env.sh:
- move check for torch to CONVTAINER_FLAVOR detection
Dockerfile
- only mount `/var/cache/apt` for apt related steps
- remove `docker-clean` from `/etc/apt/apt.conf.d` for BuildKit cache
- remove apt-get clean for BuildKit cache
- only copy frontend to frontend-builder
- mount `/usr/local/share/.cache/yarn` in frountend-builder
- separate steps for yarn install and yarn build
- build pytorch in pyproject-builder
build.sh
- prepare for installation with extras
This change allows passing a directory with multiple models in it to be
imported.
Ensures that diffusers directories will still work.
Fixed up some minor type issues.
This allows the --log_tokenization option to be used as a command line
argument (or from invokeai.init), making it possible to view
tokenization information in the terminal when using the web interface.
- 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>
This allows the --log_tokenization option to be used as a command line argument (or from invokeai.init), making it possible to view tokenization information in the terminal when using the web interface.
- Rename configure_invokeai.py to invokeai_configure.py to be consistent
with installed script name
- Remove warning message about half-precision models not being available
during the model download process.
- adjust estimated file size reported by configure
- guesstimate disk space needed for "all" models
- fix up the "latest" tag to be named 'v2.3-latest'
- To ensure a clean environment, the installer will now detect whether a
previous .venv exists in the install location, and move it to .venv-backup
before creating a fresh .venv.
- Any previous .venv-backup is deleted.
- User is informed of process.
- Rename configure_invokeai.py to invokeai_configure.py to be
consistent with installed script name
- Remove warning message about half-precision models not being
available during the model download process.
- adjust estimated file size reported by configure
- guesstimate disk space needed for "all" models
- fix up the "latest" tag to be named 'v2.3-latest'
`torch` wasn't seeing the environment variable. I suspect this is
because it was imported before the variable was set, so was running with
a different environment.
Many `torch` ops are supported on MPS so this wasn't noticed
immediately, but some samplers like k_dpm_2 still use unsupported
operations and need this fallback.
