tensorflow_tutorials/deep_mnist/deep_mnist.py
def entropy(self):
        """The cross entropy between the model and true distribution."""
        if self._entropy is not None:
            return self._entropy

        self._entropy = (
            tf.reduce_mean(-1 * tf.reduce_sum(
                self.distribution * tf.log(self.model),
                axis=[1]))
        )

        return self._entropy
The cross entropy between the model and true distribution.
The cross entropy between the model and true distribution.
The cross entropy between the model and true distribution .
def entropy(self):
        if self._entropy is not None:
            return self._entropy
        self._entropy = (
            tf.reduce_mean(-1 * tf.reduce_sum(
                self.distribution * tf.log(self.model),
                axis=[1]))
        )
        return self._entropy
def entropy ( self ) : if self . _entropy is not None : return self . _entropy self . _entropy = ( tf . reduce_mean ( - 1 * tf . reduce_sum ( self . distribution * tf . log ( self . model ) , axis = [ 1 ] ) ) ) return self . _entropy
The cross entropy between the model and true distribution.
The cross entropy between the model and true distribution .
"""The cross entropy between the model and true distribution."""
self