Refactor invoke (#405)

Fixes a problem with cross attention class missing from diffusers


models are now taken from the huggingFace cache.


https://github.com/invoke-ai/InvokeAI/commit/50eb02f68be912276a9c106d5e8038a5671a0386

docker-compose.yml

@@ -43,10 +43,10 @@ services:
     <<: *base_service
     profiles: ["invoke"]
     build: ./services/invoke/
-    image: sd-invoke:26
+    image: sd-invoke:27
     environment:
       - PRELOAD=true
-      - CLI_ARGS=
+      - CLI_ARGS=--no-nsfw_checker --no-safety_checker --xformers
 
 
   sygil: &sygil

services/invoke/Dockerfile

@@ -11,53 +11,48 @@ ENV DEBIAN_FRONTEND=noninteractive PIP_EXISTS_ACTION=w  PIP_PREFER_BINARY=1
 
 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
 
-RUN apt-get update && apt-get install git -y && apt-get clean
-
-RUN git clone https://github.com/invoke-ai/InvokeAI.git /stable-diffusion
-
-WORKDIR /stable-diffusion
-
-RUN --mount=type=cache,target=/root/.cache/pip \
-  git reset --hard f232068ab89bd80e4f5f3133dcdb62ea78f1d0f7 && \
-  git config --global http.postBuffer 1048576000 && \
-  egrep -v '^-e .' environments-and-requirements/requirements-lin-cuda.txt > req.txt && \
-  pip install -r req.txt && \
-  rm req.txt
-
 
 # patch match:
 # https://github.com/invoke-ai/InvokeAI/blob/main/docs/installation/INSTALL_PATCHMATCH.md
-RUN \
+RUN --mount=type=cache,target=/var/cache/apt \
   apt-get update && \
-  # apt-get install build-essential python3-opencv libopencv-dev -y && \
-  apt-get install make g++ libopencv-dev -y && \
+  apt-get install make g++ git libopencv-dev -y && \
   apt-get clean && \
   cd /usr/lib/x86_64-linux-gnu/pkgconfig/ && \
   ln -sf opencv4.pc opencv.pc
 
 
-ARG BRANCH=main SHA=6e0c6d9cc9f6bdbdefc4b9e94bc1ccde1b04aa42
+
+ENV ROOT=/InvokeAI
+RUN git clone https://github.com/invoke-ai/InvokeAI.git ${ROOT}
+WORKDIR ${ROOT}
+
+RUN --mount=type=cache,target=/root/.cache/pip \
+  git reset --hard 4463124bddd221c333d4c70e73aa2949ad35453d && \
+  pip install .
+
+
+ARG BRANCH=main SHA=50eb02f68be912276a9c106d5e8038a5671a0386
 RUN --mount=type=cache,target=/root/.cache/pip \
   git fetch && \
   git reset --hard && \
   git checkout ${BRANCH} && \
   git reset --hard ${SHA} && \
-  pip install .
-
+  pip install -U .
 
 RUN --mount=type=cache,target=/root/.cache/pip \
-  --mount=type=bind,from=xformers,source=/wheel.whl,target=/xformers-0.0.15-cp310-cp310-linux_x86_64.whl \
-  pip install -U opencv-python-headless huggingface_hub triton /xformers-0.0.15-cp310-cp310-linux_x86_64.whl && \
+  --mount=type=bind,from=xformers,source=/wheel.whl,target=/xformers-0.0.17-cp310-cp310-linux_x86_64.whl \
+  pip install -U opencv-python-headless triton /xformers-0.0.17-cp310-cp310-linux_x86_64.whl && \
   python3 -c "from patchmatch import patch_match"
 
 
-RUN touch invokeai.init
 COPY . /docker/
 
 ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
 ENV NVIDIA_VISIBLE_DEVICES=all
-ENV PYTHONUNBUFFERED=1 ROOT=/stable-diffusion PYTHONPATH="${PYTHONPATH}:${ROOT}" PRELOAD=false CLI_ARGS="" HF_HOME=/root/.cache/huggingface
+ENV PYTHONUNBUFFERED=1 PRELOAD=false HF_HOME=/root/.cache/huggingface CONFIG_DIR=/data/config/invoke CLI_ARGS=""
 EXPOSE 7860
 
