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new release tensorflow 2.3
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python-tensorflow/Dockerfile.2.3-py36-cuda10.1

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FROM lablup/common-base:20.07-py36-cuda10.1
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# Install TensorFlow, Keras, PyTorch and MXNet
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ENV TENSORFLOW_VERSION=2.3.0-rc2
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ENV TENSORFLOW_VERSION=2.3.0
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ENV PYTHONUNBUFFERED=1 \
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LD_LIBRARY_PATH="/usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:/usr/local/nvidia/lib64:/usr/include/x86_64-linux-gnu" \
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RUN python3 -m pip install --no-cache-dir \
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tensorflow==${TENSORFLOW_VERSION}
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RUN python3 -m pip install --no-cache-dir --extra-index-url \
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https://developer.download.nvidia.com/compute/redist \
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nvidia-dali-cuda100 && \
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python3 -m pip install --no-cache-dir --extra-index-url \
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https://developer.download.nvidia.com/compute/redist nvidia-dali-tf-plugin-cuda100
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# Install Horovod, temporarily using CUDA stubs
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RUN ldconfig /usr/local/cuda/targets/x86_64-linux/lib/stubs && \
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HOROVOD_GPU_ALLREDUCE=NCCL HOROVOD_GPU_BROADCAST=NCCL \
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HOROVOD_WITH_TENSORFLOW=1 HOROVOD_WITHOUT_PYTORCH=1 HOROVOD_WITHOUT_MXNET=1 \
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pip install --no-cache-dir horovod==0.19.4 && \
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pip install --no-cache-dir horovod==0.19.5 && \
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ldconfig
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RUN python3 -m pip install --no-cache-dir \
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Run python3 -m ipykernel install --display-name "TensorFlow 2.3 on Python 3.6 (CUDA 10.1)" && \
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cat /usr/local/share/jupyter/kernels/python3/kernel.json
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RUN jupyter nbextension enable --py --sys-prefix widgetsnbextension && \
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jupyter nbextension enable --py tensorflow_model_analysis
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# Backend.AI specifics
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LABEL ai.backend.kernelspec="1" \
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ai.backend.envs.corecount="OPENBLAS_NUM_THREADS,OMP_NUM_THREADS,NPROC" \

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