[Theano] Theano初探

1. Theano用来干嘛的？

Theano was written at the LISA lab to support rapid development of efficient machine learning algorithms. Theano is named after the Greek mathematician, who may have been Pythagoras’ wife. Theano is released under a BSD license (link).

加快处理多维数组计算。Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C implementations for problems involving large amounts of data. It can also surpass C on a CPU by many orders of magnitude by taking advantage of recent GPUs.

Theano’s compiler applies many optimizations of varying complexity to these symbolic expressions. These optimizations include, but are not limited to:

use of GPU for computations

constant folding

merging of similar subgraphs, to avoid redundant calculation

arithmetic simplification (e.g.

x*y/x -> y

,

--x -> x

)

inserting efficient BLAS operations (e.g.

GEMM

) in a variety of contexts

using memory aliasing to avoid calculation

using inplace operations wherever it does not interfere with aliasing

loop fusion for elementwise sub-expressions

improvements to numerical stability (e.g.

and

)

for a complete list, see Optimizations

2. 安装Theano

我用的是Ubuntu，所以戳Easy Installation of an Optimized Theano on Current Ubuntu. （其它系统见Installing Theano）

直接用下面指令就安装完成了

For Ubuntu 11.10 through 14.04:

#sudo apt-get install python-numpy python-scipy python-dev python-pip python-nose g++ libopenblas-dev git
#sudo pip install Theano

3. 测试一下logistic function

import theano
import theano.tensor as T
x = T.dmatrix('x')
s = 1 / (1 + T.exp(-x))
logistic = theano.function([x], s)
logistic([[0, 1], [-1, -2]])

如果没有报错就完成了