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Fixes to get builds working again #85

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fa6dfe8
Commenting out Caffe and OpenCV from README
opencoca Mar 28, 2018
de9050f
Upgrade python for SSL fix
opencoca Mar 28, 2018
88b2758
Merge branch 'master' of https://github.com/opencoca/dl-docker
opencoca Mar 29, 2018
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128 changes: 86 additions & 42 deletions Dockerfile.gpu
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,16 @@ ARG LASAGNE_VERSION=v0.1
ARG TORCH_VERSION=latest
ARG CAFFE_VERSION=master

ARG PYTHON_BASEDEPS="build-essential python-pip"
ARG PYTHON_BUILDDEPS="libbz2-dev \
libc6-dev \
libgdbm-dev \
libncursesw5-dev \
libreadline-gplv2-dev \
libsqlite3-dev \
libssl-dev \
tk-dev"

#RUN echo -e "\n**********************\nNVIDIA Driver Version\n**********************\n" && \
# cat /proc/driver/nvidia/version && \
# echo -e "\n**********************\nCUDA Version\n**********************\n" && \
Expand Down Expand Up @@ -87,6 +97,24 @@ RUN apt-get update && apt-get install -y \
# 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


ARG PYTHON_TARFILE="Python-2.7.9.tgz"
ARG PYTHON_TARHOST="https://www.python.org/ftp/python/2.7.9"
ARG PYTHON_SRCDIR="Python-2.7.9"

RUN apt-get update
RUN apt-get install -y ${PYTHON_BASEDEPS} ${PYTHON_BUILDDEPS}

RUN wget "${PYTHON_TARHOST}/${PYTHON_TARFILE}"
RUN tar xvf ${PYTHON_TARFILE}

RUN cd ${PYTHON_SRCDIR} && \
./configure && \
make && \
make install



# Install pip
RUN curl -O https://bootstrap.pypa.io/get-pip.py && \
python get-pip.py && \
Expand All @@ -109,28 +137,41 @@ RUN apt-get update && apt-get install -y \
python-matplotlib \
python-pandas \
python-sklearn \
python-sympy \
&& \
python-sympy
RUN apt-get update && apt-get install -y \
libffi-dev libssl-dev && \
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
RUN pip install --upgrade pip
RUN pip install pyopenssl ndg-httpsclient pyasn1
RUN pip --no-cache-dir install --upgrade ipython
RUN pip --no-cache-dir install Cython
RUN pip --no-cache-dir install path.py
RUN pip --no-cache-dir install Pillow
RUN pip --no-cache-dir install pygments
RUN pip --no-cache-dir install six
RUN pip --no-cache-dir install sphinx
RUN pip --no-cache-dir install wheel
RUN pip --no-cache-dir install zmq

#TODO move UP
RUN wget https://www.openssl.org/source/openssl-1.0.2n.tar.gz
RUN tar -xvzf openssl-1.0.2n.tar.gz
RUN cd openssl-1.0.2n && ./config && sudo make && sudo make install
RUN ln -sf /usr/local/ssl/bin/openssl `which openssl`

RUN sleep 1
RUN openssl version -v

RUN pip --no-cache-dir install ipykernel
RUN pip --no-cache-dir install jupyter
RUN python -m ipykernel.kernelspec

#TODO take out if ipykernel gets installed
#RUN false

# Install TensorFlow
RUN pip --no-cache-dir install \
Expand All @@ -154,22 +195,25 @@ RUN apt-get update && apt-get install -y \
apt-get autoremove && \
rm -rf /var/lib/apt/lists/*

# Install Caffe
RUN git clone -b ${CAFFE_VERSION} --depth 1 https://github.com/BVLC/caffe.git /root/caffe && \
cd /root/caffe && \
cat python/requirements.txt | xargs -n1 pip install && \
mkdir build && cd build && \
cmake -DUSE_CUDNN=1 -DBLAS=Open .. && \
make -j"$(nproc)" all && \
make install

# Set up Caffe environment variables
ENV CAFFE_ROOT=/root/caffe
ENV PYCAFFE_ROOT=$CAFFE_ROOT/python
ENV PYTHONPATH=$PYCAFFE_ROOT:$PYTHONPATH \
PATH=$CAFFE_ROOT/build/tools:$PYCAFFE_ROOT:$PATH

RUN echo "$CAFFE_ROOT/build/lib" >> /etc/ld.so.conf.d/caffe.conf && ldconfig
### Install Caffe
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You just removed all the Caffe and OpenCV, it's that ok ?

