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Eric Khun
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# Apple Silicon Mac Users
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# macOS Instructions
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Several people have gotten Stable Diffusion to work on Apple Silicon
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Macs using Anaconda, miniforge, etc. I've gathered up most of their instructions and
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put them in this fork (and readme). Things have moved really fast and so these
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instructions change often. Hopefully things will settle down a little.
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Requirements
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There's several places where people are discussing Apple
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MPS functionality: [the original CompVis
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issue](https://github.com/CompVis/stable-diffusion/issues/25), and generally on
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[lstein's fork](https://github.com/lstein/stable-diffusion/).
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- macOS 12.3 Monterey or later
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- Python
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- Patience
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- Apple Silicon*
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You have to have macOS 12.3 Monterey or later. Anything earlier than that won't work.
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*I haven't tested any of this on Intel Macs but I have read that one person got
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it to work, so Apple Silicon might not be requried.
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Tested on a 2022 Macbook M2 Air with 10-core GPU and 24 GB unified memory.
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Things have moved really fast and so these instructions change often and are
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often out-of-date. One of the problems is that there are so many different ways to
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run this.
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How to:
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We are trying to build a testing setup so that when we make changes it doesn't
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always break.
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How to (this hasn't been 100% tested yet):
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First get the weights checkpoint download started - it's big:
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1. Sign up at https://huggingface.co
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2. Go to the [Stable diffusion diffusion model page](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original)
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3. Accept the terms and click Access Repository:
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4. Download [sd-v1-4.ckpt (4.27 GB)](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/blob/main/sd-v1-4.ckpt) and note where you have saved it (probably the Downloads folder)
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While that is downloading, open Terminal and run the following commands one at a time.
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```
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# install brew (and Xcode command line tools):
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/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
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# install python 3, git, cmake, protobuf:
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brew install cmake protobuf rust
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# install miniconda (M1 arm64 version):
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curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh -o Miniconda3-latest-MacOSX-arm64.sh
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/bin/bash Miniconda3-latest-MacOSX-arm64.sh
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# clone the repo
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git clone https://github.com/lstein/stable-diffusion.git
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cd stable-diffusion
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#
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# wait until the checkpoint file has downloaded, then proceed
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#
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# create symlink to checkpoint
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mkdir -p models/ldm/stable-diffusion-v1/
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# You will have to signup then download this model: https://huggingface.co/CompVis/stable-diffusion-v-1-4-original
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PATH_TO_CKPT="$HOME/Documents/stable-diffusion-v-1-4-original" # or wherever yours is.
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PATH_TO_CKPT="$HOME/Downloads" # or wherever you saved sd-v1-4.ckpt
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ln -s "$PATH_TO_CKPT/sd-v1-4.ckpt" models/ldm/stable-diffusion-v1/model.ckpt
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CONDA_SUBDIR=osx-arm64 conda env create -f environment-mac.yaml
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# install packages
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PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-arm64 conda env create -f environment-mac.yaml
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conda activate ldm
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# only need to do this once
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python scripts/preload_models.py
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# run SD!
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python scripts/dream.py --full_precision # half-precision requires autocast and won't work
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```
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After you follow all the instructions and run dream.py you might get several errors. Here's the errors I've seen and found solutions for.
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The original scripts should work as well.
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```
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python scripts/orig_scripts/txt2img.py --prompt "a photograph of an astronaut riding a horse" --plms
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```
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Note, `export PIP_EXISTS_ACTION=w` is a precaution to fix `conda env create -f environment-mac.yaml`
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never finishing in some situations. So it isn't required but wont hurt.
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After you follow all the instructions and run dream.py you might get several
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errors. Here's the errors I've seen and found solutions for.
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### Is it slow?
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@ -53,27 +96,37 @@ One debugging step is to update to the latest version of PyTorch nightly.
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conda install pytorch torchvision torchaudio -c pytorch-nightly
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Or you can clean everything up.
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If `conda env create -f environment-mac.yaml` takes forever run this.
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git clean -f
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And run this.
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conda clean --yes --all
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Or you can reset Anaconda.
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Or you could reset Anaconda.
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conda update --force-reinstall -y -n base -c defaults conda
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### "No module named cv2" (or some other module)
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### "No module named cv2", torch, 'ldm', 'transformers', 'taming', etc.
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Did you remember to `conda activate ldm`? If your terminal prompt
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There are several causes of these errors.
