Merge 49da9c325a into 2307ff6746

.dockerignore

@@ -0,0 +1,6 @@
+__pycache__/
+*.py[cod]
+input
+models
+notebooks
+output

Dockerfile

@@ -0,0 +1,70 @@
+# 3.10.11-bullseye,  has python, git, but relatively small (<250MB)
+ARG BASE_IMAGE="python@sha256:88fb365ea5d52ec8f5799f40a4742b9fb3c91dac92f7048eabaae194a25ccc28"
+ARG GPU_MAKE="nvidia"
+ARG UID=1000
+ARG GID=1000
+
+FROM ${BASE_IMAGE}
+ARG GPU_MAKE
+ARG UID
+ARG GID
+
+SHELL [ "/bin/bash", "-uec"]
+RUN \
+  --mount=target=/var/lib/apt/lists,type=cache,sharing=locked \
+  --mount=target=/var/cache/apt,type=cache,sharing=locked \
+<<'EOF'
+  apt-get update
+  apt-get install -yq git-lfs
+  echo "comfyui" >> /etc/hostname
+EOF
+
+# run instructions as user
+USER ${UID}:${GID}
+# run python from future venv
+ENV PATH="/app/venv/bin:${PATH}"
+# copy context to obvious location
+COPY --chown=${UID}:${GID} ./ /app
+# create cache directory *with user permissions*
+WORKDIR /app/.cache
+# default to app directory
+WORKDIR /app
+# set pip cache location
+ENV XDG_CACHE_HOME="/app/.cache/pip"
+# run with mounted cache
+RUN --mount=type=cache,target=/app/.cache,uid=${UID},gid=${GID} <<'EOF'
+  mkdir -p /app/.cache/transformers
+  # choose package index based on chosen hardware
+  if [ "${GPU_MAKE}" = "nvidia" ]; then
+    EXTRA_INDEX_URL="https://download.pytorch.org/whl/cu118"
+    EXTRAS="xformers"
+  elif [ "${GPU_MAKE}" = "amd" ]; then
+    EXTRA_INDEX_URL="https://download.pytorch.org/whl/rocm5.4.2"
+    EXTRAS=""
+  elif [ "${GPU_MAKE}" = "cpu" ]; then
+    EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
+    EXTRAS=""
+  else
+    echo "Unknown GPU_MAKE provided as docker build arg."
+    exit 2
+  fi
+  # create virtual environment to manage packages
+  python -m venv venv
+  # install framework packages
+  pip install \
+    --extra-index-url "${EXTRA_INDEX_URL}" \
+    install \
+    torch \
+    torchvision \
+    torchaudio \
+    ${EXTRAS}
+  pip install -r requirements.txt
+EOF
+
+# default environment variables
+ENV COMFYUI_ADDRESS=0.0.0.0
+ENV COMFYUI_PORT=8188
+ENV COMFYUI_EXTRA_ARGS=""
+ENV TRANSFORMERS_CACHE="/app/.cache/transformers"
+# default start command
+CMD bash -c "python -u main.py --listen ${COMFYUI_ADDRESS} --port ${COMFYUI_PORT} ${COMFYUI_EXTRA_ARGS}"

comfy/sd.py

@@ -111,7 +111,7 @@ class CLIP:
             model_management.load_models_gpu([self.patcher], force_full_load=True)
         self.layer_idx = None
         self.use_clip_schedule = False
-        logging.info("CLIP model load device: {}, offload device: {}, current: {}, dtype: {}".format(load_device, offload_device, params['device'], dtype))
+        logging.info("CLIP/text encoder model load device: {}, offload device: {}, current: {}, dtype: {}".format(load_device, offload_device, params['device'], dtype))
 
     def clone(self):
         n = CLIP(no_init=True)
@@ -898,7 +898,7 @@ def load_state_dict_guess_config(sd, output_vae=True, output_clip=True, output_c
     if output_model:
         model_patcher = comfy.model_patcher.ModelPatcher(model, load_device=load_device, offload_device=model_management.unet_offload_device())
         if inital_load_device != torch.device("cpu"):
-            logging.info("loaded straight to GPU")
+            logging.info("loaded diffusion model directly to GPU")
             model_management.load_models_gpu([model_patcher], force_full_load=True)
 
     return (model_patcher, clip, vae, clipvision)

docker-compose.yaml

@@ -0,0 +1,20 @@
+version: "3.9"
+
+services:
+  comfyui:
+    user: "1000:1000"
+    build: .
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    ports:
+      - "8188:8188"
+    volumes:
+      - "./models:/app/models"
+      - "./input:/app/input"
+      - "./temp:/app/output/temp"
+      - "./output:/app/output"

ruff.toml

@@ -4,7 +4,8 @@ lint.ignore = ["ALL"]
 # Enable specific rules
 lint.select = [
     "S307",  # suspicious-eval-usage
-    "T201",  # print-usage
+    "S102", # exec
+    "T",  # print-usage
     "W",
     # The "F" series in Ruff stands for "Pyflakes" rules, which catch various Python syntax errors and undefined names.
     # See all rules here: https://docs.astral.sh/ruff/rules/#pyflakes-f