from tensorflow.contrib import metrics as metrics_lib

    result = {"loss": metrics_lib.streaming_mean(self._loss(
        logits, targets,
        weight_tensor=self._get_weight_tensor(features)))}

    # Adding default metrics
    if metrics is None and self._n_classes > 1:
      metrics = {"accuracy": metrics_lib.streaming_accuracy}

    if self._n_classes == 2:
      predictions = math_ops.sigmoid(logits)
      result["eval_auc"] = metrics_lib.streaming_auc(predictions, targets)

    if metrics:
      predictions = self._logits_to_predictions(logits, proba=False)
      result.update(self._run_metrics(predictions, targets, metrics,
                                      self._get_weight_tensor(features)))

    return result

  def _get_predict_ops(self, features):
