(self, prev, i)
A wrapper for get_train_input and get_eval_input.

    Args:
      prev: output tensor from previous step of the RNN. A tensor with shape:
        [batch_size, num_char_classes].
      i: index of a character in the output sequence.

    Returns:
      A tensor with shape [batch_size, ?] - depth depends on implementation
      details.
A wrapper for get_train_input and get_eval_input.
A wrapper for get_train_input and get_eval_input .
def get_input(self, prev, i):
    """A wrapper for get_train_input and get_eval_input.

    Args:
      prev: output tensor from previous step of the RNN. A tensor with shape:
        [batch_size, num_char_classes].
      i: index of a character in the output sequence.

    Returns:
      A tensor with shape [batch_size, ?] - depth depends on implementation
      details.
    """
    if self.is_training():
      return self.get_train_input(prev, i)
    else:
      return self.get_eval_input(prev, i)
def get_input ( self , prev , i ) : if self . is_training ( ) : return self . get_train_input ( prev , i ) else : return self . get_eval_input ( prev , i )