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add dockerfiles (#583)

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* add dockerfiles
This commit is contained in:
ngimel
2017-01-25 14:30:29 -08:00
committed by Soumith Chintala
parent aa46055274
commit 3c2ecc6b15
3 changed files with 93 additions and 0 deletions
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Dockerfile Normal file
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FROM nvidia/cuda:8.0-cudnn5-devel-ubuntu14.04
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cmake \
git \
curl \
ca-certificates \
libjpeg-dev \
libpng-dev &&\
rm -rf /var/lib/apt/lists/*
RUN curl -o ~/miniconda.sh -O https://repo.continuum.io/miniconda/Miniconda3-4.2.12-Linux-x86_64.sh && \
chmod +x ~/miniconda.sh && \
~/miniconda.sh -b -p /opt/conda && \
rm ~/miniconda.sh && \
/opt/conda/bin/conda install conda-build && \
/opt/conda/bin/conda create -y --name pytorch-py35 python=3.5.2 numpy scipy ipython mkl&& \
/opt/conda/bin/conda clean -ya
ENV PATH /opt/conda/envs/pytorch-py35/bin:$PATH
RUN conda install --name pytorch-py35 -c soumith magma-cuda80
# This must be done before pip so that requirements.txt is available
WORKDIR /opt/pytorch
COPY . .
RUN cat requirements.txt | xargs -n1 pip install --no-cache-dir && \
TORCH_CUDA_ARCH_LIST="3.5 5.2 6.0 6.1+PTX" TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \
CMAKE_LIBRARY_PATH=/opt/conda/envs/pytorch-py35/lib \
CMAKE_INCLUDE_PATH=/opt/conda/envs/pytorch-py35/include \
pip install -v .
WORKDIR /workspace
RUN chmod -R a+w /workspace

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README.md
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@ -14,6 +14,7 @@ We are in an early-release Beta. Expect some adventures and rough edges.
- [Installation](#installation)
- [Binaries](#binaries)
- [From source](#from-source)
- [Docker image](#docker-image)
- [Getting Started](#getting-started)
- [Communication](#communication)
- [Releases and Contributing](#releases-and-contributing)
@ -169,6 +170,25 @@ pip install -r requirements.txt
python setup.py install
```
### Docker image
Dockerfiles are supplied to build images with cuda support and cudnn v5 and cudnn v6 RC. Build them as usual
```
docker build . -t pytorch-cudnnv5
```
or
```
docker build . -t pytorch-cudnnv6 -f tools/docker/Dockerfile-v6
```
and run them with nvidia-docker:
```
nvidia-docker run --rm -ti --ipc=host pytorch-cudnnv5
```
Please note that pytorch uses shared memory to share data between processes, so if torch multiprocessing is used (e.g.
for multithreaded data loaders) the default shared memory segment size that container runs with is not enough, and you
should increase shared memory size either with --ipc=host or --shm-size command line options to nvidia-docker run.
## Getting Started
Three pointers to get you started:

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FROM nvidia/cuda:8.0-devel-ubuntu14.04
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cmake \
git \
curl \
ca-certificates \
libjpeg-dev \
libpng-dev &&\
rm -rf /var/lib/apt/lists/*
RUN curl -fsSL http://developer.download.nvidia.com/compute/redist/cudnn/v6.0/cudnn-8.0-linux-x64-v6.0-rc.tgz -O && \
tar -xzf cudnn-8.0-linux-x64-v6.0-rc.tgz -C /usr/local && \
rm cudnn-8.0-linux-x64-v6.0-rc.tgz && \
ldconfig
RUN ln -s /usr/local/cuda/lib64/libcudnn.so.6.0.5 /usr/lib/x86_64-linux-gnu/libcudnn.so.6.0.5
RUN curl -o ~/miniconda.sh -O https://repo.continuum.io/miniconda/Miniconda3-4.2.12-Linux-x86_64.sh && \
chmod +x ~/miniconda.sh && \
~/miniconda.sh -b -p /opt/conda && \
rm ~/miniconda.sh && \
/opt/conda/bin/conda install conda-build && \
/opt/conda/bin/conda create -y --name pytorch-py35 python=3.5.2 numpy scipy ipython mkl&& \
/opt/conda/bin/conda clean -ya
ENV PATH /opt/conda/envs/pytorch-py35/bin:$PATH
RUN conda install --name pytorch-py35 -c soumith magma-cuda80
# This must be done before pip so that requirements.txt is available
WORKDIR /opt/pytorch
COPY . .
RUN cat requirements.txt | xargs -n1 pip install --no-cache-dir && \
TORCH_CUDA_ARCH_LIST="3.5 5.2 6.0 6.1+PTX" TORCH_NVCC_FLAGS="-Xfatbin -compress-all" \
CMAKE_LIBRARY_PATH=/opt/conda/envs/pytorch-py35/lib \
CMAKE_INCLUDE_PATH=/opt/conda/envs/pytorch-py35/include \
pip install -v .
WORKDIR /workspace
RUN chmod -R a+w /workspace