 ENTRYPOINT ["/docker/entrypoint.sh"]
-CMD invokeai --web --host 0.0.0.0 --port 7860 --config /docker/models.yaml --root_dir ${ROOT} --outdir /output/invoke ${CLI_ARGS}
+CMD invokeai --web --host 0.0.0.0 --port 7860 --root_dir ${ROOT} --config ${CONFIG_DIR}/models.yaml --outdir /output/invoke ${CLI_ARGS}
+# TODO: make sure the config is persisted between sessions

services/invoke/entrypoint.sh

@@ -4,25 +4,25 @@ set -Eeuo pipefail
 
 declare -A MOUNTS
 
+mkdir -p ${CONFIG_DIR}
+
 # cache
 MOUNTS["/root/.cache"]=/data/.cache/
 
+# this is really just a hack to avoid migrations
+rm -rf ${HF_HOME}/diffusers
+
 # ui specific
 MOUNTS["${ROOT}/models/codeformer"]=/data/Codeformer/
-
 MOUNTS["${ROOT}/models/gfpgan/GFPGANv1.4.pth"]=/data/GFPGAN/GFPGANv1.4.pth
-MOUNTS["${ROOT}/models/gfpgan/weights"]=/data/.cache/
-
+MOUNTS["${ROOT}/models/gfpgan/weights"]=/data/GFPGAN/
 MOUNTS["${ROOT}/models/realesrgan"]=/data/RealESRGAN/
 
-MOUNTS["${ROOT}/models/bert-base-uncased"]=/data/.cache/huggingface/transformers/
-MOUNTS["${ROOT}/models/openai/clip-vit-large-patch14"]=/data/.cache/huggingface/transformers/
-MOUNTS["${ROOT}/models/CompVis/stable-diffusion-safety-checker"]=/data/.cache/huggingface/transformers/
+MOUNTS["${ROOT}/models/ldm"]=/data/.cache/invoke/ldm/
 
 MOUNTS["${ROOT}/embeddings"]=/data/embeddings/
 
 # hacks
-MOUNTS["${ROOT}/models/clipseg"]=/data/.cache/invoke/clipseg/
 
 for to_path in "${!MOUNTS[@]}"; do
   set -Eeuo pipefail
@@ -40,7 +40,8 @@ done
 
 if "${PRELOAD}" == "true"; then
   set -Eeuo pipefail
-  invokeai-configure --skip-sd-weights --root ${ROOT} --yes
+  invokeai-configure --root ${ROOT} --yes
+  cp ${ROOT}/configs/models.yaml ${CONFIG_DIR}/models.yaml
 fi
 
 exec "$@"

services/invoke/models.yaml

@@ -1,23 +0,0 @@
-# This file describes the alternative machine learning models
-# available to InvokeAI script.
-#
-# To add a new model, follow the examples below. Each
-# model requires a model config file, a weights file,
-# and the width and height of the images it
-# was trained on.
-stable-diffusion-1.5:
-  description: Stable Diffusion version 1.5
-  weights: /data/StableDiffusion/v1-5-pruned-emaonly.ckpt
-  vae: /data/VAE/vae-ft-mse-840000-ema-pruned.ckpt
-  config: ./invokeai/configs/stable-diffusion/v1-inference.yaml
-  width: 512
-  height: 512
-  default: true
-inpainting-1.5:
-  description: RunwayML SD 1.5 model optimized for inpainting
-  weights: /data/StableDiffusion/sd-v1-5-inpainting.ckpt
-  vae: /data/VAE/vae-ft-mse-840000-ema-pruned.ckpt
-  config: ./invokeai/configs/stable-diffusion/v1-inpainting-inference.yaml
-  width: 512
-  height: 512
-  default: false