message: Add a test for model.predict with tf.keras.layers.ConvLSTM2D layer when XLA dynamic padder is enabled.
diff: @@ -251,6 +251,33 @@ class KerasModelsTest(test.TestCase, parameterized.TestCase):
  train_step(input_iterator)
  + @combinations.generate(
  + combinations.combine(
  + distribution=strategy_combinations.all_strategies,
  + mode=["eager"]))
  + def test_model_predict_with_dynamic_batch(self, distribution):
  + input_data = np.random.random([1, 32, 64, 64, 3])
  + input_shape = tuple(input_data.shape[1:])
  +
  + def build_model():
  + model = keras.models.Sequential()
  + model.add(
  + keras.layers.ConvLSTM2D(
  + 4,
  + kernel_size=(4, 4),
  + activation="sigmoid",
  + padding="same",
  + input_shape=input_shape))
  + model.add(keras.layers.GlobalMaxPooling2D())
  + model.add(keras.layers.Dense(2, activation="sigmoid"))
  + return model
  +
  + with distribution.scope():
  + model = build_model()
  + model.compile(loss="binary_crossentropy", optimizer="adam")
  + result = model.predict(input_data)
  + self.assertEqual(result.shape, (1, 2))
  +
  @combinations.generate(
  combinations.combine(
  distribution=strategy_combinations.all_strategies,
  