forked from JSchapke/essential-gene-detection
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathDockerfile
130 lines (105 loc) · 4.58 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
FROM 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_64/7fa2af80.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 \
bzip2 \
libx11-6 \
&& rm -rf /var/lib/apt/lists/*
# Create a working directory.
RUN mkdir /app
WORKDIR /app
# 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
# 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=/home/user/miniconda/bin:$PATH
ENV CONDA_AUTO_UPDATE_CONDA=false
# Create a Python 3.6 environment.
RUN /home/user/miniconda/bin/conda install conda-build \
&& /home/user/miniconda/bin/conda create -y --name py36 python=3.6.5 \
&& /home/user/miniconda/bin/conda clean -ya
ENV CONDA_DEFAULT_ENV=py36
ENV CONDA_PREFIX=/home/user/miniconda/envs/$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 PyTorch Geometric.
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 torch-scatter==2.0.4 -f https://pytorch-geometric.com/whl/torch-1.4.0+cu101.html
RUN pip install torch-sparse==0.6.1 -f https://pytorch-geometric.com/whl/torch-1.4.0+cu101.html
RUN pip install torch-cluster==1.5.4 -f https://pytorch-geometric.com/whl/torch-1.4.0+cu101.html
RUN pip install torch-geometric==1.5.0
RUN pip install tqdm optuna
COPY . .