July 28, 2020
PyTorch feature classification changes
Traditionally features in PyTorch were classified as either stable or experimental with an implicit third option of testing bleeding edge features by building master or through installing nightly builds (available via prebuilt whls). This has, in a few cases, caused some confusion around the level of readiness, commitment to the feature and backward compatibility that can be expected from a user perspective. Moving forward, we’d like to better classify the 3 types of features as well as defin...
July 28, 2020
Microsoft becomes maintainer of the Windows version of PyTorch
Along with the PyTorch 1.6 release, we are excited to announce that Microsoft has expanded its participation in the PyTorch community and will be responsible for the development and maintenance of the PyTorch build for Windows.
July 28, 2020
Introducing native PyTorch automatic mixed precision for faster training on NVIDIA GPUs
Most deep learning frameworks, including PyTorch, train with 32-bit floating point (FP32) arithmetic by default. However this is not essential to achieve full accuracy for many deep learning models. In 2017, NVIDIA researchers developed a methodology for mixed-precision training, which combined
