I'm facing a similar problem. I'm trying to implement a VAE for audio.
the code that is causing me the problem are briefed : z_mean = Dense( self.z_dim , init=initialization , activation='linear')(H2) z_mean = LeakyReLU(alpha=.001)(z_mean) z_log_var = Dense( self.z_dim , init=initialization , activation='linear')(H2) z_log_var = LeakyReLU(alpha=.001)(z_log_var) z = Lambda(self.sampling , output_shape=K.int_shape(z_mean) )([z_mean, z_log_var]) H3 = Dense(input_dim - 1, init=initialization , activation='linear')(z) #causing all troublle grads fail to communicate information to the z_log_var and z_mean. When I do grads = K.gradients(cost, trainable_vars) "Backtrace when that variable is created " shows me above line On Saturday, January 16, 2016 at 9:02:06 AM UTC-6, Yang Xiang wrote: > > Hi all, > > I encountered theano.gradient.DisconnectedInputError when I wrote my code > for an end-to-end process. I have a series of parameters to update. In > order to check which parameter caused the disconnect error, I removed them > from the function's parameters one by one. But after I removed all the > parameters (params=[]), this error was still there? What does this case > mean? > > The error report stated: theano.gradient.DisconnectedInputError: grad > method was asked to compute the gradient with respect to a variable that is > not part of the computational graph of the cost, or is used only by a > non-differentiable operator: <TensorType(float64, 4D)> > > Could anyone help? > > Thanks. > > Yang > -- --- 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 [email protected]. For more options, visit https://groups.google.com/d/optout.
