minimal installation of keras 1.0.8 running example code at the end

Dockerfile-working

FROM nvidia/cuda:7.5-cudnn5-devel

ENV CONDA_DIR /opt/conda
ENV PATH $CONDA_DIR/bin:$PATH

RUN mkdir -p $CONDA_DIR && \
    echo export PATH=$CONDA_DIR/bin:'$PATH' > /etc/profile.d/conda.sh && \
    apt-get update && \
    apt-get install -y wget git libhdf5-dev g++ graphviz && \
    wget --quiet https://repo.continuum.io/miniconda/Miniconda3-3.9.1-Linux-x86_64.sh && \
    echo "6c6b44acdd0bc4229377ee10d52c8ac6160c336d9cdd669db7371aa9344e1ac3 *Miniconda3-3.9.1-Linux-x86_64.sh" | sha256sum -c - && \
    /bin/bash /Miniconda3-3.9.1-Linux-x86_64.sh -f -b -p $CONDA_DIR && \
    rm Miniconda3-3.9.1-Linux-x86_64.sh

ENV NB_USER keras
ENV NB_UID 1000

RUN useradd -m -s /bin/bash -N -u $NB_UID $NB_USER && \
    mkdir -p $CONDA_DIR && \
    chown keras $CONDA_DIR -R && \
    mkdir -p /src && \
    chown keras /src

USER keras

# Python
ARG python_version=3.5.1
ARG tensorflow_version=0.9.0rc0-cp35-cp35m
RUN conda install -y python=${python_version} && \
    pip install https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-${tensorflow_version}-linux_x86_64.whl && \
    conda clean -yt
RUN pip install git+git://github.com/fchollet/keras.git@1.0.8

ENV PYTHONPATH='/src/:$PYTHONPATH'

WORKDIR /src

EXPOSE 8888

CMD echo "\
from keras.models import Sequential\n\
from keras.layers import Convolution2D, MaxPooling2D, Activation\n\
model = Sequential()\n\
model.add(Convolution2D(32, 3, 3, input_shape=(3, 150, 150)))\n\
model.add(Activation('relu'))\n\
model.add(MaxPooling2D(pool_size=(2, 2)))\n" | python3