Final PyTorch 1.8 Release

This is the final release for PyTorch 1.8. This branch has been archived in "archive-1.8". The develop branch now supports PyTorch 2.

What's Changed

• Add improved FaceID model and new datasets by @oguzhanbsolak in #276
• Add NAS KWS model, Dynamic Augmentation and Automated Evaluation Notebook by @alicangok in #280
• Face Detection Library Replacement by @oguzhanbsolak in #287 and #320
• Add Auto Encoder Model, Sample Motor Dataset Loader, and Evaluation Notebooks by @rotx-maxim in #296
• Update KWS, MSNoise, Signalmixer Data Loaders & Evaluation Notebook by @EyubogluMerve in #299
• Final PyTorch 1.8 release by @rotx-maxim in #324
• Improve documentation
• Various bug fixes

Full Changelog: 2023121...2024070

New models and datasets, bug fixes, documentation updates

What's Changed

• Bug fixes and documentation updates
• Add depthwise convolution support to Conv1d, and depthwise ConvTranspose2d to MAX78002
• Updated face detection, KWS and cats & dogs models
• New action recognition model and Kinetics400 dataset
• New object detection model: Feature Pyramid Detector (FPN) - PascalVOC
• New Bayer2RGB network for debayerization

Bug fixes, documentation updates, model improvements

What's Changed

• Bug fixes
• Documentation updates
• Add support for pool dilation on MAX78002
• Add notebook to evaluate a trained KWS model with audio files

Full Changelog: 2022071...2022122

Object detection model; various improvements

• Object detection model and example
• Bug fixes
• Improved documentation
• Updated examples
• Updated submodules

Documentation updates and bug fixes

• Bug fixes
• Improved documentation

Please follow the instructions in README.md to upgrade (ignore the zip files under “Assets”).

Improved documentation and Windows support, bug fixes

Note: “develop” is now the default branch. The virtual environment is now in the “venv” folder.

• Documentation improvements
• Bug fixes
• Windows support (WSL2 and native)
• Dilated Conv1d
• Additional models and datasets
• Updated SDK

Please follow the instructions in README.md to upgrade (ignore the zip files under “Assets”).

Bug fixes, documentation improvements

• Minor bug fixes to training script
• Documentation improvements

Please follow the instructions in README.md to upgrade (ignore the zip files in the Release).

Network Architecture Search (NAS), updated Documentation, Bugfixes

•	Network Architecture Search (NAS)
•	Update documentation
•	Update models and data loaders
•	Bug fixes

Please follow the instructions in README.md to upgrade (ignore the zip files in the Release).

PyTorch 1.8.1, updated Documentation, Bugfixes

• Update documentation
• Upgrade to PyTorch 1.8.1
• ConvTranspose2d support
• Update models and data loaders
• Bug fixes

Please follow the instructions in README.md to upgrade (ignore the zip files in the Release).

Quantization-Aware Training, Python 3.8.6, Bugfixes

The main improvement in this release is enabling Quantization-Aware Training (QAT) by default.
Additionally, it upgrades to:

• PyTorch 1.71, Python 3.8.6, CUDA 11
  There is also a number of bug fixes and documentation improvements.

Please follow the instructions in README.md to upgrade (ignore the zip files in the Release).