You can do it in a few different ways: * b = a.reshape(a.shape[0],1) * b = a.dimshuffle(0, 'x')
I recommand the last one as depending of the graph around, the dimshuffle could be optimized away. Fred On Mon, Oct 24, 2016 at 3:55 AM, <linzhesha...@gmail.com> wrote: > Assume that i have two vectors a and b, and i would like to add these two to > get a matrix. In numpy i can do it in this way. > > import numpy as np > a = np.array([0,1,2]) > b = a.reshape(3,1) > a+b > > In theano i can do it like > > a = numpy.array([[0,1,2]]) > b = numpy.array([[0],[1],[2]])##b = a.reshape(a.shape[1],a.shape[0]) > a1=theano.shared(numpy.asarray(a), broadcastable =(True,False), borrow =True) > b1 = theano.shared(numpy.asarray(b),broadcastable=(False, True),borrow = True) > > alpha_matrix = T.add(a1, b1) > alpha_matrix_compute = theano.function([], alpha_matrix)for i in range(10000): > c = alpha_matrix_compute() > > But the problem is that, a and b are not given and they are calculated during > the program running. So they cannot be defined as shared values. > So, symbolic value must be used. How to calculate it with symbolic value? > > -- > > --- > You received this message because you are subscribed to the Google Groups > "theano-users" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to theano-users+unsubscr...@googlegroups.com. > For more options, visit https://groups.google.com/d/optout. > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
