Dockerfile

FROM ubuntu:16.04

# Build dependencies
RUN echo "deb-src http://archive.ubuntu.com/ubuntu/ xenial main restricted" >> /etc/apt/sources.list && apt-get update && apt-get install -y python-pip git mercurial build-essential cmake libopenblas-dev

RUN pip install --upgrade pip
RUN pip install wheel

RUN pip install cython

RUN pip install numpy==1.12.0

ENV EIGEN_VERSION 699b659
# ENV EIGEN_VERSION 346ecdb
RUN cd /opt && \
        hg clone https://bitbucket.org/eigen/eigen/ -r ${EIGEN_VERSION}

# code for installing Intel MKL. You need to supply l_mkl_2018.1.163.tgz file
#COPY l_mkl_2018.1.163.tgz /opt/
#COPY docker/my_silent.cfg /opt/l_mkl_2018.1.163/
#RUN cd /opt/ && \
#    tar zxvf l_mkl_2018.1.163.tgz && cd /opt/l_mkl_2018.1.163 && \
#    ./install.sh --silent "my_silent.cfg"
#ENV LD_PRELOAD /opt/intel/mkl/lib/intel64/libmkl_def.so:/opt/intel/mkl/lib/intel64/libmkl_avx2.so:/opt/intel/mkl/lib/intel64/libmkl_core.so:/opt/intel/mkl/lib/intel64/libmkl_intel_lp64.so:/opt/intel/mkl/lib/intel64/libmkl_intel_thread.so:/opt/intel/lib/intel64_lin/libiomp5.so

# DyNet, version 4234759
ENV DYNET_VERSION 2.0.1
RUN cd /opt && \
        git clone https://github.com/clab/dynet.git && \
        cd dynet && \
        git checkout ${DYNET_VERSION} && \
        mkdir build && \
        cd build && \
        cmake .. -DEIGEN3_INCLUDE_DIR=/opt/eigen -DPYTHON=`which python` && \
        make -j2 && \
        cd python && \
        python ../../setup.py build --build-dir=.. --skip-build install

RUN cd /opt/dynet/build && make -j2 install

# if you want to use Intel MKL, change the above cmake line to
# cmake .. -DEIGEN3_INCLUDE_DIR=/opt/eigen -DPYTHON=`which python` -DMKL_ROOT /opt/intel/mkl && \

ENV DYLD_LIBRARY_PATH /opt/dynet/build/dynet/
ENV LD_LIBRARY_PATH /opt/dynet/build/dynet/

RUN mkdir /opt/ner-tagger-dynet

WORKDIR /opt/ner-tagger-dynet

COPY *.py /opt/ner-tagger-dynet/
COPY requirements.txt /opt/ner-tagger-dynet/

RUN pip install -r requirements.txt

RUN mkdir dataset

COPY evaluation/conlleval evaluation/
RUN mkdir -p evaluation/temp/eval_logs/

RUN mkdir models/