rnn_encoder_test.py 文件源码

def test_encode(self):
    inputs = tf.random_normal(
        [self.batch_size, self.sequence_length, self.input_depth])
    example_length = tf.ones(
        self.batch_size, dtype=tf.int32) * self.sequence_length

    encode_fn = rnn_encoder.UnidirectionalRNNEncoder(self.params, self.mode)
    encoder_output = encode_fn(inputs, example_length)

    with self.test_session() as sess:
      sess.run(tf.global_variables_initializer())
      encoder_output_ = sess.run(encoder_output)

    np.testing.assert_array_equal(encoder_output_.outputs.shape,
                                  [self.batch_size, self.sequence_length, 32])
    self.assertIsInstance(encoder_output_.final_state,
                          tf.contrib.rnn.LSTMStateTuple)
    np.testing.assert_array_equal(encoder_output_.final_state.h.shape,
                                  [self.batch_size, 32])
    np.testing.assert_array_equal(encoder_output_.final_state.c.shape,
                                  [self.batch_size, 32])