Hi, it's a nice work and thanks for sharing the code.
I have a puzzle, in arga_vae model, when you define the OptimizerVAE in optimizer.py, the generator_loss doesn't plus the auto-encoder cost
self.generator_loss = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.ones_like(d_fake), logits=d_fake))
rather than
self.generator_loss = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.ones_like(d_fake), logits=d_fake))+self.cost.
Can you please tell me the reason to do this?
Thanks a lot.
Hi, it's a nice work and thanks for sharing the code.
I have a puzzle, in arga_vae model, when you define the OptimizerVAE in optimizer.py, the generator_loss doesn't plus the auto-encoder cost
self.generator_loss = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.ones_like(d_fake), logits=d_fake))rather than
self.generator_loss = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.ones_like(d_fake), logits=d_fake))+self.cost.Can you please tell me the reason to do this?
Thanks a lot.