v1.8.1
版本发布时间: 2021-03-26 00:07:08
pytorch/pytorch最新发布版本:v2.4.1(2024-09-05 03:59:29)
PyTorch 1.8.1 Release Notes
- New Features
- Improvements
- Bug Fixes
- Documentation
New Features
Revamp of profiling tools in torch.profiler
The torch.profiler
submodule is now available. It leveraged the newly released kineto library for profiling.
You can find more details in this blogpost: https://pytorch.org/blog/introducing-pytorch-profiler-the-new-and-improved-performance-tool/
Enable use of autocast for pytorch xla (#48570)
The torch.cuda.autocast
package can now be used in conjunction with torch xla to provide easy mixed-precision training.
Improvements
- Make
torch.
submodule import more autocomplete-friendly (#52339) - Add support in ONNX for
torch.{isinf,any,all}
(#53529) - Replace thrust with cub in GPU implementation of
torch.randperm
for performance (#54537)
Bug fixes
Misc
- Fixes for
torch.distributions
validation checks (#53763) - Allow changing the padding vector for
nn.Embedding
(#53447) - Fix TensorPipe for large copies and interoperability with CUDA (#53804)
- Properly de-sugar
Ellipsis
in TorchScript (#53766) - Stop using OneDNN for group convolutions when groups size is a multiple of
24
(#54015) - Use
int8_t
instead ofchar
in{load,store}_scalar
(#52616) - Make ideep honor
torch.set_num_thread
(#53871) - Fix dimension out of range in
pixel_{un}shuffle
(#54178) - Update kineto to fix libtorch builds (#54205)
- Fix distributed autograd CUDA stream synchronization for send/recv operations (#54358)
ONNX
- Update error handling in ONNX to avoid
ValueError
(#53548) - Update assign output shape for nested structure and dict output (#53311)
- Update embedding export wrt
padding_idx
(#53931)