---
title: F.A.Q.
hide:
- toc
---
# :material-frequently-asked-questions: 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):
```bash
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:
```bash
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.