-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathDockerfile
166 lines (135 loc) · 5.82 KB
/
Dockerfile
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
FROM ubuntu:18.04
# metainformation
LABEL org.opencontainers.image.version = "2.3.1"
LABEL org.opencontainers.image.authors = "Matthias Fey"
LABEL org.opencontainers.image.source = "https://github.com/pyg-team/pytorch_geometric"
LABEL org.opencontainers.image.licenses = "MIT"
LABEL org.opencontainers.image.base.name="docker.io/library/ubuntu:18.04"
RUN apt-get update && apt-get install -y apt-transport-https ca-certificates && \
rm -rf /var/lib/apt/lists/*
RUN apt-get update && apt-get install -y --no-install-recommends apt-utils gnupg2 curl && \
curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub | apt-key add - && \
curl -fsSL https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub | apt-key add - && \
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/cuda.list && \
echo "deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list &&\
apt-get purge --autoremove -y curl && \
rm -rf /var/lib/apt/lists/*
ENV CUDA_VERSION 10.1.243
ENV NCCL_VERSION 2.4.8
ENV CUDA_PKG_VERSION 10-1=$CUDA_VERSION-1
ENV CUDNN_VERSION 7.6.5.32
RUN apt-get update && apt-get install -y --no-install-recommends \
cuda-cudart-$CUDA_PKG_VERSION \
cuda-compat-10-1 && \
ln -s cuda-10.1 /usr/local/cuda && \
rm -rf /var/lib/apt/lists/*
RUN apt-get update && apt-get install -y --allow-unauthenticated --no-install-recommends \
cuda-libraries-$CUDA_PKG_VERSION \
cuda-nvtx-$CUDA_PKG_VERSION \
libcublas10=10.2.1.243-1 \
libnccl2=$NCCL_VERSION-1+cuda10.1 && \
apt-mark hold libnccl2 && \
rm -rf /var/lib/apt/lists/*
RUN apt-get update && apt-get install -y --allow-unauthenticated --no-install-recommends \
cuda-libraries-dev-$CUDA_PKG_VERSION \
cuda-nvml-dev-$CUDA_PKG_VERSION \
cuda-minimal-build-$CUDA_PKG_VERSION \
cuda-command-line-tools-$CUDA_PKG_VERSION \
libnccl-dev=$NCCL_VERSION-1+cuda10.1 \
libcublas-dev=10.2.1.243-1 \
&& \
rm -rf /var/lib/apt/lists/*
RUN apt-get update && apt-get install -y --no-install-recommends \
libcudnn7=$CUDNN_VERSION-1+cuda10.1 \
libcudnn7-dev=$CUDNN_VERSION-1+cuda10.1 \
&& \
apt-mark hold libcudnn7 && \
rm -rf /var/lib/apt/lists/*
ENV LIBRARY_PATH /usr/local/cuda/lib64/stubs
# NVIDIA docker 1.0.
LABEL com.nvidia.volumes.needed="nvidia_driver"
LABEL com.nvidia.cuda.version="${CUDA_VERSION}"
RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
# NVIDIA container runtime.
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
ENV NVIDIA_REQUIRE_CUDA "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
# PyTorch (Geometric) installation
RUN rm /etc/apt/sources.list.d/cuda.list && \
rm /etc/apt/sources.list.d/nvidia-ml.list
RUN apt-get update && apt-get install -y \
curl \
ca-certificates \
vim \
sudo \
git \
wget \
bzip2 \
libx11-6 \
&& rm -rf /var/lib/apt/lists/*
# Create a working directory.
RUN mkdir /app
WORKDIR /app
# Install Miniconda.
RUN curl -so ~/miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
&& chmod +x ~/miniconda.sh \
&& ~/miniconda.sh -b -p ~/miniconda \
&& rm ~/miniconda.sh
ENV PATH=~/miniconda/bin:$PATH
RUN export PATH=~/miniconda/bin:$PATH
ENV CONDA_AUTO_UPDATE_CONDA=false
# Create a non-root user and switch to it.
RUN adduser --disabled-password --gecos '' --shell /bin/bash user \
&& chown -R user:user /app
RUN echo "user ALL=(ALL) NOPASSWD:ALL" > /etc/sudoers.d/90-user
USER user
# All users can use /home/user as their home directory.
ENV HOME=/home/user
RUN chmod 777 /home/user
# Create a Python 3.6 environment.
RUN ~/miniconda/bin/conda install conda-build \
&& ~/miniconda/bin/conda create -y --name py36 python=3.6.5 \
&& ~/miniconda/bin/conda clean -ya
ENV CONDA_DEFAULT_ENV=py36
ENV CONDA_PREFIX=~/miniconda/envs/$CONDA_DEFAULT_ENV
ENV PATH=$CONDA_PREFIX/bin:$PATH
# CUDA 10.0-specific steps.
RUN conda install -y -c pytorch \
cudatoolkit=10.1 \
"pytorch=1.4.0=py3.6_cuda10.1.243_cudnn7.6.3_0" \
torchvision=0.5.0=py36_cu101 \
&& conda clean -ya
# Install HDF5 Python bindings.
RUN conda install -y h5py=2.8.0 \
&& conda clean -ya
RUN pip install h5py-cache==1.0
# Install TorchNet, a high-level framework for PyTorch.
RUN pip install torchnet==0.0.4
# Install Requests, a Python library for making HTTP requests.
RUN conda install -y requests=2.19.1 \
&& conda clean -ya
# Install Graphviz.
RUN conda install -y graphviz=2.40.1 python-graphviz=0.8.4 \
&& conda clean -ya
# Install OpenCV3 Python bindings.
RUN sudo apt-get update && sudo apt-get install -y --no-install-recommends \
libgtk2.0-0 \
libcanberra-gtk-module \
&& sudo rm -rf /var/lib/apt/lists/*
RUN conda install -y -c menpo opencv3=3.1.0 \
&& conda clean -ya
# Install PyG.
RUN CPATH=/usr/local/cuda/include:$CPATH \
&& LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH \
&& DYLD_LIBRARY_PATH=/usr/local/cuda/lib:$DYLD_LIBRARY_PATH
RUN pip install scipy
RUN pip install --no-index torch_scatter -f https://data.pyg.org/whl/torch-1.4.0+cu101.html \
&& pip install --no-index torch_sparse -f https://data.pyg.org/whl/torch-1.4.0+cu101.html \
&& pip install --no-index torch_cluster -f https://data.pyg.org/whl/torch-1.4.0+cu101.html \
&& pip install --no-index torch_spline_conv -f https://data.pyg.org/whl/torch-1.4.0+cu101.html \
&& pip install torch-geometric
# Set the default command to python3.
CMD ["python3"]