#?coding:?utf-8
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2017-8-20
使用最基本的LSTM神經(jīng)網(wǎng)預(yù)測(cè)客運(yùn)數(shù)據(jù)
HParams：?模型的超參數(shù)
TS_LSTM：時(shí)間序列訓(xùn)練的LSTM模型
train_test：訓(xùn)練和測(cè)試函數(shù)
@?蔣秋華
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import?numpy?as?np??
import?tensorflow?as?tf??
import?matplotlib.pyplot?as?plt??
import?pandas?as?pd??
from?collections?import?namedtuple???
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簡(jiǎn)單的時(shí)間序列LSTM模型！
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HParams?=?namedtuple（‘HParams‘
?????????????????????‘seq_size?hidden_size?learning_rate‘）

class?TS_LSTM（object）:
????def?__init__（self?hps）:
????????self._X?=?X?=?tf.placeholder（tf.float32?[None?hps.seq_size?1]）??
????????self._Y?=?Y?=?tf.placeholder（tf.float32?[None?hps.seq_size]）??????
????????W?=?tf.Variable（tf.random_normal（[hps.hidden_size?1]）?name=‘W‘）??
????????b?=?tf.Variable（tf.random_normal（[1]）?name=‘b‘）??
????????lstm_cell?=?tf.nn.rnn_cell.BasicLSTMCell（hps.hidden_size）??#測(cè)試cost?1.3809
????????#?lstm_cell?=?tf.nn.rnn_cell.BasicLSTMCell（config.hidden_sizeactivation=tf.nn.relu）???#測(cè)試cost?261.078，性能太差
????????outputs?states?=?tf.nn.dynamic_rnn（lstm_cell?X?dtype=tf.float32）??
????????W_repeated?=?tf.tile（tf.expand_dims（W?0）?[tf.shape（X）[0]?1?1]）??
????????output?=?tf.nn.xw_plus_b（outputs?W_repeated?b）??
????????self._output?=?output?=?tf.squeeze（output）??
????????self._cost?=?cost?=?tf.reduce_mean（tf.square（output?-?Y））??
????????self._train_op?=?tf.train.AdamOptimizer（hps.learning_rate）.minimize（cost）??
????????
????@property
????def?X（self）:
????????return?self._X

????@property
????def?Y（self）:
????????return?self._Y???

????@property
????def?cost（self）:
????????return?self._cost
????
????@property
????def?output（self）:
????????return?self._output

????@property
????def?train_op（self）:
????????return?self._train_op

def?train_test（hps?data）:
?????#訓(xùn)練數(shù)據(jù)準(zhǔn)備
????train_data_len?=?len（data）*2//3
????train_x?train_y?=?[]?[]??
????for?i?in?range（train_data_len?-?hps.seq_size?-?1）:??
????????train_x.append（np.expand_dims（data[i?:?i?+?hps.seq_size]?axis=1）.tolist（））??
????????train_y.append（data[i?+?1?:?i?+?hps.seq_size?+?1].tolist（））??
????#測(cè)試數(shù)據(jù)準(zhǔn)備????
????test_data_len?=?len（data）//3
????test_x?test_y?=?[]?[]??
????for?i?in?range（train_data_len
???????????????????train_data_len+test_data_len?-?hps.seq_size?-?1）:??
????????test_x.append（np.expand_dims（data[i?:?i?+?hps.seq_size]?axis=1）.tolist（））??
????????test_y.append（data[i?+?1?:?i?+?hps.seq_size?+?1].tolist（））??
?????
????with?tf.Graph（）.as_default（）?tf.Session（）?as?sess:??
????????with?tf.variable_scope（‘model‘reuse=None）:
????????????m_train?=?TS_LSTM（hps）
#????????with?tf.variable_scope（‘model‘reuse=True）:????#建立的測(cè)試模型沒有什么用！
#????????????m_test?=?TS_LSTM（Falseconfig）???????????
????????????????????????
????????#訓(xùn)練
????????tf.global_variables_initializer（）.run（）
????????for?step?in?range（20000）:??
????????????_?train_cost?=?sess.run（[m_train.train_op?m_train.cost]?
??????????????????????????????feed_dict={m_train.X:?train_x?m_train.Y:?train_y}）??
????????????????
????????#預(yù)測(cè)?
????????test_cost?output?=?sess.run（[m_train.cost?m_train.output]
??????????????????feed_dict={m_tra