tf.add_n(self.output_photo_discr_loss.values())
// Compute discriminator accuracies.
self.input_painting_discr_acc = {key: tf.reduce_mean(tf.cast(x=(pred > tf.ones_like(pred)*0.5),
dtype=tf.float32)) * scale_weight[key]
for key, pred in zip(self.input_painting_discr_predictions.keys(),
self.input_painting_discr_predictions.values())}
After Change
dtype=tf.float32)) * scale_weight[key]
for key, pred in zip(self.input_photo_discr_predictions.keys(),
self.input_photo_discr_predictions.values())}
self.output_photo_discr_acc = {key: tf.reduce_mean(tf.cast(x=(pred < tf.zeros_like(pred)),
dtype=tf.float32)) * scale_weight[key]
for key, pred in zip(self.output_photo_discr_predictions.keys(),
self.output_photo_discr_predictions.values())}
