Added Wasserstein loss

loss_functions.py

+import tensorflow as tf
+
+def wgan_d_loss(y_true, y_pred, EPS=1e-12):
+    return tf.reduce_mean(y_pred) - tf.reduce_mean(y_true)
+
+def wgan_g_loss(y_true, y_pred, EPS=1e-12):
+    return tf.reduce_mean(y_pred + EPS)
+
+def gan_d_loss(y_true, y_pred, EPS=1e-12):
+    return tf.reduce_mean(tf.math.log(y_true + EPS) + tf.math.log(1 - y_pred + EPS))
+
+def gan_g_loss(y_true, y_pred, EPS=1e-12):
+    return tf.reduce_mean(-tf.math.log(y_pred + EPS))
+