install_apt.md 2.9 KB
Newer Older
G
gineshidalgo99 已提交
1 2 3 4 5 6
---
title: "Installation: Ubuntu"
---

# Ubuntu Installation

G
gineshidalgo99 已提交
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
### For Ubuntu (>= 17.04)

**Installing pre-compiled Caffe**

Everything including caffe itself is packaged in 17.04 and higher versions.
To install pre-compiled Caffe package, just do it by

    sudo apt install caffe-cpu

for CPU-only version, or

    sudo apt install caffe-cuda

for CUDA version. Note, the cuda version may break if your NVIDIA driver
and CUDA toolkit are not installed by APT.

[Package status of CPU-only version](https://launchpad.net/ubuntu/+source/caffe)

[Package status of CUDA version](https://launchpad.net/ubuntu/+source/caffe-contrib)

**Installing Caffe from source**

We may install the dependencies by merely one line

    sudo apt build-dep caffe-cpu        # dependencies for CPU-only version
    sudo apt build-dep caffe-cuda       # dependencies for CUDA version

It requires a `deb-src` line in your `sources.list`.
Continue with [compilation](installation.html#compilation).

### For Ubuntu (\< 17.04)

G
gineshidalgo99 已提交
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
**General dependencies**

    sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
    sudo apt-get install --no-install-recommends libboost-all-dev

**CUDA**: Install by `apt-get` or the NVIDIA `.run` package.
The NVIDIA package tends to follow more recent library and driver versions, but the installation is more manual.
If installing from packages, install the library and latest driver separately; the driver bundled with the library is usually out-of-date.
This can be skipped for CPU-only installation.

**BLAS**: install ATLAS by `sudo apt-get install libatlas-base-dev` or install OpenBLAS by `sudo apt-get install libopenblas-dev` or MKL for better CPU performance.

**Python** (optional): if you use the default Python you will need to `sudo apt-get install` the `python-dev` package to have the Python headers for building the pycaffe interface.

**Compatibility notes, 16.04**

CUDA 8 is required on Ubuntu 16.04.

**Remaining dependencies, 14.04**

Everything is packaged in 14.04.

    sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev

**Remaining dependencies, 12.04**

These dependencies need manual installation in 12.04.

    # glog
    wget https://github.com/google/glog/archive/v0.3.3.tar.gz
    tar zxvf v0.3.3.tar.gz
    cd glog-0.3.3
    ./configure
    make && make install
    # gflags
    wget https://github.com/schuhschuh/gflags/archive/master.zip
    unzip master.zip
    cd gflags-master
    mkdir build && cd build
    export CXXFLAGS="-fPIC" && cmake .. && make VERBOSE=1
    make && make install
    # lmdb
    git clone https://github.com/LMDB/lmdb
    cd lmdb/libraries/liblmdb
    make && make install

Note that glog does not compile with the most recent gflags version (2.1), so before that is resolved you will need to build with glog first.

Continue with [compilation](installation.html#compilation).