message: Fix recurrent tutorial's code snippet.
diff: @@ -77,9 +77,7 @@ The basic pseudocode is as follows:
  words_in_dataset = tf.placeholder(tf.float32, [time_steps, batch_size, num_features])
  lstm = tf.contrib.rnn.BasicLSTMCell(lstm_size)
  # Initial state of the LSTM memory.
  -hidden_state = tf.zeros([batch_size, lstm.state_size])
  -current_state = tf.zeros([batch_size, lstm.state_size])
  -state = hidden_state, current_state
  +state = lstm.zero_state(batch_size, dtype=tf.float32)
  probabilities = []
  loss = 0.0
  for current_batch_of_words in words_in_dataset:
  @@ -112,7 +110,7 @@ words = tf.placeholder(tf.int32, [batch_size, num_steps])
  lstm = tf.contrib.rnn.BasicLSTMCell(lstm_size)
  # Initial state of the LSTM memory.
  -initial_state = state = tf.zeros([batch_size, lstm.state_size])
  +initial_state = state = lstm.zero_state(batch_size, dtype=tf.float32)
  for i in range(num_steps):
  # The value of state is updated after processing each batch of words.
  