Deep Learning notes ------ configure and install caffe-cpu only mode in linux, and install caffecpuonly

Deep Learning notes ------ configure and install caffe-cpu only mode in linux, and install caffecpuonly

This article is suitable for beginners to learn the simplest way to configure caffe. This is the most silly configuration method I have summarized after reading the methods of various great gods on the Internet.

I am also suffering from attacks and growth in the Process of constantly configuring caffe @. @

Step 1: configure the dependent environment required by caffe

Open the terminal.

Sudo apt-get install git libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler

Sudo apt-get install -- no-install-recommends libboost-all-dev libatlas-base-dev python-dev libgflags-dev libgoogle-glog-dev liblmdb-dev

Step 2: Upgrade gcc and g ++ to 4.9

This step is mainly to prepare for configuring cuda, but it is best to update it.

Sudo add-apt-repository ppa: ubuntu-toolchain-r/test

Sudo apt-get update

Sudo apt-get install gcc-4.9

Sudo apt-get install g ++-4.9

Sudo su

Cd ../usr/bin

Ln-s/usr/bin/g ++-4.9/usr/bin/g ++-f

Ln-s/usr/bin/gcc-4.9/usr/bin/gcc-f

Later, the gcc and g ++ versions are 4.9 by default, and can be queried through gcc -- version.

Step 3: Compile caffe

Download caffe source code on github, web site https://github.com/BVLC/caffe

Download the package and extract it to the main folder directory.

Cd caffe

Cp Makefile. config. example Makefile. config

Open Makefile. config and modify CPU_ONLY = 1. Delete the # sign.

Save and exit.

Make-j8 # (number of CPU threads you call after j)

Make test

Make runtest

If no error is reported, the playing is successful.

Step 4. Install anaconda and configure the python Interface

The official anaconda website provides free and installation instructions, which are easy to use. Https://www.continuum.io/downloads

Change environment variables.

Sudo gedit/etc/profile

Export PATH =/home/irondroid/anaconda2/bin: $ PATH

Export PYTHONPATH =/home/irondroid/caffe/python: $ PYTHONPATH

Export ld_pre load =/usr/lib/x86_64-linux-gnu/libstdc ++. so.6

Source/etc/profile

Cd caffe

Make pycaffe

Step 5. Complete caffe Installation

After restarting the computer, enter python. If the anaconda path appears, it indicates that anaconda is successfully installed. Then

>>> Import caffe

If any errors such as protobuf occur

Sudo chmod 777-R anaconda2

Conda install protobuf

In this way, you can

Then

>>> Import caffe

>>>

Verify that the installation is successful.

Step 6. recompile caffe

If caffe needs to be re-compiled in a new situation, compilation may fail after make clean. In most cases

Cannot find # include "caffe/proto/caffe. pb. h" #1761

If the above error occurs, you need to perform the following steps:

Cd caffe

Protoc src/caffe/proto/caffe. proto -- cpp_out =.

Mkdir include/caffe/proto

Mv src/caffe/proto/caffe. pb. h include/caffe/proto

And then make.

Step 7: Configure cuda and cudnn

I haven't configured the table successfully yet. Read the Table @*@