标签:教程 scipy his upgrade dir echo bin ports imp
我这里GPU型号为 tesla T4, 算力为7.5,会有一些特殊处理。首先是我不会在Dockerfile中编译caffe
本次环境安装通过Dockerfile安装,如果按照本教程要先安装docker以及nvidia-docker
git clone https://github.com/BVLC/caffe.git
内容如下
FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu16.04
LABEL maintainer caffe-maint@googlegroups.com
RUN apt-get update && apt-get install -y --no-install-recommends build-essential vim python-opencv python-tk cmake git wget libatlas-base-dev libboost-all-dev libgflags-dev libgoogle-glog-dev libhdf5-serial-dev libleveldb-dev liblmdb-dev libopencv-dev libprotobuf-dev libsnappy-dev protobuf-compiler python-dev python-numpy python-pip python-setuptools python-scipy && rm -rf /var/lib/apt/lists/*
ENV CAFFE_ROOT=/opt/caffe
WORKDIR $CAFFE_ROOT
# FIXME: use ARG instead of ENV once DockerHub supports this
# https://github.com/docker/hub-feedback/issues/460
ENV CLONE_TAG=1.0
RUN git clone -b ${CLONE_TAG} --depth 1 https://github.com/BVLC/caffe.git .
RUN pip install --upgrade pip && pip install pip -U && pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && pip install python-dateutil==2.5.0
# git clone https://github.com/NVIDIA/nccl.git && cd nccl && make -j install && cd .. && rm -rf nccl &&
RUN cd python && for req in $(cat requirements.txt) pydot; do pip install $req; done && cd ..
RUN mkdir build && cd build && #cmake -DUSE_CUDNN=1 .. &&
#make -j"$(nproc)"
ENV PYCAFFE_ROOT $CAFFE_ROOT/python
ENV PYTHONPATH $PYCAFFE_ROOT:$PYTHONPATH
ENV PATH $CAFFE_ROOT/build/tools:$PYCAFFE_ROOT:$PATH
RUN echo "$CAFFE_ROOT/build/lib" >> /etc/ld.so.conf.d/caffe.conf && ldconfig
WORKDIR /workspace
nvidia-docker build -t caffe-cuda10:gpu gpu
构建成功后可以通过下面查看
docker images
nvidia-docker run -it caffe-cuda10:gpu /bin/bash
通过
nvidia-docker ps -a
查看刚创建的container_id,然后开始使用
nvidia-docker exec -it container_id /bin/bash
因为这张gpu卡的算力是7.5的,所以在Dockerfile中没有编译caffe.
修改/opt/caffe/cmake/的Cuda.cmake在第7行加上75
set(Caffe_known_gpu_archs "20 21(20) 30 35 50 60 61 75")
然后cd到build目录下
cmake -DUSE_CUDNN=1 ..
make -j"$(nproc)"
完成!
如果算力没有超过6.1可以使用下面这个Dockerfile,修改的地方就是在Dockerfile中编译好环境。
就是不高于这个-gencode arch=compute_61,code=compute_61
FROM nvidia/cuda:8.0-cudnn6-devel-ubuntu16.04
LABEL maintainer caffe-maint@googlegroups.com
RUN apt-get update && apt-get install -y --no-install-recommends build-essential vim python-opencv python-tk cmake git wget libatlas-base-dev libboost-all-dev libgflags-dev libgoogle-glog-dev libhdf5-serial-dev libleveldb-dev liblmdb-dev libopencv-dev libprotobuf-dev libsnappy-dev protobuf-compiler python-dev python-numpy python-pip python-setuptools python-scipy && rm -rf /var/lib/apt/lists/*
ENV CAFFE_ROOT=/opt/caffe
WORKDIR $CAFFE_ROOT
# FIXME: use ARG instead of ENV once DockerHub supports this
# https://github.com/docker/hub-feedback/issues/460
ENV CLONE_TAG=1.0
RUN git clone -b ${CLONE_TAG} --depth 1 https://github.com/BVLC/caffe.git .
RUN pip install --upgrade pip && pip install pip -U && pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && pip install python-dateutil==2.5.0
# git clone https://github.com/NVIDIA/nccl.git && cd nccl && make -j install && cd .. && rm -rf nccl &&
RUN cd python && for req in $(cat requirements.txt) pydot; do pip install $req; done && cd ..
RUN mkdir build && cd build && cmake -DUSE_CUDNN=1 .. && make -j"$(nproc)"
ENV PYCAFFE_ROOT $CAFFE_ROOT/python
ENV PYTHONPATH $PYCAFFE_ROOT:$PYTHONPATH
ENV PATH $CAFFE_ROOT/build/tools:$PYCAFFE_ROOT:$PATH
RUN echo "$CAFFE_ROOT/build/lib" >> /etc/ld.so.conf.d/caffe.conf && ldconfig
WORKDIR /workspace
这些依赖是训练的依赖,没有可以不执行。
apt-get update
apt-get install python-skimage
pip install python-dateutil==2.1 -i https://pypi.tuna.tsinghua.edu.cn/simple some-package
标签:教程 scipy his upgrade dir echo bin ports imp
原文地址:https://www.cnblogs.com/cyssmile/p/14268909.html