theano 中的一个函数 sparse_block_dot; Function: for b in range(batch_size): for j in range(o.shape[1]): for i in range(h.shape[1]): o[b, j, :] += numpy.dot(h[b, i], W[iIdx[b, i], oIdx[b, j]]) Image Example Input Parameter - W (iBlocks, oBlocks, iSize, oSiz…

Transposed Convolution, 也叫Fractional Strided Convolution, 或者流行的(错误)称谓: 反卷积, Deconvolution. 定义请参考tutorial. 此处也是对tutorial中的theano实现做一个总结, 得到一段可用的Deconvolution代码. 反卷积(都这么叫了, 那我也不纠结这个了. )的实现方式之一是前向卷积操作的反向梯度传播过程, 所以在Theano中可使用theano.tensor.nnet.abstract_c…

Theano printing To visualize the internal relation graph of theano variables. Installing conda install pydot graphviz add graphviz path D:\Anaconda\Library\bin\graphvizto system PATH[windows version] or: download installer from http://www.graphviz.or…

Graph Structure Graph Definition theano's symbolic mathematical computation, which is composed of: Apply node: the application of an operator to some variable. Variable node: symbolic varibles. Op node: mathematical operation like: +,-,*,\,sqrt,sum,t…

Theano Inplace inplace Computation computation that destroy their inputs as a side-effect. Example if you iterate over matrix and double every elements, this is an inplace operations. because when you are done, the original inputs has been overwritte…

broadcasting Theano vs. Numpy broadcast mechanism allows a scalar may be added to a matrix, a vector to a matrix or a scalar to a vecotor. Examples T and F stands for True and False respectively, denoting which dimension can be broadcasted. Diference…

selected from Theano Doc Optimizing Scan performance Minimizing Scan Usage performan as much of the computation as possible outside of Scan. This may have the effect increasing memory usage but also reduce the overhead introduce by Scan. Explicitly p…

说明:系统是unbuntu14.04LTS,32位的操作系统,以前安装了python3.4,现在想要安装theano和keras.步骤如下: 1,安装pip sudo apt-get install python3-setuptools sudo easy_install3 pip 2,安装g++ sudo apt-get install g++ 采用上述命令安装g++,安装完成后可用g++ -version查看是否安装完成.注意,如果没有安装g++,在import theano时会出现以下错误…

import numpy import theano.tensor as T from theano import function x = T.dscalar('x') y = T.dscalar('y') z = x + y f = function([x, y], z)numpy.allclose(f(16.3, 12.1), 28.4) 输出为truenumpy.allclose(z.eval({x:16.3, y:12.1}, 28.4)) 输出为true tensor:高维数组,T…

Theano 学习笔记(一) theano 为什么要定义共享变量? 定义共享变量的原因在于GPU的使用,如果不定义共享的话,那么当GPU调用这些变量时,遇到一次就要调用一次,这样就会花费大量时间在数据存取上,导致使用GPU代码运行很慢,甚至比仅用CPU还慢. 共享变量的类型必须为floatX 因为GPU要求在floatX上操作,所以所有的共享变量都要声明为floatX类型 shared_x = theano.shared(numpy.asarray(data_x, dtype=theano.co…