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