Hey, So I'm trying to implement a VAE on keras, and the following is a snippet of the code I've written.
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)* Now when I later compile the model: model = Model(input=data_input, output=[xh , z_mean , z_log_var ] ) grads = K.gradients(cost, trainable_vars) it gives me the error: *theano.gradient.DisconnectedInputError: * *Backtrace when that variable is created:* * H3 = Dense(input_dim - 1, init=initialization , activation='linear')(z)* Does anyone have any idea why this error is there? My guess is that the gradient fail to apply from the z to z_mean and z_log_var Regards Priyank Pathak -- --- 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.
