message: [Improve test coverage] add a unit test for Keras bidirectional RNN.
diff: @@ -708,6 +708,29 @@ class ControlFlowTest(TestModels):
  expected_value = model.predict(input_data)
  np.testing.assert_almost_equal(expected_value, actual_value, decimal=5)
  + @test_util.run_v2_only
  + def testKerasBidirectionalRNN(self):
  + input_data = constant_op.constant(
  + np.array(np.random.random_sample((1, 10, 10)), dtype=np.float32))
  + model = keras.models.Sequential()
  + model.add(
  + keras.layers.Bidirectional(
  + recurrent_v2.LSTM(units=10, return_sequences=True),
  + input_shape=(10, 10)))
  + model.add(keras.layers.Bidirectional(recurrent_v2.LSTM(units=10)))
  + model.add(keras.layers.Dense(5))
  + model.add(keras.layers.Activation('softmax'))
  +
  + # Convert model.
  + converter = lite.TFLiteConverterV2.from_keras_model(model)
  + converter.experimental_new_converter = True
  + tflite_model = converter.convert()
  + actual_value = self._evaluateTFLiteModel(tflite_model, [input_data])[0]
  +
  + # Check values from converted model.
  + expected_value = model.predict(input_data)
  + np.testing.assert_almost_equal(expected_value, actual_value, decimal=5)
  +
  class GrapplerTest(TestModels):
  