basic_rnn_test.py 文件源码

def testComputation(self):
    model_rnn = snt.ModelRNN(self.model)
    inputs = tf.random_normal([self.batch_size, 5])
    prev_state = tf.placeholder(tf.float32,
                                shape=[self.batch_size, self.hidden_size])

    outputs, next_state = model_rnn(inputs, prev_state)

    with self.test_session() as sess:
      prev_state_data = np.random.randn(self.batch_size, self.hidden_size)
      feed_dict = {prev_state: prev_state_data}
      sess.run(tf.global_variables_initializer())

      outputs_value = sess.run([outputs, next_state], feed_dict=feed_dict)
      outputs_value, next_state_value = outputs_value

    self.assertAllClose(prev_state_data, outputs_value)
    self.assertAllClose(outputs_value, next_state_value)