Fix incorrect reference to model in Transformer class (keras-team#2078)

fix: correct model reference to self in Transformer class

Changed model.compute_loss() to self.compute_loss() in train_step 
and test_step methods to properly reference the class instance.

Author: MeysamMoghaddam

examples/audio/transformer_asr.py

@@ -247,7 +247,7 @@ def train_step(self, batch):
             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(None, one_hot, preds, sample_weight=mask)
         trainable_vars = self.trainable_variables
         gradients = tape.gradient(loss, trainable_vars)
         self.optimizer.apply_gradients(zip(gradients, trainable_vars))
@@ -262,7 +262,7 @@ def test_step(self, batch):
         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(None, one_hot, preds, sample_weight=mask)
         self.loss_metric.update_state(loss)
         return {"loss": self.loss_metric.result()}