#RUN git clone -b ${CAFFE_VERSION} --depth 1 https://github.com/BVLC/caffe.git /root/caffe
#RUN cd /root/caffe && \
# cat python/requirements.txt | xargs -n1 -L 1 pip install
#RUN pip install -r /root/caffe/python/requirements.txt
#RUN cd /root/caffe && \
# mkdir build && cd build && \
# cmake -DUSE_CUDNN=1 -DBLAS=Open .. && \
# make -j"$(nproc)" all
#RUN cd /root/caffe/build && \
# make install
#
## Set up Caffe environment variables
#ENV CAFFE_ROOT=/root/caffe
#ENV PYCAFFE_ROOT=$CAFFE_ROOT/python
#ENV PYTHONPATH=$PYCAFFE_ROOT:$PYTHONPATH \
# PATH=$CAFFE_ROOT/build/tools:$PYCAFFE_ROOT:$PATH
#
#RUN echo "$CAFFE_ROOT/build/lib" >> /etc/ld.so.conf.d/caffe.conf && ldconfig


# Install Theano and set up Theano config (.theanorc) for CUDA and OpenBLAS
Expand Down Expand Up @@ -219,16 +263,16 @@ RUN luarocks install nn && \
cd iTorch && \
luarocks make

# 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
#TODO# Install OpenCV
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The same as above.

#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

# Set up notebook config
COPY jupyter_notebook_config.py /root/.jupyter/
Expand Down
6 changes: 2 additions & 4 deletions README.md
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Expand Up @@ -3,23 +3,21 @@ Here are Dockerfiles to get you up and running with a fully functional deep lear

If you are not familiar with Docker, but would still like an all-in-one solution, start here: [What is Docker?](#what-is-docker). If you know what Docker is, but are wondering why we need one for deep learning, [see this](#why-do-i-need-a-docker)

## Update: I've built a quick tool, based on dl-docker, to run your DL project on the cloud with zero setup. You can start running your Tensorflow project on AWS in <30seconds using Floyd. See [www.floydhub.com](https://www.floydhub.com). It's free to try out.
### Happy to take feature requests/feedback and answer questions - mail me [email protected].

## Specs
This is what you get out of the box when you create a container with the provided image/Dockerfile:
* Ubuntu 14.04
* [CUDA 8.0](https://developer.nvidia.com/cuda-toolkit) (GPU version only)
* [cuDNN v5](https://developer.nvidia.com/cudnn) (GPU version only)
* [Tensorflow](https://www.tensorflow.org/)
* [Caffe](http://caffe.berkeleyvision.org/)
* ~~[Caffe](http://caffe.berkeleyvision.org/)~~
* [Theano](http://deeplearning.net/software/theano/)
* [Keras](http://keras.io/)
* [Lasagne](http://lasagne.readthedocs.io/en/latest/)
* [Torch](http://torch.ch/) (includes nn, cutorch, cunn and cuDNN bindings)
* [iPython/Jupyter Notebook](http://jupyter.org/) (including iTorch kernel)
* [Numpy](http://www.numpy.org/), [SciPy](https://www.scipy.org/), [Pandas](http://pandas.pydata.org/), [Scikit Learn](http://scikit-learn.org/), [Matplotlib](http://matplotlib.org/)
* [OpenCV](http://opencv.org/)
* ~~[OpenCV](http://opencv.org/)~~
* A few common libraries used for deep learning

## Setup
Expand Down