Bug fix release with updated binaries for Python 3.9 and cuDNN 8.0.5
PyTorch 1.7.1 Release Notes
- New Features
- Critical Fixes
- Other Fixes
New Features
Add Python 3.9 binaries for linux and macOS (#48133) and Windows (#48218)
NOTE: Conda installs for Python 3.9 will require the conda-forge
channel, example:
conda install -y -c pytorch -c conda-forge pytorch
.
Upgrade CUDA binaries to use cuDNN 8.0.5 (builder repo #571)
This upgrade fix regressions on Ampere cards introduced in cuDNN 8.0.4.
It will improve performance for 3090 RTX cards, and may improve performance in other RTX-30 series card.
Critical Fixes
Python 3.9
- Use custom version of pybind11 to work around Python 3.9 issues (#48312)
- Fix jit Python 3.9 parsing (#48744)
- Fix cpp_extension to work with Python 3.9 (#48768)
Build
- Fix cpp_extension to properly handle env variable on Windows (#48937)
- Properly package libomp.dylib for macOS binaries (#48337)
- Fix build for statically linked OpenBLAS on aarch64 (#48819)
Misc
torch.sqrt
: fix wrong output values for very large complex input (#48216)max_pool1d
: fix for discontiguous inputs (#48219)collect_env
: fix detection of DEBUG flag (#48319)collect_env
: Fix to work when PyTorch is not installed (#48311)- Fix
amp
memory usage when running inno_grad()
mode (#48936) nn.ParameterList
andnn.ParameterDict
: Remove spurious warnings (#48215)- Tensor Expression fuser bugfixes (#48137)