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.
QUESTION#
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}
QUESTION#
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 .
QUESTION#
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.
QUESTION#
There's a feature or bugfix in the Stable Diffusion GitHub that you want to try out.
SOLUTION#
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.
QUESTION#
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