Enhancements:
1. Directory-based imports will not attempt to import components of diffusers models.
2. Diffuser directory imports now supported
3. Files that end with .ckpt that are not Stable Diffusion models (such as VAEs) are
skipped during import.
Bugs identified in Psychedelicious's review:
1. The invokeai-configure form now tracks the current contents of `invokeai.init` correctly.
2. The autoencoders are no longer treated like installable models, but instead are
mandatory support models. They will no longer appear in `models.yaml`
Bugs identified in Damian's review:
1. If invokeai-model-install is started before the root directory is initialized, it will
call invokeai-configure to fix the matter.
2. Fix bug that was causing empty `models.yaml` under certain conditions.
3. Made import textbox smaller
4. Hide the "convert to diffusers" options if nothing to import.
In theory, this reduces peak memory consumption by doing the conditioned
and un-conditioned predictions one after the other instead of in a
single mini-batch.
In practice, it doesn't reduce the reported "Max VRAM used for this
generation" for me, even without xformers. (But it does slow things down
by a good 18%.)
That suggests to me that the peak memory usage is during VAE decoding,
not the diffusion unet, but ymmv. It does [improve things for gogurt's
16 GB
M1](https://github.com/invoke-ai/InvokeAI/pull/2732#issuecomment-1436187407),
so it seems worthwhile.
To try it out, use the `--sequential_guidance` option:
2dded68267/ldm/invoke/args.py (L487-L492)
- Adds an update action to launcher script
- This action calls new python script `invokeai-update`, which prompts
user to update to latest release version, main development version, or
an arbitrary git tag or branch name.
- It then uses `pip` to update to whatever tag was specified.
The user interface (such as it is) looks like this:
![updater-screenshot](https://user-images.githubusercontent.com/111189/218291539-e5542662-6bfd-46ef-8ea9-655ca77392b7.png)
- The TI script was looping over all files in the training image
directory, regardless of whether they were image files or not. This PR
adds a check for image file extensions.
-
- Closes#2715
- Fixes longstanding bug in the token vector size code which caused .pt
files to be assigned the wrong token vector length. These were then
tossed out during directory scanning.
- Fixes longstanding bug in the token vector size code which caused
.pt files to be assigned the wrong token vector length. These
were then tossed out during directory scanning.
- Fixed the test for token length; tested on several .pt and .bin files
- Also added a __main__ entrypoint for CLI.py, to make pdb debugging a
bit more convenient.