下載Anoconda

Anaconda 是一個用於科學計算的 Python 發行版，支援 Linux, Mac, Windows, 包含了眾多流行的科學計算、資料分析的 Python 包。

Anaconda 具有比pip包管理更強大的能力,不僅管理python 包的依賴,也同時管理其他非python的依賴,所以有逐漸取代pip的趨勢. 同時, Anaconda還有virtual envi等功能, 可以建立虛擬環境.

Anaconda 安裝包可以到 https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/ 下載。

TUNA 還提供了 Anaconda 倉庫的映象，執行以下命令:

conda config –add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ conda config –set show_channel_urls yes 即可新增 Anaconda Python 免費倉庫。

Conda 三方源 當前tuna還維護了一些anaconda三方源。

配置

Conda Forge
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
msys2
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/

https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-4.3.1-Linux-x86_64.sh
[
 
[email protected]nServer ~]$ bash Anaconda3-4.3.1-Linux-x86_64.sh

Welcome to Anaconda3 4.3.1 (by Continuum Analytics, Inc.)


[[email protected] ~]$ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
[[email protected] ~]$ conda config --set show_channel_urls yes
[
 
[email protected] ~]$ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
[[email protected] ~]$ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/

[[email protected] ~]$ vi .condarc
channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
  - defaults
show_channel_urls: true

安裝機器學習相關包

安裝numpy scipy mkl

[[email protected] ~]$ conda install numpy scipy mkl 
Fetching package metadata ...

CondaHTTPError: HTTP None None for url <https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/linux-64/repodata.json>
Elapsed: None

An HTTP error occurred when trying to retrieve this URL.
HTTP errors are often intermittent, and a simple retry will get you on your way.
SSLError(SSLError(SSLError("bad handshake: Error([('SSL routines', 'ssl3_get_server_certificate', 'certificate verify failed')],)",),),)

刪除 .condarc的- defaults

[[email protected] ~]$ conda config --show
add_anaconda_token: True
add_pip_as_python_dependency: True
allow_softlinks: True
always_copy: False
always_softlink: False
always_yes: False
auto_update_conda: True
binstar_upload: None
changeps1: True
channel_alias: https://conda.anaconda.org
channel_priority: True
channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
client_ssl_cert:
client_ssl_cert_key:
create_default_packages: []
debug: False
default_channels:
  - https://repo.continuum.io/pkgs/free
  - https://repo.continuum.io/pkgs/r
  - https://repo.continuum.io/pkgs/pro
disallow: []
envs_dirs:
  - /home/zhouhh/anaconda3/envs
  - /home/zhouhh/.conda/envs
json: False
offline: False
proxy_servers: {}
quiet: False
shortcuts: True
show_channel_urls: True
ssl_verify: True
track_features: []
update_dependencies: True
use_pip: True
verbosity: 0

安裝theano

[[email protected] ~]$ conda intall theano
The following NEW packages will be INSTALLED:

    libgpuarray: 0.6.4-0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
    mako:        1.0.6-py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
    pygpu:       0.6.4-py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
    theano:      0.9.0-py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free

安裝keras

預設會安裝tensorflow 1.1

[[email protected] ~]$ conda install keras
Fetching package metadata .....
Solving package specifications: .

Package plan for installation in environment /home/zhouhh/anaconda3:

The following NEW packages will be INSTALLED:

    keras:       2.0.2-py36_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
    libprotobuf: 3.2.0-0           https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
    protobuf:    3.2.0-py36_0      https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
    tensorflow:  1.1.0-np112py36_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free

測試機器學習環境

[zhouhh@mainServer ~]$ python3
Python 3.6.0 |Anaconda custom (64-bit)| (default, Dec 23 2016, 12:22:00)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from keras.models import Sequential
Using TensorFlow backend.
>>> from keras.layers import Dense, Activation
>>> model = Sequential([
...     Dense(32, input_shape=(784,)),
...     Activation('relu'),
...     Dense(10),
...     Activation('softmax'),
... ])

修改.keras/keras.json 將”backend”: “tensorflow”改為 “backend”: “theano”

[[email protected] ~]$ cat .keras/keras.json
{
    "epsilon": 1e-07,
    "floatx": "float32",
    "image_data_format": "channels_last",
    "backend": "theano"

}

[[email protected] ~]$ python3
Python 3.6.0 |Anaconda custom (64-bit)| (default, Dec 23 2016, 12:22:00)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from keras.models import Sequential
Using Theano backend.
>>> from keras.layers import Dense, Activation
>>> model = Sequential([
...     Dense(32, input_shape=(784,)),
...     Activation('relu'),
...     Dense(10),
...     Activation('softmax'),
... ])
>>>

至此,keras,tensorflow和theano安裝成功

如非註明轉載, 均為原創. 本站遵循知識共享CC協議,轉載請註明來源