diff options
Diffstat (limited to 'tensorflow/python/keras/integration_test.py')
| -rw-r--r-- | tensorflow/python/keras/integration_test.py | 26 |
1 files changed, 26 insertions, 0 deletions
diff --git a/tensorflow/python/keras/integration_test.py b/tensorflow/python/keras/integration_test.py index 2a05699407..a103b9fbf2 100644 --- a/tensorflow/python/keras/integration_test.py +++ b/tensorflow/python/keras/integration_test.py @@ -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) |