diff --git a/tensorflow_examples/models/densenet/densenet.py b/tensorflow_examples/models/densenet/densenet.py
index d98509a5dfd..2254a2dfef1 100644
--- a/tensorflow_examples/models/densenet/densenet.py
+++ b/tensorflow_examples/models/densenet/densenet.py
@@ -188,7 +188,7 @@ def __init__(self, num_filters, data_format,
                                        data_format=data_format,
                                        kernel_initializer="he_normal",
                                        kernel_regularizer=l2(weight_decay))
-    self.avg_pool = tf.keras.layers.AveragePooling2D(data_format=data_format)
+    self.avg_pool = tf.keras.layers.AveragePooling2D(pool_size(2,2),data_format=data_format)
 
   def call(self, x, training=True):
     output = self.batchnorm(x, training=training)
diff --git a/tensorflow_examples/models/nmt_with_attention/train.py b/tensorflow_examples/models/nmt_with_attention/train.py
index 13914ce1fe9..705a322d76a 100644
--- a/tensorflow_examples/models/nmt_with_attention/train.py
+++ b/tensorflow_examples/models/nmt_with_attention/train.py
@@ -154,8 +154,8 @@ def training_loop(self, train_ds, test_ds):
     template = 'Epoch: {}, Train Loss: {}, Test Loss: {}'
 
     for epoch in range(self.epochs):
-      self.train_loss_metric.reset_states()
-      self.test_loss_metric.reset_states()
+      self.train_loss_metric.reset_state()
+      self.test_loss_metric.reset_state()
 
       for inp, targ in train_ds:
         self.train_step((inp, targ))