def __call__(self, inputs):
    with tf.name_scope(self.name):
        if (self.logging and (not self.sparse_inputs)):
            tf.summary.histogram((self.name + '/inputs'), inputs)
        outputs = self._call(inputs)
        if self.logging:
            tf.summary.histogram((self.name + '/outputs'), outputs)
        return outputs
def __call__(self, inputs):
    with tf.name_scope(self.name):
        if (self.logging and (not self.sparse_inputs)):
            tf.summary.histogram((self.name + '/inputs'), inputs)
        outputs = self._call(inputs)
        if self.logging:
            tf.summary.histogram((self.name + '/outputs'), outputs)
        return outputs