message: Add integration test for Keras RNN that run with TF RNN cell.
diff: @@ -21,9 +21,11 @@ from __future__ import print_function
  import numpy as np
  from tensorflow.python import keras
  +from tensorflow.python.framework import dtypes
  from tensorflow.python.keras import testing_utils
  from tensorflow.python.layers import core as tf_core_layers
  from tensorflow.python.ops import nn
  +from tensorflow.python.ops import rnn_cell
  from tensorflow.python.platform import test
  @@ -103,6 +105,30 @@ class KerasIntegrationTest(test.TestCase):
  verbose=2)
  self.assertGreater(history.history['val_acc'][-1], 0.7)
  + def test_temporal_classification_sequential_tf_rnn(self):
  + with self.test_session():
  + np.random.seed(1337)
  + (x_train, y_train), _ = testing_utils.get_test_data(
  + train_samples=100,
  + test_samples=0,
  + input_shape=(4, 10),
  + num_classes=2)
  + y_train = keras.utils.to_categorical(y_train)
  +
  + model = keras.models.Sequential()
  + model.add(keras.layers.RNN(rnn_cell.LSTMCell(5), return_sequences=True,
  + input_shape=x_train.shape[1:]))
  + model.add(keras.layers.RNN(rnn_cell.GRUCell(y_train.shape[-1],
  + activation='softmax',
  + dtype=dtypes.float32)))
  + model.compile(loss='categorical_crossentropy',
  + optimizer=keras.optimizers.Adam(lr=0.1),
  + metrics=['accuracy'])
  + history = model.fit(x_train, y_train, epochs=15, batch_size=16,
  + validation_data=(x_train, y_train),
  + verbose=2)
  + self.assertGreater(history.history['val_acc'][-1], 0.7)
  +
  def test_image_classification_sequential(self):
  with self.test_session():
  np.random.seed(1337)
  