run autogen make

Author: sachinprasadhs

templates/examples/audio/transformer_asr.md

@@ -263,7 +263,7 @@ class Transformer(keras.Model):
             preds = self([source, dec_input])
             one_hot = tf.one_hot(dec_target, depth=self.num_classes)
             mask = tf.math.logical_not(tf.math.equal(dec_target, 0))
-            loss = model.compute_loss(None, one_hot, preds, sample_weight=mask)
+            loss = self.compute_loss(y=one_hot, y_pred=preds, sample_weight=mask)
         trainable_vars = self.trainable_variables
         gradients = tape.gradient(loss, trainable_vars)
         self.optimizer.apply_gradients(zip(gradients, trainable_vars))
@@ -278,7 +278,7 @@ class Transformer(keras.Model):
         preds = self([source, dec_input])
         one_hot = tf.one_hot(dec_target, depth=self.num_classes)
         mask = tf.math.logical_not(tf.math.equal(dec_target, 0))
-        loss = model.compute_loss(None, one_hot, preds, sample_weight=mask)
+        loss = self.compute_loss(y=one_hot, y_pred=preds, sample_weight=mask)
         self.loss_metric.update_state(loss)
         return {"loss": self.loss_metric.result()}