@@ -262,7 +262,7 @@ class Transformer(keras.Model):
262262 preds = self ([source, dec_input])
263263 one_hot = tf.one_hot(dec_target, depth = self .num_classes)
264264 mask = tf.math.logical_not(tf.math.equal(dec_target, 0 ))
265- loss = model .compute_loss(None , one_hot, preds, sample_weight = mask)
265+ loss = self .compute_loss(None , one_hot, preds, sample_weight = mask)
266266 trainable_vars = self .trainable_variables
267267 gradients = tape.gradient(loss, trainable_vars)
268268 self .optimizer.apply_gradients(zip (gradients, trainable_vars))
@@ -277,7 +277,7 @@ class Transformer(keras.Model):
277277 preds = self ([source, dec_input])
278278 one_hot = tf.one_hot(dec_target, depth = self .num_classes)
279279 mask = tf.math.logical_not(tf.math.equal(dec_target, 0 ))
280- loss = model .compute_loss(None , one_hot, preds, sample_weight = mask)
280+ loss = self .compute_loss(None , one_hot, preds, sample_weight = mask)
281281 self .loss_metric.update_state(loss)
282282 return {" loss" : self .loss_metric.result()}
283283
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