本文整理汇总了Python中decoder.Decoder.restore方法的典型用法代码示例。如果您正苦于以下问题：Python Decoder.restore方法的具体用法？Python Decoder.restore怎么用？Python Decoder.restore使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类decoder.Decoder的用法示例。
在下文中一共展示了Decoder.restore方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: decode
# 需要导入模块: from decoder import Decoder [as 别名]
# 或者: from decoder.Decoder import restore [as 别名]
def decode(self, reader, writer):
'''
compute pseudo likelihoods the testing set
Args:
reader: a feature reader object to read features to decode
writer: a writer object to write likelihoods
'''
#create a decoder
decoder = Decoder(self.dnn, self.input_dim, reader.max_input_length)
#read the prior
prior = np.load(self.conf['savedir'] + '/prior.npy')
#start tensorflow session
config = tf.ConfigProto()
config.gpu_options.allow_growth = True #pylint: disable=E1101
with tf.Session(graph=decoder.graph, config=config):
#load the model
decoder.restore(self.conf['savedir'] + '/final')
#feed the utterances one by one to the neural net
while True:
utt_id, utt_mat, looped = reader.get_utt()
if looped:
break
#compute predictions
output = decoder(utt_mat)
#get state likelihoods by dividing by the prior
output = output/prior
#floor the values to avoid problems with log
np.where(output == 0, np.finfo(float).eps, output)
#write the pseudo-likelihoods in kaldi feature format
writer.write_next_utt(utt_id, np.log(output))
#close the writer
writer.close()