Here's what my code in numpy looks like: tensor = shared(np.random.randn(7, 16, 16))
e_tensor = tensor.eval() tensor2 = e_tensor[0,:,:] tensor2[tensor2 < 1] = 0.0 tensor2[tensor2 > 0 = 1.0 new_tensor = [tensor2] for i in range(1, e_tensor.shape[0]): new_tensor.append(np.multiply(tensor2, e_tensor[i,:,:])) output = np.array(new_tensor).reshape(7,16,16) On Tuesday, January 17, 2017 at 10:47:24 AM UTC-5, Corey Nolet wrote: > > I have a tensor which is (7,16,16), let's denote as Tijk. I need to make > the following function: > > for j in range(0, 16): > for k in range(0, 16): > if T0jk == 0: > for i in range(1, 7): > Tijk = 0 > > > Any ideas on how this can be done with Theano's tensor API? > > > Thanks! : > > -- --- 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.