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import tensorflow as tf
import hyperchamber as hc
from hypergan.losses.base_loss import BaseLoss
class SoftmaxLoss(BaseLoss):
def _create(self, d_real, d_fake):
gan = self.gan
config = self.config
ops = self.gan.ops
ln_zb = tf.reduce_sum(tf.exp(-d_real), axis=1)+tf.reduce_sum(tf.exp(-d_fake), axis=1)
ln_zb = tf.log(ln_zb)
d_loss = tf.reduce_mean(d_real, axis=1) + ln_zb
g_loss = tf.reduce_mean(d_fake, axis=1) + tf.reduce_mean(d_real, axis=1) + ln_zb
d_loss = ops.reshape(d_loss, [])
g_loss = ops.reshape(g_loss, [])
return [d_loss, g_loss]
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