v22.1.0

[bmaltais]

• 2023/10/10 (v22.1.0)
  • Remove support for torch 1 to align with kohya_ss sd-scripts code base.
  • Add Intel ARC GPU support with IPEX support on Linuix / WSL
    • Users needs to set these manually:
      • Mixed precision to BF16,
      • Attention to SDPA,
      • Optimizer to: AdamW (or any other non 8 bit one).
    • Run setup with: ./setup.sh --use-ipex
    • Run the GUI with: ./gui.sh --use-ipex
  • Merging main branch of sd-scripts:
    • tag_images_by_wd_14_tagger.py now supports Onnx. If you use Onnx, TensorFlow is not required anymore. #864 Thanks to Isotr0py!
      • --onnx option is added. If you use Onnx, specify --onnx option.
      • Please install Onnx and other required packages.
        1. Uninstall TensorFlow.
        2. pip install tensorboard==2.14.1 This is required for the specified version of protobuf.
        3. pip install protobuf==3.20.3 This is required for Onnx.
        4. pip install onnx==1.14.1
        5. pip install onnxruntime-gpu==1.16.0 or pip install onnxruntime==1.16.0
    • --append_tags option is added to tag_images_by_wd_14_tagger.py. This option appends the tags to the existing tags, instead of replacing them. #858 Thanks to a-l-e-x-d-s-9!
    • OFT is now supported.
      • You can use networks.oft for the network module in sdxl_train_network.py. The usage is the same as networks.lora. Some options are not supported.
      • sdxl_gen_img.py also supports OFT as --network_module.
      • OFT only supports SDXL currently. Because current OFT tweaks Q/K/V and O in the transformer, and SD1/2 have extremely fewer transformers than SDXL.
      • The implementation is heavily based on laksjdjf's OFT implementation. Thanks to laksjdjf!
    • Other bug fixes and improvements.