Dockerfile

FROM ubuntu:14.04

ARG THEANO_VERSION=rel-0.8.2
ARG TENSORFLOW_VERSION=0.12.1
ARG TENSORFLOW_ARCH=cpu

RUN apt-get update && apt-get install -y git

# 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 and Theano
RUN pip --no-cache-dir install \
    https://storage.googleapis.com/tensorflow/linux/${TENSORFLOW_ARCH}/tensorflow-${TENSORFLOW_VERSION}-cp27-none-linux_x86_64.whl
# Install Theano and set up Theano config (.theanorc) OpenBLAS
RUN pip --no-cache-dir install git+git://github.com/Theano/Theano.git@${THEANO_VERSION} && \
    \
        echo "[global]\ndevice=cpu\nfloatX=float32\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 Pytorch
RUN pip --no-cache-dir install http://download.pytorch.org/whl/cu75/torch-0.1.12.post2-cp27-none-linux_x86_64.whl
RUN pip --no-cache-dir install torchvision

# copy the current repository
COPY . /root/convai

# Install dependencies
RUN pip install -r /root/convai/requirements.txt

# clone the models
RUN cd /root/convai/models && ./setup

# download the data
RUN cd /root/convai/data && ./setup

EXPOSE 8000

# run the bot
CMD python /root/convai/bot.py