might be a breaking change, not sure if users rely on this.
- Introduced `c10::Device::MAX_NUM_DEVICES` as a replacement for the old `C10_COMPILE_TIME_MAX_GPUS`
[^1]: This field was unsigned, so I guess this has also been undef behavior the whole time? Our default device index is -1, so this always wrapped around to 255 when written to the `ArgumentInfo` struct. When I switched the `DeviceIndex` to `int16_t`, it actually stayed 255 after unpacking from `ArgumentInfo` again, as the `DeviceIndex` was now wide enough that it didn't wrap back to -1.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/119639
Approved by: https://github.com/cyyever, https://github.com/albanD
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70851
This is a step towards OSS/fbcode convergence since OSS uses this file
in both CMake and Bazel.
ghstack-source-id: 147170896
Test Plan: Relying on the extensive CI internal tests for this.
Reviewed By: malfet
Differential Revision: D33299102
fbshipit-source-id: c650dd4755f8d696d5fce81c583d5c73782e3990
(cherry picked from commit 741ca140c8)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15692
It was leading to ocassional crashes with dynamically linked CUDA because runtime was already destroyed.
Also, unique_ptr<T[]> is more suitable than deque<T> for the purpose.
Reviewed By: Yangqing
Differential Revision: D13571988
fbshipit-source-id: 37eb26dfbe361c49160367b53f87bd037c6c0e46
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/13900
Add c10 cuda library.
Right now, this is not used by anything, and only tests if the CUDA
headers are available (and not, e.g., that linking works.)
Extra changes:
- cmake/public/cuda.cmake now is correctly include guarded, so you
can include it multiple times without trouble.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Reviewed By: smessmer
Differential Revision: D13025313
fbshipit-source-id: fda85b4c35783ffb48ddd6bbb98dbd9154119d86
