RNN-LSTM时间序列Tensorflow 0.12错误

我想了解一下，时间序列使用RNN-LSTM并在网上找到这个代码：https://github.com/mouradmourafiq/tensorflow-lstm-regression

但是，当试图在v0.12下运行时，我遇到了这些错误 . 我该如何解决这个错误？

WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/monitors.py:320 in __init__.: __init__ (from tensorfl
        ow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05.
        Instructions for updating:
        Monitors are deprecated. Please use tf.train.SessionRunHook.
        WARNING:tensorflow:From lstm_trend.py:48 in <module>.: calling fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with x is deprecated 
        and will be removed after 2016-12-01.
        Instructions for updating:
        Estimator is decoupled from Scikit Learn interface by moving into
        separate class SKCompat. Arguments x, y and batch_size are only
        available in the SKCompat class, Estimator will only accept input_fn.
        Example conversion:
          est = Estimator(...) -> est = SKCompat(Estimator(...))
        WARNING:tensorflow:From lstm_trend.py:48 in <module>.: calling fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with y is deprecated 
        and will be removed after 2016-12-01.
        Instructions for updating:
        Estimator is decoupled from Scikit Learn interface by moving into
        separate class SKCompat. Arguments x, y and batch_size are only
        available in the SKCompat class, Estimator will only accept input_fn.
        Example conversion:
          est = Estimator(...) -> est = SKCompat(Estimator(...))
        WARNING:tensorflow:From lstm_trend.py:48 in <module>.: calling fit (from tensorflow.contrib.learn.python.learn.estimators.estimator) with batch_size is de
        precated and will be removed after 2016-12-01.
        Instructions for updating:
        Estimator is decoupled from Scikit Learn interface by moving into
        separate class SKCompat. Arguments x, y and batch_size are only
        available in the SKCompat class, Estimator will only accept input_fn.
        Example conversion:
          est = Estimator(...) -> est = SKCompat(Estimator(...))
        Traceback (most recent call last):
          File "lstm_trend.py", line 48, in <module>
            regressor.fit(X['train'], y['train'],monitors=[validation_monitor],batch_size=BATCH_SIZE,steps=TRAINING_STEPS)
          File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/util/deprecation.py", line 191, in new_func
            return func(*args, **kwargs)
          File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 355, in fit
            max_steps=max_steps)
          File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 699, in _train_model
            train_ops = self._get_train_ops(features, labels)
          File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 1052, in _get_train_ops
            return self._call_model_fn(features, labels, model_fn_lib.ModeKeys.TRAIN)
          File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/estimators/estimator.py", line 1023, in _call_model_fn
            model_fn_results = self._model_fn(features, labels)
          File "/home/username/rtw-rnn/lstm_model.py", line 122, in _lstm_model
            output = dnn_layers(output[-1], dense_layers)
          File "/home/username/rtw-rnn/lstm_model.py", line 114, in dnn_layers
            return learn.ops.dnn(input_layers, layers)
        AttributeError: 'module' object has no attribute 'dnn'