model.py 文件源码

def _variable_with_weight_decay(self, name, shape, stddev, wd=None):
        """Helper to create an initialized Variable with weight decay.
        Note that the Variable is initialized with a truncated normal distribution.
        A weight decay is added only if one is specified.
        Args:
            name: name of the variable
            shape: list of ints
            stddev: standard deviation of a truncated Gaussian
            wd: add L2Loss weight decay multiplied by this float. If None, weight
                decay is not added for this Variable.
        Returns:
            Variable Tensor
        """
        var = self._variable_on_cpu(
            name,
            shape,
            tf.truncated_normal_initializer(stddev=stddev))
        if wd is not None:
            # weight_decay = tf.mul(tf.constant(0.1), wd, name='weight_loss')
            weight_decay = tf.mul(tf.nn.l2_loss(var), wd, name='weight_loss')
            tf.add_to_collection('losses', weight_decay)
            # tf.add_to_collection('losses', wd)
        return var