def forward(self, data, state):
fake_score, x_fake, x = data
recon_loss = binary_crossentropy(y_true=x,
y_pred=x_fake,
from_logits=True)
adv_loss = binary_crossentropy(y_pred=fake_score,
y_true=tf.ones_like(fake_score),
from_logits=True)
return adv_loss + self.alpha * recon_loss
def forward(self, data, state):
true_score, fake_score = data
real_loss = binary_crossentropy(y_pred=true_score,
y_true=tf.ones_like(true_score),
from_logits=True)
fake_loss = binary_crossentropy(y_pred=fake_score,
y_true=tf.zeros_like(fake_score),
from_logits=True)
total_loss = real_loss + fake_loss
return total_loss
def forward(self, data, state):
return binary_crossentropy(y_pred=data,
y_true=tf.ones_like(data),
from_logits=True)
