mirror of
https://github.com/vale981/ray
synced 2025-03-06 10:31:39 -05:00
e109c13b83
In https://github.com/ray-project/ray/blob/ray-1.11.0/docker/ray-ml/Dockerfile, the order of pip install commands currently matters (potentially a lot). It would be good to run one big pip install command to avoid ending up with a broken env. Co-authored-by: Kai Fricke <krfricke@users.noreply.github.com>
45 lines
1.6 KiB
Docker
45 lines
1.6 KiB
Docker
ARG BASE_IMAGE
|
|
FROM rayproject/ray:nightly"$BASE_IMAGE"
|
|
ARG PYTHON_MINOR_VERSION=7
|
|
|
|
# We have to uninstall wrapt this way for Tensorflow compatibility
|
|
COPY requirements.txt ./
|
|
COPY requirements_dl.txt ./
|
|
COPY requirements_ml_docker.txt ./
|
|
COPY requirements_rllib.txt ./
|
|
COPY requirements_tune.txt ./requirements_tune.txt
|
|
COPY requirements_train.txt ./
|
|
COPY requirements_upstream.txt ./
|
|
|
|
RUN sudo apt-get update \
|
|
&& sudo apt-get install -y gcc \
|
|
cmake \
|
|
libgtk2.0-dev \
|
|
zlib1g-dev \
|
|
libgl1-mesa-dev \
|
|
unzip \
|
|
unrar \
|
|
&& $HOME/anaconda3/bin/pip --no-cache-dir install -U pip \
|
|
&& $HOME/anaconda3/bin/pip --no-cache-dir install -U \
|
|
-r requirements.txt \
|
|
-r requirements_rllib.txt \
|
|
-r requirements_train.txt \
|
|
-r requirements_tune.txt \
|
|
-r requirements_upstream.txt \
|
|
# explicitly install (overwrite) pytorch with CUDA support
|
|
&& $HOME/anaconda3/bin/pip --no-cache-dir install -U \
|
|
-r requirements_ml_docker.txt \
|
|
# Remove dataclasses & typing because they are included in Python > 3.6
|
|
&& if [ $(python -c 'import sys; print(sys.version_info.minor)') != "6" ]; then \
|
|
$HOME/anaconda3/bin/pip uninstall dataclasses typing -y; fi \
|
|
&& sudo rm \
|
|
requirements.txt \
|
|
requirements_ml_docker.txt \
|
|
requirements_tune.txt \
|
|
requirements_rllib.txt \
|
|
requirements_train.txt \
|
|
requirements_upstream.txt \
|
|
&& sudo apt-get clean
|
|
|
|
# Make sure tfp is installed correctly and matches tf version.
|
|
RUN python -c "import tensorflow_probability"
|