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First, did you remember to `conda activate ldm`? If your terminal prompt
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begins with "(ldm)" then you activated it. If it begins with "(base)"
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or something else you haven't.
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If it says you're missing taming you need to rebuild your virtual
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Second, you might've run `./scripts/preload_models.py` or `./scripts/dream.py`
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instead of `python ./scripts/preload_models.py` or `python ./scripts/dream.py`.
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The cause of this error is long so it's below.
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Third, if it says you're missing taming you need to rebuild your virtual
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environment.
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conda env remove -n ldm
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conda env create -f environment-mac.yaml
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If you have activated the ldm virtual environment and tried rebuilding
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Fourth, If you have activated the ldm virtual environment and tried rebuilding
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it, maybe the problem could be that I have something installed that
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you don't and you'll just need to manually install it. Make sure you
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activate the virtual environment so it installs there instead of
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@ -84,6 +137,56 @@ globally.
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You might also need to install Rust (I mention this again below).
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### How many snakes are living in your computer?
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Here's the reason why you have to specify which python to use.
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There are several versions of python on macOS and the computer is
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picking the wrong one. More specifically, preload_models.py and dream.py says to
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find the first `python3` in the path environment variable. You can see which one
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it is picking with `which python3`. These are the mostly likely paths you'll see.
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% which python3
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/usr/bin/python3
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The above path is part of the OS. However, that path is a stub that asks you if
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you want to install Xcode. If you have Xcode installed already,
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/usr/bin/python3 will execute /Library/Developer/CommandLineTools/usr/bin/python3 or
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/Applications/Xcode.app/Contents/Developer/usr/bin/python3 (depending on which
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Xcode you've selected with `xcode-select`).
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% which python3
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/opt/homebrew/bin/python3
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If you installed python3 with Homebrew and you've modified your path to search
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for Homebrew binaries before system ones, you'll see the above path.
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% which python
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/opt/anaconda3/bin/python
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If you drop the "3" you get an entirely different python. Note: starting in
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macOS 12.3, /usr/bin/python no longer exists (it was python 2 anyway).
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If you have Anaconda installed, this is what you'll see. There is a
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/opt/anaconda3/bin/python3 also.
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(ldm) % which python
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/Users/name/miniforge3/envs/ldm/bin/python
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This is what you'll see if you have miniforge and you've correctly activated
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the ldm environment. This is the goal.
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It's all a mess and you should know [how to modify the path environment variable](https://support.apple.com/guide/terminal/use-environment-variables-apd382cc5fa-4f58-4449-b20a-41c53c006f8f/mac)
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if you want to fix it. Here's a brief hint of all the ways you can modify it
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(don't really have the time to explain it all here).
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- ~/.zshrc
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- ~/.bash_profile
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- ~/.bashrc
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- /etc/paths.d
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- /etc/path
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Which one you use will depend on what you have installed except putting a file
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in /etc/paths.d is what I prefer to do.
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### Debugging?
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@ -208,7 +311,7 @@ change instead. This is a 32-bit vs 16-bit problem.
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What? Intel? On an Apple Silicon?
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Intel MKL FATAL ERROR: This system does not meet the minimum requirements for use of the Intel(R) Math Kernel Library.
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The processor must support the Intel(R) Supplemental Streaming SIMD Extensions 3 (Intel(R) SSSE3) instructions.██████████████| 50/50 [02:25<00:00, 2.53s/it]
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The processor must support the Intel(R) Supplemental Streaming SIMD Extensions 3 (Intel(R) SSSE3) instructions.
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The processor must support the Intel(R) Streaming SIMD Extensions 4.2 (Intel(R) SSE4.2) instructions.
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The processor must support the Intel(R) Advanced Vector Extensions (Intel(R) AVX) instructions.
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@ -280,7 +280,14 @@ class T2I:
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), 'can only work with strength in [0.0, 1.0]'
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width, height, _ = self._resolution_check(width, height, log=True)
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scope = autocast if self.precision == 'autocast' else nullcontext
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# TODO: - Check if this is still necessary to run on M1 devices.
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# - Move code into ldm.dream.devices to live alongside other
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# special-hardware casing code.
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if self.precision == 'autocast' and torch.cuda.is_available():
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scope = autocast
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else:
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scope = nullcontext
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if sampler_name and (sampler_name != self.sampler_name):
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self.sampler_name = sampler_name
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