F.A.Q.#
Frequently-Asked-Questions#
Here are a few common installation problems and their solutions. Often these are caused by incomplete installations or crashes during the install process.
During conda env create, conda hangs indefinitely#
If it is because of the last PIP step (usually stuck in the Git Clone step, you can check the detailed log by this method):
export PIP_LOG="/tmp/pip_log.txt"
touch ${PIP_LOG}
tail -f ${PIP_LOG} &
conda env create -f environment-mac.yaml --debug --verbose
killall tail
rm ${PIP_LOG}
SOLUTION
Conda sometimes gets stuck at the last PIP step, in which several git repositories are cloned and built.
Enter the stable-diffusion directory and completely remove the src directory
and all its contents. The safest way to do this is to enter the stable-diffusion
directory and give the command git clean -f. If this still doesn't fix the
problem, try "conda clean -all" and then restart at the conda env create step.
To further understand the problem to checking the install lot using this method:
export PIP_LOG="/tmp/pip_log.txt"
touch ${PIP_LOG}
tail -f ${PIP_LOG} &
conda env create -f environment-mac.yaml --debug --verbose
killall tail
rm ${PIP_LOG}
invoke.py crashes with the complaint that it can't find ldm.simplet2i.py#
Or it complains that function is being passed incorrect parameters.
SOLUTION
Reinstall the stable diffusion modules. Enter the stable-diffusion directory
and give the command pip install -e .
Missing modules#
invoke.py dies, complaining of various missing modules, none of which starts
with ldm.
SOLUTION
From within the InvokeAI directory, run conda env update This is also
frequently the solution to complaints about an unknown function in a module.
How can I try new features#
There's a feature or bugfix in the Stable Diffusion GitHub that you want to try out.
SOLUTIONS
Main Branch#
If the fix/feature is on the main branch, enter the stable-diffusion directory
and do a git pull.
Usually this will be sufficient, but if you start to see errors about missing or
incorrect modules, use the command pip install -e . and/or conda env update
(These commands won't break anything.)
pip install -e . and/or conda env update -f environment.yaml
(These commands won't break anything.)
Sub Branch#
If the feature/fix is on a branch (e.g. "foo-bugfix"), the recipe is similar,
but do a git pull <name of branch>.
Not Committed#
If the feature/fix is in a pull request that has not yet been made part of the main branch or a feature/bugfix branch, then from the page for the desired pull request, look for the line at the top that reads "xxxx wants to merge xx commits into lstein:main from YYYYYY". Copy the URL in YYYY. It should have the format
https://github.com/<name of contributor>/stable-diffusion/tree/<name of branch>
Then go to the directory above stable-diffusion and rename the directory to "stable-diffusion.lstein", "stable-diffusion.old", or anything else. You can then git clone the branch that contains the pull request:
git clone https://github.com/<name of contributor>/stable-diffusion/tree/<name of branch>
You will need to go through the install procedure again, but it should be fast because all the dependencies are already loaded.
CUDA out of memory#
Image generation crashed with CUDA out of memory error after successful sampling.
SOLUTION
Try to run script with option --free_gpu_mem This will free memory before
image decoding step.
Created: September 11, 2022