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Upgrade to CUDA 11.0 (#985) · HpcDataLab/docker-python@05cbde6 · GitHub

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

Commit 05cbde6

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rosbo
authored
Upgrade to CUDA 11.0 (Kaggle#985)
http://b/175341540
1 parent 08723a4 commit 05cbde6

2 files changed

Lines changed: 24 additions & 28 deletions

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‎Dockerfile‎

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,7 @@
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ARG BASE_TAG=m66
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ARG TENSORFLOW_VERSION=2.4.1
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FROM gcr.io/kaggle-images/python-tensorflow-whl:${TENSORFLOW_VERSION}-py37 as tensorflow_whl
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FROM gcr.io/kaggle-images/python-tensorflow-whl:${TENSORFLOW_VERSION}-py37-2 as tensorflow_whl
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FROM gcr.io/deeplearning-platform-release/base-cpu:${BASE_TAG}
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ADD clean-layer.sh /tmp/clean-layer.sh
@@ -81,7 +81,7 @@ RUN apt-get install -y libfreetype6-dev && \
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pip install wordcloud && \
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pip install xgboost && \
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# Pinned to match GPU version. Update version together.
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pip install lightgbm==3.1.1 && \
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pip install lightgbm==3.2.0 && \
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pip install pydot && \
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pip install keras && \
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pip install keras-tuner && \
@@ -406,8 +406,7 @@ RUN pip install flashtext && \
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pip install dlib && \
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pip install kaggle-environments && \
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pip install geopandas && \
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# b/175638062 remove pin once we update to cuDNN 8.x
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pip install nnabla==1.13.0 && \
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pip install nnabla && \
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pip install vowpalwabbit && \
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# papermill can replace nbconvert for executing notebooks
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pip install papermill && \

‎gpu.Dockerfile‎

Lines changed: 21 additions & 24 deletions
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@@ -1,7 +1,7 @@
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ARG BASE_TAG=staging
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FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04 AS nvidia
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FROM gcr.io/kaggle-images/python-tensorflow-whl:2.4.1-py37 as tensorflow_whl
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FROM nvidia/cuda:11.0-cudnn8-devel-ubuntu18.04 AS nvidia
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FROM gcr.io/kaggle-images/python-tensorflow-whl:2.4.1-py37-2 as tensorflow_whl
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FROM gcr.io/kaggle-images/python:${BASE_TAG}
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ADD clean-layer.sh /tmp/clean-layer.sh
@@ -15,11 +15,9 @@ RUN sed -i 's/deb https:\/\/developer.download.nvidia.com/deb http:\/\/developer
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# Ensure the cuda libraries are compatible with the custom Tensorflow wheels.
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# TODO(b/120050292): Use templating to keep in sync or COPY installed binaries from it.
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ENV CUDA_MAJOR_VERSION=10
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ENV CUDA_MINOR_VERSION=2
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ENV CUDA_PATCH_VERSION=89
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ENV CUDA_VERSION=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION.$CUDA_PATCH_VERSION
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ENV CUDA_PKG_VERSION=$CUDA_MAJOR_VERSION-$CUDA_MINOR_VERSION=$CUDA_VERSION-1
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ENV CUDA_MAJOR_VERSION=11
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ENV CUDA_MINOR_VERSION=0
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ENV CUDA_VERSION=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION
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LABEL com.nvidia.volumes.needed="nvidia_driver"
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LABEL com.nvidia.cuda.version="${CUDA_VERSION}"
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ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/bin:${PATH}
@@ -34,19 +32,19 @@ ENV NVIDIA_VISIBLE_DEVICES=all
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ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
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ENV NVIDIA_REQUIRE_CUDA="cuda>=$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION"
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RUN apt-get update && apt-get install -y --no-install-recommends \
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cuda-cupti-$CUDA_PKG_VERSION \
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cuda-cudart-$CUDA_PKG_VERSION \
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cuda-cudart-dev-$CUDA_PKG_VERSION \
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cuda-libraries-$CUDA_PKG_VERSION \
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cuda-libraries-dev-$CUDA_PKG_VERSION \
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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-$CUDA_PKG_VERSION \
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libcudnn7=7.6.5.32-1+cuda$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION \
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libcudnn7-dev=7.6.5.32-1+cuda$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION \
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libnccl2=2.5.6-1+cuda$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION \
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libnccl-dev=2.5.6-1+cuda$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION && \
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ln -s /usr/local/cuda-$CUDA_MAJOR_VERSION.$CUDA_MINOR_VERSION /usr/local/cuda && \
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cuda-cupti-$CUDA_VERSION \
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cuda-cudart-$CUDA_VERSION \
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cuda-cudart-dev-$CUDA_VERSION \
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cuda-libraries-$CUDA_VERSION \
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cuda-libraries-dev-$CUDA_VERSION \
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cuda-nvml-dev-$CUDA_VERSION \
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cuda-minimal-build-$CUDA_VERSION \
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cuda-command-line-tools-$CUDA_VERSION \
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libcudnn8=8.0.4.30-1+cuda$CUDA_VERSION \
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libcudnn8-dev=8.0.4.30-1+cuda$CUDA_VERSION \
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libnccl2=2.7.8-1+cuda$CUDA_VERSION \
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libnccl-dev=2.7.8-1+cuda$CUDA_VERSION && \
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ln -s /usr/local/cuda-$CUDA_VERSION /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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@@ -69,7 +67,7 @@ RUN pip uninstall -y lightgbm && \
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cd /usr/local/src && \
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git clone --recursive https://github.com/microsoft/LightGBM && \
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cd LightGBM && \
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git checkout tags/v3.1.1 && \
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git checkout tags/v3.2.0 && \
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mkdir build && cd build && \
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cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ .. && \
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make -j$(nproc) && \
@@ -80,7 +78,7 @@ RUN pip uninstall -y lightgbm && \
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/tmp/clean-layer.sh
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# Install JAX
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RUN pip install jax==0.2.6 jaxlib==0.1.57+cuda$CUDA_MAJOR_VERSION$CUDA_MINOR_VERSION -f https://storage.googleapis.com/jax-releases/jax_releases.html && \
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RUN pip install jax==0.2.12 jaxlib==0.1.64+cuda$CUDA_MAJOR_VERSION$CUDA_MINOR_VERSION -f https://storage.googleapis.com/jax-releases/jax_releases.html && \
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/tmp/clean-layer.sh
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# Reinstall packages with a separate version for GPU support.
@@ -102,8 +100,7 @@ RUN pip install /tmp/tfa_gpu/tensorflow*.whl && \
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RUN pip install pycuda && \
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pip install cupy-cuda$CUDA_MAJOR_VERSION$CUDA_MINOR_VERSION && \
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pip install pynvrtc && \
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# b/175638062 remove pin once we update to cuDNN 8.x
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pip install nnabla-ext-cuda$CUDA_MAJOR_VERSION$CUDA_MINOR_VERSION==1.13.0 && \
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pip install nnabla-ext-cuda$CUDA_MAJOR_VERSION$CUDA_MINOR_VERSION && \
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/tmp/clean-layer.sh
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109106
# Re-add TensorBoard Jupyter extension patch

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