我对 Docker 和容器化还比较陌生。我想要减小在生产环境中 my_proj Docker 容器的大小。
我更喜欢通过 Poetry 安装软件包和管理依赖。
如何在 Dockerfile 中指定使用只支持 CPU 的 PyTorch？
如果要在 bash 终端上执行此操作，可以输入以下命令：
poetry add pytorch-cpu torchvision-cpu -c pytorch
（或者conda install...）
我现有的Dockerfile：
FROM python:3.7-slim as base
RUN apt-get update -y \
&& apt-get -y --no-install-recommends install curl wget\
&& rm -rf /var/lib/apt/lists/*
ENV ROOT /home/worker/python/my_proj
WORKDIR $ROOT
ARG ATLASSIAN_TOKEN
ARG POETRY_HTTP_BASIC_AZURE_PASSWORD
ARG ACCESS_KEY
ENV AWS_ACCESS_KEY_ID=$ACCESS_KEY
ARG SECRET_KEY
ENV AWS_SECRET_ACCESS_KEY=$SECRET_KEY
ARG REPO
ENV REPO_URL=$REPO
ENV PYPIRC_PATH=$ROOT/.pypirc
ENV \
PYTHONFAULTHANDLER=1 \
POETRY_VERSION=1.1.4 \
POETRY_HOME=/etc/poetry \
XDG_CACHE_HOME=/home/worker/.cache \
POETRY_VIRTUALENVS_IN_PROJECT=true \
MPLCONFIGDIR=/home/worker/matplotlib \
PATH=/home/worker/python/my_proj/.venv/bin:/usr/local/bin:/etc/poetry/bin:$PATH
ADD https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py ./
RUN python get-poetry.py && chmod +x /etc/poetry/bin/poetry
RUN --mount=type=cache,target=/root/.cache pip install twine keyring artifacts-keyring
RUN --mount=type=cache,target=/root/.cache apt update && apt install gcc -y
FROM base as ws
ARG WS_APIKEY
ARG WS_PROJECTVERSION=
ARG WS_PROJECTNAME=workers-python-my_proj
ARG WS_PRODUCTNAME=HALO
COPY --chown=worker:worker . .
RUN --mount=type=cache,uid=1000,target=/home/worker/.cache poetry install --no-dev
COPY --from=openjdk:15-slim-buster /usr/local/openjdk-15 /usr/local/openjdk-15
ENV JAVA_HOME /usr/local/openjdk-15
ENV PATH $JAVA_HOME/bin:$PATH
RUN --mount=type=cache,uid=1000,target=/home/worker/.cache ./wss_agent.sh
FROM base as test
COPY . .
RUN poetry config experimental.new-installer false
RUN poetry install
RUN cd my_proj && poetry run invoke deployconfluence_server_pass=$ATLASSIAN_TOKEN
FROM base as package
COPY . .
RUN poetry build
RUN python -m pip install --upgrade pip && \
pip install twine keyring artifacts-keyring && \
twine upload -r $REPO_URL --config-file $PYPIRC_PATH dist/* --skip-existing
FROM base as build
COPY . .
RUN poetry config experimental.new-installer false
RUN poetry install --no-dev
RUN pip3 --no-cache-dir install --upgrade awscli
RUN aws s3 cp s3://....tar.gz $ROOT/my_proj # censored url
RUN mkdir $ROOT/my_proj/bert-base-cased && cd $ROOT/my_proj/bert-base-cased && \
wget https://huggingface.co/bert-base-cased/resolve/main/config.json && \
wget https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json && \
wget https://huggingface.co/bert-base-cased/resolve/main/tokenizer_config.json
FROM python:3.7-slim as production
ENV ROOT=/home/worker/python/my_proj \
VIRTUAL_ENV=/home/worker/python/my_proj/.venv\
PATH=/home/worker/python/my_proj/.venv/bin:/home/worker/python/my_proj:$PATH
COPY --from=build /home/worker/python/my_proj/pyproject.toml /home/worker/python/
COPY --from=build /home/worker/python/my_proj/.venv /home/worker/python/my_proj/.venv
COPY --from=build /home/worker/python/my_proj/my_proj /home/worker/python/my_proj
WORKDIR $ROOT
ENV PYTHONPATH=$ROOT:/home/worker/python/
ENTRYPOINT [ "primary_worker", "--mongo" ]
Dockerfile？在隔离的环境中，比如在我的本地机器上或者在一个网站上？ - user16341274