docker/Dockerfile.demo_gpu

# Minimum docker image for demo purposes
# prebuilt-image: tvmai/demo-gpu
FROM nvidia/cuda:9.0-cudnn7-devel

RUN apt-get update --fix-missing

COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh
RUN bash /install/ubuntu_install_core.sh

# Python: basic dependencies
RUN apt-get update && apt-get install -y python3-dev python3-pip
RUN pip3 install numpy nose-timer cython decorator scipy

# LLVM
RUN echo deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-6.0 main \
     >> /etc/apt/sources.list.d/llvm.list && \
     wget -O - http://apt.llvm.org/llvm-snapshot.gpg.key|sudo apt-key add - && \
     apt-get update && apt-get install -y --force-yes llvm-6.0

# Jupyter notebook.
RUN pip3 install matplotlib Image Pillow jupyter[notebook]

# Deep learning frameworks
RUN pip3 install mxnet tensorflow keras gluoncv

# Build TVM
COPY install/install_tvm_gpu.sh /install/install_tvm_gpu.sh
RUN bash /install/install_tvm_gpu.sh

# Environment variables
ENV PYTHONPATH=/usr/tvm/python:/usr/tvm/topi/python:/usr/tvm/nnvm/python/:/usr/tvm/vta/python:${PYTHONPATH}
ENV PATH=/usr/local/nvidia/bin:${PATH}
ENV PATH=/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/local/nvidia/lib64:${LD_LIBRARY_PATH}