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update to python 3.7 · tieonlinux/docker-python@a72c378 · GitHub

/ docker-python Public
forked from Kaggle/docker-python

Commit a72c378

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rosbo
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update to python 3.7
1 parent 7fa5016 commit a72c378

3 files changed

Lines changed: 21 additions & 24 deletions

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‎Dockerfile‎

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@@ -21,11 +21,6 @@ RUN sed -i "s/httpredir.debian.org/debian.uchicago.edu/" /etc/apt/sources.list &
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apt-get -y install cmake && \
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/tmp/clean-layer.sh
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# Tensorflow doesn't support python 3.7 yet. See https://github.com/tensorflow/tensorflow/issues/20517
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# Fix to install Tensorflow: Downgrade python 3.7->3.6.6.
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RUN conda install -y python=3.6.6 && \
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/tmp/clean-layer.sh
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# The anaconda base image includes outdated versions of these packages. Update them to include the latest version.
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RUN pip install --upgrade seaborn python-dateutil dask && \
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pip install pyyaml joblib pytagcloud husl geopy ml_metrics mne pyshp && \

‎gpu.Dockerfile‎

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@@ -1,7 +1,7 @@
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ARG BASE_TAG=staging
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FROM nvidia/cuda:9.2-cudnn7-devel-ubuntu16.04 AS nvidia
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FROM gcr.io/kaggle-images/python-tensorflow-whl:1.12.0-py36 as tensorflow_whl
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FROM gcr.io/kaggle-images/python-tensorflow-whl:1.13.1-py36 as tensorflow_whl
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FROM gcr.io/kaggle-images/python:${BASE_TAG}
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ADD clean-layer.sh /tmp/clean-layer.sh
@@ -13,8 +13,8 @@ COPY --from=nvidia /etc/apt/trusted.gpg /etc/apt/trusted.gpg.d/cuda.gpg
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# Ensure the cuda libraries are compatible with the custom Tensorflow wheels.
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# TODO(b/120050292): Use templating to keep in sync or COPY installed binaries from it.
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ENV CUDA_VERSION=9.2.148
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ENV CUDA_PKG_VERSION=9-2=$CUDA_VERSION-1
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ENV CUDA_VERSION=10.1.105
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ENV CUDA_PKG_VERSION=10-1=$CUDA_VERSION-1
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LABEL com.nvidia.volumes.needed="nvidia_driver"
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LABEL com.nvidia.cuda.version="${CUDA_VERSION}"
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ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
@@ -26,7 +26,7 @@ ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
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ENV LD_LIBRARY_PATH="/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/lib64/stubs"
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ENV NVIDIA_VISIBLE_DEVICES=all
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ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
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ENV NVIDIA_REQUIRE_CUDA="cuda>=9.2"
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ENV NVIDIA_REQUIRE_CUDA="cuda>=10.1"
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RUN apt-get update && apt-get install -y --no-install-recommends \
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cuda-cupti-$CUDA_PKG_VERSION \
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cuda-cudart-$CUDA_PKG_VERSION \
@@ -36,30 +36,33 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
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cuda-nvml-dev-$CUDA_PKG_VERSION \
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cuda-minimal-build-$CUDA_PKG_VERSION \
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cuda-command-line-tools-$CUDA_PKG_VERSION \
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libcudnn7=7.4.1.5-1+cuda9.2 \
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libcudnn7-dev=7.4.1.5-1+cuda9.2 \
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libnccl2=2.3.7-1+cuda9.2 \
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libnccl-dev=2.3.7-1+cuda9.2 && \
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ln -s /usr/local/cuda-9.2 /usr/local/cuda && \
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libcudnn7=7.5.0.56-1+cuda10.1 \
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libcudnn7-dev=7.5.0.56-1+cuda10.1 \
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libnccl2=2.4.2-1+cuda10.1 \
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libnccl-dev=2.4.2-1+cuda10.1 && \
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ln -s /usr/local/cuda-10.1 /usr/local/cuda && \
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ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 && \
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/tmp/clean-layer.sh
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# TODO(rosbo): given tha pytorch and mxnet and cupy don't have cuda 10.1 versions.
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# Consider installing cuda 10.0
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# Reinstall packages with a separate version for GPU support
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# Tensorflow
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COPY --from=tensorflow_whl /tmp/tensorflow_gpu/*.whl /tmp/tensorflow_gpu/
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RUN pip uninstall -y tensorflow && \
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pip install /tmp/tensorflow_gpu/tensorflow*.whl && \
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rm -rf /tmp/tensorflow_gpu && \
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conda uninstall -y pytorch-cpu torchvision-cpu && \
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conda install -y pytorch torchvision cudatoolkit=9.2 -c pytorch && \
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conda install -y pytorch torchvision cudatoolkit=10.0 -c pytorch && \
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pip uninstall -y mxnet && \
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# b/126259508 --no-deps prevents numpy from being downgraded.
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pip install --no-deps mxnet-cu92 && \
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pip install --no-deps mxnet-cu100 && \
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/tmp/clean-layer.sh
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# Install GPU-only packages
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RUN pip install pycuda && \
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pip install cupy-cuda92 && \
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pip install cupy-cuda100 && \
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pip install pynvrtc && \
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/tmp/clean-layer.sh
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‎tensorflow-whl/Dockerfile‎

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Original file line numberDiff line numberDiff line change
@@ -28,7 +28,7 @@ ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
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ENV LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/lib64/stubs"
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ENV NVIDIA_VISIBLE_DEVICES=all
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ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
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ENV NVIDIA_REQUIRE_CUDA="cuda>=9.0"
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ENV NVIDIA_REQUIRE_CUDA="cuda>=10.1"
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RUN apt-get update && apt-get install -y --no-install-recommends \
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cuda-cupti-$CUDA_PKG_VERSION \
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cuda-cudart-$CUDA_PKG_VERSION \
@@ -49,7 +49,7 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
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# Install bazel
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# Tensorflow 1.13 requires the Bazel 0.19.2: https://www.tensorflow.org/install/source
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ENV BAZEL_VERSION=0.19.2
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RUN apt-get update && apt-get install -y gnupg zip && \
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RUN apt-get install -y gnupg zip && \
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echo "deb http://ppa.launchpad.net/webupd8team/java/ubuntu precise main" | tee -a /etc/apt/sources.list && \
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echo "deb-src http://ppa.launchpad.net/webupd8team/java/ubuntu precise main" | tee -a /etc/apt/sources.list && \
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apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys --no-tty EEA14886 C857C906 2B90D010 && \
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dpkg -i bazel_*.deb && \
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rm bazel_*.deb
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# Tensorflow doesn't support python 3.7 yet. See https://github.com/tensorflow/tensorflow/issues/20517
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RUN conda install -y python=3.6.6
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# Fetch tensorflow
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# Fetch tensorflow & install dependencies.
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RUN cd /usr/local/src && \
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git clone https://github.com/tensorflow/tensorflow && \
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cd tensorflow && \
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git checkout r1.13
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git checkout r1.13 && \
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pip install keras_applications --no-deps && \
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pip install keras_preprocessing --no-deps
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# Create a tensorflow wheel for CPU
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RUN cd /usr/local/src/tensorflow && \

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