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Mac tensorflow mnist实例
Hello~
Thank you very much for sharing the code!
I try to use my own data set ( with the same shape as mnist) in code. 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_mnist/tensorflow_mnist.py
cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_*tf.log(y), reduction_indices = [1]))
If y contains 0 (output of softmax ), the result of tf.log(y)
is inf
because log(0)
is illegal . And this may cause the result of loss to become NAN.
It could be fixed by making the following changes:
cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_*tf.log(y + 1e-10), reduction_indices = [1]))
or
cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_*tf.log(tf.clip_by_value(y,1e-10,1.0)), reduction_indices = [1]))
Hope to hear from you ~
Thanks in advance! : )
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