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chore(docker): reduce size between docker builds #7571
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@@ -13,52 +13,62 @@ RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \ | |
git | ||
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# Install `uv` for package management | ||
COPY --from=ghcr.io/astral-sh/uv:0.5.5 /uv /uvx /bin/ | ||
COPY --from=ghcr.io/astral-sh/uv:0.5.21 /uv /uvx /bin/ | ||
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ENV VIRTUAL_ENV=/opt/venv | ||
ENV PATH="$VIRTUAL_ENV/bin:$PATH" | ||
ENV INVOKEAI_SRC=/opt/invokeai | ||
ENV PYTHON_VERSION=3.11 | ||
ENV UV_PYTHON=3.11 | ||
ENV UV_COMPILE_BYTECODE=1 | ||
ENV UV_LINK_MODE=copy | ||
ENV UV_INDEX="https://download.pytorch.org/whl/cu124" | ||
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ARG GPU_DRIVER=cuda | ||
ARG TARGETPLATFORM="linux/amd64" | ||
# unused but available | ||
ARG BUILDPLATFORM | ||
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# Switch to the `ubuntu` user to work around dependency issues with uv-installed python | ||
RUN mkdir -p ${VIRTUAL_ENV} && \ | ||
mkdir -p ${INVOKEAI_SRC} && \ | ||
RUN mkdir -p ${INVOKEAI_SRC} && \ | ||
chmod -R a+w /opt | ||
USER ubuntu | ||
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# Install python and create the venv | ||
RUN uv python install ${PYTHON_VERSION} && \ | ||
uv venv --relocatable --prompt "invoke" --python ${PYTHON_VERSION} ${VIRTUAL_ENV} | ||
# Install python | ||
RUN --mount=type=cache,target=/home/ubuntu/.cache/uv,uid=1000,gid=1000 \ | ||
uv python install ${PYTHON_VERSION} | ||
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WORKDIR ${INVOKEAI_SRC} | ||
COPY invokeai ./invokeai | ||
COPY pyproject.toml ./ | ||
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# Editable mode helps use the same image for development: | ||
# the local working copy can be bind-mounted into the image | ||
# at path defined by ${INVOKEAI_SRC} | ||
# Install project's dependencies as a separate layer so they aren't rebuilt every commit. | ||
# bind-mount instead of copy to defer adding sources to the image until next layer. | ||
# | ||
# NOTE: there are no pytorch builds for arm64 + cuda, only cpu | ||
# x86_64/CUDA is the default | ||
RUN --mount=type=cache,target=/home/ubuntu/.cache/uv,uid=1000,gid=1000 \ | ||
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \ | ||
--mount=type=bind,source=invokeai,target=invokeai \ | ||
if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \ | ||
UV_INDEX="https://download.pytorch.org/whl/cpu"; \ | ||
elif [ "$GPU_DRIVER" = "rocm" ]; then \ | ||
UV_INDEX="https://download.pytorch.org/whl/rocm6.1"; \ | ||
fi && \ | ||
uv sync --no-install-project | ||
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# Now that the bulk of the dependencies have been installed, copy in the project files that change more frequently. | ||
COPY invokeai invokeai | ||
COPY pyproject.toml . | ||
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RUN --mount=type=cache,target=/home/ubuntu/.cache/uv,uid=1000,gid=1000 \ | ||
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \ | ||
if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \ | ||
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \ | ||
UV_INDEX="https://download.pytorch.org/whl/cpu"; \ | ||
elif [ "$GPU_DRIVER" = "rocm" ]; then \ | ||
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm6.1"; \ | ||
else \ | ||
extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu124"; \ | ||
UV_INDEX="https://download.pytorch.org/whl/rocm6.1"; \ | ||
fi && \ | ||
uv pip install --python ${PYTHON_VERSION} $extra_index_url_arg -e "." | ||
uv sync | ||
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#### Build the Web UI ------------------------------------ | ||
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FROM node:20-slim AS web-builder | ||
FROM docker.io/node:20-slim AS web-builder | ||
ENV PNPM_HOME="/pnpm" | ||
ENV PATH="$PNPM_HOME:$PATH" | ||
RUN corepack use [email protected] | ||
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@@ -97,26 +107,24 @@ RUN apt update && apt install -y --no-install-recommends \ | |
apt-get clean && apt-get autoclean | ||
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ENV INVOKEAI_SRC=/opt/invokeai | ||
ENV VIRTUAL_ENV=/opt/venv | ||
ENV PYTHON_VERSION=3.11 | ||
ENV INVOKEAI_ROOT=/invokeai | ||
ENV INVOKEAI_HOST=0.0.0.0 | ||
ENV INVOKEAI_PORT=9090 | ||
ENV PATH="$VIRTUAL_ENV/bin:$INVOKEAI_SRC:$PATH" | ||
ENV PATH="$INVOKEAI_SRC/.venv/bin:$INVOKEAI_SRC:$PATH" | ||
ENV CONTAINER_UID=${CONTAINER_UID:-1000} | ||
ENV CONTAINER_GID=${CONTAINER_GID:-1000} | ||
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# Install `uv` for package management | ||
# and install python for the ubuntu user (expected to exist on ubuntu >=24.x) | ||
# this is too tiny to optimize with multi-stage builds, but maybe we'll come back to it | ||
COPY --from=ghcr.io/astral-sh/uv:0.5.5 /uv /uvx /bin/ | ||
COPY --from=ghcr.io/astral-sh/uv:0.5.21 /uv /uvx /bin/ | ||
USER ubuntu | ||
RUN uv python install ${PYTHON_VERSION} | ||
USER root | ||
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# --link requires buldkit w/ dockerfile syntax 1.4 | ||
COPY --link --from=builder ${INVOKEAI_SRC} ${INVOKEAI_SRC} | ||
COPY --link --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV} | ||
COPY --link --from=web-builder /build/dist ${INVOKEAI_SRC}/invokeai/frontend/web/dist | ||
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# Link amdgpu.ids for ROCm builds | ||
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As far as I can tell, CUDA builds of torch 2.4.1 have a dependency on triton, which has two consequences:
If we had an exact dependency on
torch==2.4.1+cu124
, uv's resolver would figure it out which version of triton works, and it would be fine.However, since the torch version is left ambiguous, it's possible for the resolver to decide that non-CUDA torch==2.4.1 is a better solution since that doesn't conflict with the latest version of xformers. 😖