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Dockerfile
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FROM nvidia/cuda:8.0-cudnn5-devel-ubuntu14.04
MAINTAINER Chebrolu Harika <[email protected]>
ARG THEANO_VERSION=rel-0.8.2
ARG TENSORFLOW_VERSION=0.12.1
ARG TENSORFLOW_ARCH=gpu
ARG KERAS_VERSION=1.2.0
ARG TORCH_VERSION=latest
RUN echo -e "\n**********************\nNVIDIA Driver Version\n**********************\n" && \
cat /proc/driver/nvidia/version && \
echo -e "\n**********************\nCUDA Version\n**********************\n" && \
nvcc -V && \
echo -e "\n\nBuilding your Deep Learning Docker Image...\n"
# Install some dependencies
RUN apt-get update && apt-get install -y \
bc \
build-essential \
cmake \
curl \
g++ \
gfortran \
git \
libffi-dev \
libfreetype6-dev \
libhdf5-dev \
libjpeg-dev \
liblcms2-dev \
libopenblas-dev \
liblapack-dev \
libopenjpeg2 \
libpng12-dev \
libssl-dev \
libtiff5-dev \
libwebp-dev \
libzmq3-dev \
nano \
pkg-config \
python-dev \
software-properties-common \
unzip \
vim \
wget \
zlib1g-dev \
qt5-default \
libvtk6-dev \
zlib1g-dev \
libjpeg-dev \
libwebp-dev \
libpng-dev \
libtiff5-dev \
libjasper-dev \
libopenexr-dev \
libgdal-dev \
libdc1394-22-dev \
libavcodec-dev \
libavformat-dev \
libswscale-dev \
libtheora-dev \
libvorbis-dev \
libxvidcore-dev \
libx264-dev \
yasm \
libopencore-amrnb-dev \
libopencore-amrwb-dev \
libv4l-dev \
libxine2-dev \
libtbb-dev \
libeigen3-dev \
python-dev \
python-tk \
python-numpy \
python3-dev \
python3-tk \
python3-numpy \
ant \
default-jdk \
doxygen \
&& \
apt-get clean && \
apt-get autoremove && \
rm -rf /var/lib/apt/lists/* && \
# Link BLAS library to use OpenBLAS using the alternatives mechanism (https://www.scipy.org/scipylib/building/linux.html#debian-ubuntu)
update-alternatives --set libblas.so.3 /usr/lib/openblas-base/libblas.so.3
# Install pip
RUN curl -O https://bootstrap.pypa.io/get-pip.py && \
python get-pip.py && \
rm get-pip.py
# Add SNI support to Python
RUN pip --no-cache-dir install \
pyopenssl \
ndg-httpsclient \
pyasn1
# Install useful Python packages using apt-get to avoid version incompatibilities with Tensorflow binary
# especially numpy, scipy, skimage and sklearn (see https://github.com/tensorflow/tensorflow/issues/2034)
RUN apt-get update && apt-get install -y \
python-numpy \
python-scipy \
python-nose \
python-h5py \
python-skimage \
python-matplotlib \
python-pandas \
python-sklearn \
python-sympy \
&& \
apt-get clean && \
apt-get autoremove && \
rm -rf /var/lib/apt/lists/*
# Install other useful Python packages using pip
RUN pip --no-cache-dir install --upgrade ipython && \
pip --no-cache-dir install \
Cython \
ipykernel \
jupyter \
path.py \
Pillow \
pygments \
six \
sphinx \
wheel \
zmq \
&& \
python -m ipykernel.kernelspec
# Install TensorFlow
RUN pip --no-cache-dir install \
https://storage.googleapis.com/tensorflow/linux/${TENSORFLOW_ARCH}/tensorflow_${TENSORFLOW_ARCH}-${TENSORFLOW_VERSION}-cp27-none-linux_x86_64.whl
# Install Theano and set up Theano config (.theanorc) for CUDA and OpenBLAS
RUN pip --no-cache-dir install git+git://github.com/Theano/Theano.git@${THEANO_VERSION} && \
\
echo "[global]\ndevice=gpu\nfloatX=float32\noptimizer_including=cudnn\nmode=FAST_RUN \
\n[lib]\ncnmem=0.95 \
\n[nvcc]\nfastmath=True \
\n[blas]\nldflag = -L/usr/lib/openblas-base -lopenblas \
\n[DebugMode]\ncheck_finite=1" \
> /root/.theanorc
# Install Keras
RUN pip --no-cache-dir install git+git://github.com/fchollet/keras.git@${KERAS_VERSION}
# Install Torch
RUN git clone https://github.com/torch/distro.git /root/torch --recursive && \
cd /root/torch && \
bash install-deps && \
yes no | ./install.sh
# Export the LUA evironment variables manually
ENV LUA_PATH='/root/.luarocks/share/lua/5.1/?.lua;/root/.luarocks/share/lua/5.1/?/init.lua;/root/torch/install/share/lua/5.1/?.lua;/root/torch/install/share/lua/5.1/?/init.lua;./?.lua;/root/torch/install/share/luajit-2.1.0-beta1/?.lua;/usr/local/share/lua/5.1/?.lua;/usr/local/share/lua/5.1/?/init.lua' \
LUA_CPATH='/root/.luarocks/lib/lua/5.1/?.so;/root/torch/install/lib/lua/5.1/?.so;./?.so;/usr/local/lib/lua/5.1/?.so;/usr/local/lib/lua/5.1/loadall.so' \
PATH=/root/torch/install/bin:$PATH \
LD_LIBRARY_PATH=/root/torch/install/lib:$LD_LIBRARY_PATH \
DYLD_LIBRARY_PATH=/root/torch/install/lib:$DYLD_LIBRARY_PATH
ENV LUA_CPATH='/root/torch/install/lib/?.so;'$LUA_CPATH
# Install OpenCV
RUN git clone --depth 1 https://github.com/opencv/opencv.git /root/opencv && \
cd /root/opencv && \
mkdir build && \
cd build && \
cmake -DWITH_QT=ON -DWITH_OPENGL=ON -DFORCE_VTK=ON -DWITH_TBB=ON -DWITH_GDAL=ON -DWITH_XINE=ON -DBUILD_EXAMPLES=ON .. && \
make -j"$(nproc)" && \
make install && \
ldconfig && \
echo 'ln /dev/null /dev/raw1394' >> ~/.bashrc
WORKDIR "/root"
RUN pip install flow2ml
ADD . flow2Ml/
WORKDIR /root/flow2ml
# Clean and remove not required packages
RUN DEBIAN_FRONTEND=noninteractive \
apt-get autoremove -y && \
apt-get clean -y && \
rm -rf /var/cache/apt/archives/* /var/cache/apt/lists/* /tmp/* /root/cache/.
CMD ["/bin/bash"]