Refactor invoke (#405)
Fixes a problem with cross attention class missing from diffusers
models are now taken from the huggingFace cache.
50eb02f68b
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AbdBarho
GitHub
parent
555c26b7ce
commit
10c16e1971
@ -43,10 +43,10 @@ services:
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<<: *base_service
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profiles: ["invoke"]
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build: ./services/invoke/
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image: sd-invoke:26
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image: sd-invoke:27
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environment:
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- PRELOAD=true
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- CLI_ARGS=
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- CLI_ARGS=--no-nsfw_checker --no-safety_checker --xformers
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sygil: &sygil
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@ -11,53 +11,48 @@ ENV DEBIAN_FRONTEND=noninteractive PIP_EXISTS_ACTION=w PIP_PREFER_BINARY=1
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RUN --mount=type=cache,target=/root/.cache/pip pip install torch==1.13.1+cu117 torchvision --extra-index-url https://download.pytorch.org/whl/cu117
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RUN apt-get update && apt-get install git -y && apt-get clean
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RUN git clone https://github.com/invoke-ai/InvokeAI.git /stable-diffusion
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WORKDIR /stable-diffusion
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RUN --mount=type=cache,target=/root/.cache/pip \
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git reset --hard f232068ab89bd80e4f5f3133dcdb62ea78f1d0f7 && \
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git config --global http.postBuffer 1048576000 && \
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egrep -v '^-e .' environments-and-requirements/requirements-lin-cuda.txt > req.txt && \
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pip install -r req.txt && \
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rm req.txt
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# patch match:
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# https://github.com/invoke-ai/InvokeAI/blob/main/docs/installation/INSTALL_PATCHMATCH.md
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RUN \
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RUN --mount=type=cache,target=/var/cache/apt \
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apt-get update && \
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# apt-get install build-essential python3-opencv libopencv-dev -y && \
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apt-get install make g++ libopencv-dev -y && \
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apt-get install make g++ git libopencv-dev -y && \
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apt-get clean && \
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cd /usr/lib/x86_64-linux-gnu/pkgconfig/ && \
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ln -sf opencv4.pc opencv.pc
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ARG BRANCH=main SHA=6e0c6d9cc9f6bdbdefc4b9e94bc1ccde1b04aa42
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ENV ROOT=/InvokeAI
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RUN git clone https://github.com/invoke-ai/InvokeAI.git ${ROOT}
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WORKDIR ${ROOT}
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RUN --mount=type=cache,target=/root/.cache/pip \
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git reset --hard 4463124bddd221c333d4c70e73aa2949ad35453d && \
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pip install .
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ARG BRANCH=main SHA=50eb02f68be912276a9c106d5e8038a5671a0386
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RUN --mount=type=cache,target=/root/.cache/pip \
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git fetch && \
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git reset --hard && \
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git checkout ${BRANCH} && \
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git reset --hard ${SHA} && \
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pip install .
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pip install -U .
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RUN --mount=type=cache,target=/root/.cache/pip \
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--mount=type=bind,from=xformers,source=/wheel.whl,target=/xformers-0.0.15-cp310-cp310-linux_x86_64.whl \
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pip install -U opencv-python-headless huggingface_hub triton /xformers-0.0.15-cp310-cp310-linux_x86_64.whl && \
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--mount=type=bind,from=xformers,source=/wheel.whl,target=/xformers-0.0.17-cp310-cp310-linux_x86_64.whl \
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pip install -U opencv-python-headless triton /xformers-0.0.17-cp310-cp310-linux_x86_64.whl && \
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python3 -c "from patchmatch import patch_match"
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RUN touch invokeai.init
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COPY . /docker/
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ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
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ENV NVIDIA_VISIBLE_DEVICES=all
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ENV PYTHONUNBUFFERED=1 ROOT=/stable-diffusion PYTHONPATH="${PYTHONPATH}:${ROOT}" PRELOAD=false CLI_ARGS="" HF_HOME=/root/.cache/huggingface
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ENV PYTHONUNBUFFERED=1 PRELOAD=false HF_HOME=/root/.cache/huggingface CONFIG_DIR=/data/config/invoke CLI_ARGS=""
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EXPOSE 7860
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ENTRYPOINT ["/docker/entrypoint.sh"]
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CMD invokeai --web --host 0.0.0.0 --port 7860 --config /docker/models.yaml --root_dir ${ROOT} --outdir /output/invoke ${CLI_ARGS}
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CMD invokeai --web --host 0.0.0.0 --port 7860 --root_dir ${ROOT} --config ${CONFIG_DIR}/models.yaml --outdir /output/invoke ${CLI_ARGS}
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# TODO: make sure the config is persisted between sessions
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@ -4,25 +4,25 @@ set -Eeuo pipefail
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declare -A MOUNTS
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mkdir -p ${CONFIG_DIR}
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# cache
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MOUNTS["/root/.cache"]=/data/.cache/
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# this is really just a hack to avoid migrations
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rm -rf ${HF_HOME}/diffusers
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# ui specific
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MOUNTS["${ROOT}/models/codeformer"]=/data/Codeformer/
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MOUNTS["${ROOT}/models/gfpgan/GFPGANv1.4.pth"]=/data/GFPGAN/GFPGANv1.4.pth
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MOUNTS["${ROOT}/models/gfpgan/weights"]=/data/.cache/
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MOUNTS["${ROOT}/models/gfpgan/weights"]=/data/GFPGAN/
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MOUNTS["${ROOT}/models/realesrgan"]=/data/RealESRGAN/
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MOUNTS["${ROOT}/models/bert-base-uncased"]=/data/.cache/huggingface/transformers/
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MOUNTS["${ROOT}/models/openai/clip-vit-large-patch14"]=/data/.cache/huggingface/transformers/
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MOUNTS["${ROOT}/models/CompVis/stable-diffusion-safety-checker"]=/data/.cache/huggingface/transformers/
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MOUNTS["${ROOT}/models/ldm"]=/data/.cache/invoke/ldm/
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MOUNTS["${ROOT}/embeddings"]=/data/embeddings/
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# hacks
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MOUNTS["${ROOT}/models/clipseg"]=/data/.cache/invoke/clipseg/
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for to_path in "${!MOUNTS[@]}"; do
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set -Eeuo pipefail
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@ -40,7 +40,8 @@ done
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if "${PRELOAD}" == "true"; then
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set -Eeuo pipefail
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invokeai-configure --skip-sd-weights --root ${ROOT} --yes
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invokeai-configure --root ${ROOT} --yes
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cp ${ROOT}/configs/models.yaml ${CONFIG_DIR}/models.yaml
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fi
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exec "$@"
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@ -1,23 +0,0 @@
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# This file describes the alternative machine learning models
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# available to InvokeAI script.
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#
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# To add a new model, follow the examples below. Each
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# model requires a model config file, a weights file,
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# and the width and height of the images it
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# was trained on.
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stable-diffusion-1.5:
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description: Stable Diffusion version 1.5
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weights: /data/StableDiffusion/v1-5-pruned-emaonly.ckpt
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vae: /data/VAE/vae-ft-mse-840000-ema-pruned.ckpt
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config: ./invokeai/configs/stable-diffusion/v1-inference.yaml
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width: 512
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height: 512
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default: true
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inpainting-1.5:
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description: RunwayML SD 1.5 model optimized for inpainting
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weights: /data/StableDiffusion/sd-v1-5-inpainting.ckpt
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vae: /data/VAE/vae-ft-mse-840000-ema-pruned.ckpt
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config: ./invokeai/configs/stable-diffusion/v1-inpainting-inference.yaml
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width: 512
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height: 512
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default: false
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