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一些机器学习的实践
Hello~
Thank you very much for sharing the code!
I try to run the script tensorflow/book/deeplearning/code/06-6.py
. After some iterations, it is found that the training loss becomes NAN. After carefully checking the code, I found that the following code may trigger NAN in loss:
In tensorflow/book/deeplearning/code/06-6.py
# 通过设置log前的最小值不让归0,防止出现 log(0) 未定义
tf.clip_by_value(self.pred, 1e-15, 1.0)
cross_entropy = tf.reduce_mean(-tf.reduce_sum(self.y*tf.log(self.pred), reduction_indices=1))
I noticed that tf.clip_by_value(self.pred, 1e-15, 1.0)
was used to avoid log(0). However, tf.clip_by_value
will not change the value in self.pred
. We need to get the return value of the clip function and re-assign it to self.pred
Making the following changes may get rid of NAN:
self.pred = tf.clip_by_value(self.pred, 1e-15, 1.0)
cross_entropy = tf.reduce_mean(-tf.reduce_sum(self.y*tf.log(self.pred), reduction_indices=1))
Hope to hear from you ~
Thanks in advance! : )
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