Merge pull request #58 from sony/feature/20181025-dockerfile

[doc][docker] Add Dockerfile beta

Dockerfile

@@ -0,0 +1,26 @@
+ARG CUDA_VER=9.0
+ARG CUDNN_VER=7
+
+FROM nvidia/cuda:${CUDA_VER}-cudnn${CUDNN_VER}-runtime-ubuntu16.04
+
+ARG PYTHON_VER=3.5
+ARG CUDA_VER=9.0
+ENV PATH /opt/miniconda3/bin:$PATH
+ENV OMP_NUM_THREADS 1
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    wget \
+    bzip2 \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN umask 0 \
+    && wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh \
+    && bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/miniconda3 \
+    && rm -rf Miniconda3-latest-Linux-x86_64.sh \
+    && conda install -y python=${PYTHON_VER} \
+    && (pip install --no-cache-dir -U setuptools || pip install --no-cache-dir -U setuptools || pip install --no-cache-dir -U setuptools || true) \
+    && conda install -y opencv jupyter
+
+RUN umask 0 \
+    && pip install nnabla-ext-cuda`echo $CUDA_VER | sed 's/\.//g'`

README.md

@@ -9,3 +9,27 @@ Before running an example, also run the following command inside the example dir
 cd example_directory
 pip install -r requirements.txt
 ```
+
+
+## Docker image
+
+If you have [Docker](https://www.docker.com/) and [NVIDIA Docker](https://www.docker.com/) on your system, you can build and run a CUDA-compatible Docker image which contains dependencies for running most of the examples in this repository.
+
+The following command creates the Docker image.
+
+```shell
+docker build -t local/nnabla-examples . --build-arg CUDA_VER=9.2 --build-arg CUDNN_VER=7 --build-arg PYTHON_VER=3.6
+```
+
+The options followed by `--build-arg` specify the versions of some dependent software. You can ommit these arguments if you use the default. You can find the default versions at the lines containing `ARG` commands in the [Dockerfile](./Dockerfile).
+
+
+A Docker container of the created image can be launched by;
+
+```shell
+nvidia-docker run {options} local/nnabla-examples {command}
+```
+
+*Note*:
+
+* You must use a CUDA toolkit version compatible with your CUDA driver version on your host system.