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  • v2.3.3 fd74f51384
    比较

    Release 2.3.3 (#3058)

    frostbyte_neo 发布于 2023-04-01 14:17:43 +00:00

    (note that this is actually release candidate 7, but I made the mistake
    of including an old rc number in the branch and can't easily change it)

    Updating Root directory

    • Introduced new mechanism for updating the root directory when
      necessary. Currently only used to update the invoke.sh script using new
      dialog colors.
    • Fixed ROCm torch module version number

    Loading legacy 2.0/2.1 models

    • Due to not converting the torch.dtype precision correctly, the
      load_pipeline_from_original_stable_diffusion_ckpt() was returning
      models of dtype float32 regardless of the precision setting. This caused
      a precision mismatch crash.
    • Problem now fixed (also see #3057 for the same fix to main)

    Support for a fourth textual inversion embedding file format

    • This variant, exemplified by "easynegative.safetensors" has a single
      'embparam' key containing a Tensor.
    • Also refactored code to make it easier to read.
    • Handle both pickle and safetensor formats.

    Persistent model selection

    • To be consistent with WebUI parameter behavior, the currently selected
      model is saved on exit and restored on restart for both WebUI and CLI

    Bug fixes

    • Name of VAE cache directory was "hug", not "hub". This is fixed.

    VAE fixes

    • Allow custom VAEs to be assigned to a legacy model by placing a
      like-named vae file adjacent to the checkpoint file.
    • The custom VAE will be picked up and incorporated into the diffusers
      model if the user chooses to convert/optimize.

    Custom config file loading

    • Some of the civitai models instruct users to place a custom .yaml file
      adjacent to the checkpoint file. This generally wasn't working because
      some of the .yaml files use FrozenCLIPEmbedder rather than
      WeightedFrozenCLIPEmbedder, and our FrozenCLIPEmbedder class doesn't
      handle the personalization_config section used by the the textual
      inversion manager. Other .yaml files don't have the
      personalization_config section at all. Both these issues are
      fixed.#1685

    Consistent pytorch version

    • There was an inconsistency between the pytorch version requirement in
      pyproject.toml and the requirement in the installer (which does a
      little jiggery-pokery to load torch with the right CUDA/ROCm version
      prior to the main pip install. This was causing torch to be installed,
      then uninstalled, and reinstalled with a different version number. This
      is now fixed.
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