sdca_ops.py 文件源码

def _l2_loss(self, l2):
    """Computes the (un-normalized) l2 loss of the model."""
    with name_scope('sdca/l2_loss'):
      sums = []
      for name in ['sparse_features_weights', 'dense_features_weights']:
        for weights in self._convert_n_to_tensor(self._variables[name]):
          with ops.device(weights.device):
            sums.append(
                math_ops.reduce_sum(
                    math_ops.square(math_ops.cast(weights, dtypes.float64))))
      sum = math_ops.add_n(sums)
      # SDCA L2 regularization cost is: l2 * sum(weights^2) / 2
      return l2 * sum / 2.0