根據install MXNet

MXNet安裝其實是從c++文件make編譯成動態庫到incubator-mxnet/lib/libmxnet.so，而incubator-mxnet/python其實是用python調用c++庫的方法封裝，然后用pip安裝到python，之后example里面的文件就可以import mxnet as mx了。

Linux-Python-CPU-Build from Source on Ubuntu安裝。

查看系統

lsb_release -a

Minimum Requirements

GCC版本：gcc -v

GNU Make：已安裝

Step 1 Install build tools and git.

$ sudo apt-get update

$ sudo apt-get install -y build-essential git

Step 2 Install OpenBLAS

$ sudo apt-get install -y libopenblas-dev liblapack-dev

Step 3 Install OpenCV.

$ sudo apt-get install -y libopencv-dev

Step 4 Download MXNet sources and build MXNet core shared library.

$ git clone --recursive https://github.com/apache/incubator-mxnet

$ cd incubator-mxnet

$ make -j $(nproc) USE_OPENCV=1 USE_BLAS=openblas

cd incubator-mxnet

git submodule init

git submodule update

出錯：src/nnvm/tvm_bridge.cc:37:37: fatal error: tvm/runtime/packed_func.h: No such file or directory

git submodule update --init --recursive

ps：make時間很長。

Build the MXNet Python binding

sudo pip uninstall mxnet

cd python

pip install --upgrade pip

sudo pip install -e .

Linux-Python-CPU-Build from Source on CentOS, Multi-Machines安裝。

配置MXNet在各個node上

sudo yum install build-essential git

sudo yum install lapack-devel openblas-devel opencv-devel

git clone --recursive https://github.com/apache/incubator-mxnet

cd incubator-mxnet

make clean_all

make -j $(nproc) USE_OPENCV=1 USE_BLAS=openblas USE_DIST_KVSTORE=1 USE_PROFILER=1

sudo pip uninstall mxnet

cd python

sudo pip install --upgrade pip

sudo pip install -e .

分布式安裝及運行

總結

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