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import tensorflow as tf
import hyperchamber as hc
from hypergan.losses.base_loss import BaseLoss
class SupervisedLoss(BaseLoss):
def _create(self, d_real, d_fake):
gan = self.gan
config = self.config
batch_size = gan.batch_size()
net = d_real
num_classes = gan.ops.shape(gan.inputs.y)[1]
net = gan.discriminator.ops.linear(net, num_classes)
net = self.layer_regularizer(net)
d_class_loss = tf.nn.softmax_cross_entropy_with_logits(logits=net,labels=gan.inputs.y)
d_class_loss = gan.ops.squash(d_class_loss)
self.metrics = {
'd_class_loss': d_class_loss
}
return [d_class_loss, None]
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