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Release 2.3.3 (#3058)
(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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README.md

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_For Linux with an AMD GPU:_
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```sh
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pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.2
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pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
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```
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_For Macintoshes, either Intel or M1/M2:_
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binary_installer/install.bat.in

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