This PR addresses issues raised by #3008.
1. Update documentation to indicate the correct maximum batch size for
TI training when xformers is and isn't used.
2. Update textual inversion code so that the default for batch size
is aware of xformer availability.
3. Add documentation for how to launch TI with distributed learning.
This PR ports the `main` PR #2871 to the v2.3 branch. This adjusts
the global diffusers model cache to work with the 0.14 diffusers
layout of placing models in HF_HOME/hub rather than HF_HOME/diffusers.
-At some point pathlib was added to the list of imported modules and this
broken the os.path code that assembled the sample data set.
-Now fixed by replacing os.path calls with Path methods
- The invokeai-ti and invokeai-merge scripts will crash if there is not enough space
in the console to fit the user interface (even after responsive formatting).
- This PR intercepts the errors and prints a useful error message advising user to
make window larger.
- Issue is that if insufficient diffusers models are defined in
models.yaml the frontend would ungraciously crash.
- Now it emits appropriate error messages telling user what the problem
is.
- This fixes an edge case crash when the textual inversion frontend
tried to display the list of models and no default model defined
in models.yaml
Co-authored-by: Jonathan <34005131+JPPhoto@users.noreply.github.com>
