bug fix

core/metric.py

@@ -23,11 +23,13 @@ class Metric(object):
     __metaclass__ = abc.ABCMeta
 
     def __init__(self, config):
-        """ """
+        """R
+        """
         pass
 
     def clear(self, scope=None):
-        """ """
+        """R
+        """
         if scope is None:
             scope = fluid.global_scope()
 
@@ -41,9 +43,13 @@ class Metric(object):
             data_array = np.zeros(var._get_dims()).astype(dtype)
             var.set(data_array, place)
 
-    def get_global_metric_state(self, fleet, scope, metric_name, mode="sum"):
-        """ """
-        input = np.array(scope.find_var(metric_name).get_tensor())
+    def _get_global_metric_state(self, fleet, scope, metric_name, mode="sum"):
+        """R
+        """
+        var = scope.find_var(metric_name)
+        if not var:
+            return None
+        input = np.array(var.get_tensor())
         if fleet is None:
             return input
         fleet._role_maker._barrier_worker()
@@ -54,8 +60,9 @@ class Metric(object):
         output = output.reshape(old_shape)
         return output
 
-    def cal_global_metrics(self, fleet, scope=None):
-        """ """
+    def calc_global_metrics(self, fleet, scope=None):
+        """R
+        """
         if scope is None:
             scope = fluid.global_scope()
 
@@ -65,9 +72,9 @@ class Metric(object):
             global_metrics[key] = self.get_global_metric_state(fleet, scope,
                                                                varname)
 
-        return self.calculate(global_metrics)
+        return self._calculate(global_metrics)
 
-    def calculate(self, global_metrics):
+    def _calculate(self, global_metrics):
         pass
 
     @abc.abstractmethod

core/metrics/binary_class/auc.py

@@ -74,7 +74,7 @@ class AUC(Metric):
         self.metrics["AUC"] = auc_out
         self.metrics["BATCH_AUC"] = batch_auc_out
 
-    def calculate_bucket_error(self, global_pos, global_neg):
+    def _calculate_bucket_error(self, global_pos, global_neg):
         """R
         """
         num_bucket = len(global_pos)
@@ -122,7 +122,7 @@ class AUC(Metric):
         bucket_error = error_sum / error_count if error_count > 0 else 0.0
         return bucket_error
 
-    def calculate_auc(self, global_pos, global_neg):
+    def _calculate_auc(self, global_pos, global_neg):
         """R
         """
         num_bucket = len(global_pos)
@@ -148,7 +148,7 @@ class AUC(Metric):
             auc_value = area / (pos * neg)
         return auc_value
 
-    def calculate(self, global_metrics):
+    def _calculate(self, global_metrics):
         result = dict()
         for key in self._global_metric_state_vars:
             if key not in global_metrics:
@@ -165,10 +165,10 @@ class AUC(Metric):
             result['copc'] = 0
             result['mean_q'] = 0
         else:
-            result['auc'] = self.calculate_auc(result['stat_pos'],
-                                               result['stat_neg'])
-            result['bucket_error'] = self.calculate_auc(result['stat_pos'],
-                                                        result['stat_neg'])
+            result['auc'] = self._calculate_auc(result['stat_pos'],
+                                                result['stat_neg'])
+            result['bucket_error'] = self._calculate_bucket_error(
+                result['stat_pos'], result['stat_neg'])
             result['actual_ctr'] = result['pos_ins_num'] / result[
                 'total_ins_num']
             result['mae'] = result['abserr'] / result['total_ins_num']

core/metrics/binary_class/precision_recall.py

@@ -29,7 +29,8 @@ class PrecisionRecall(Metric):
     """
 
     def __init__(self, **kwargs):
-        """ """
+        """R
+        """
         if "input" not in kwargs or "label" not in kwargs or "class_num" not in kwargs:
             raise ValueError(
                 "PrecisionRecall expect input, label and class_num as inputs.")
@@ -107,9 +108,7 @@ class PrecisionRecall(Metric):
         self.metrics["precision_recall_f1"] = accum_metrics
         self.metrics["[TP FP TN FN]"] = states_info
 
-    # self.metrics["batch_metrics"] = batch_metrics
-
-    def calculate(self, global_metrics):
+    def _calculate(self, global_metrics):
         for key in self._global_metric_state_vars:
             if key not in global_metrics:
                 raise ValueError("%s not existed" % key)

core/metrics/pairwise_pn.py

@@ -84,7 +84,7 @@ class PosNegRatio(Metric):
         self.metrics['RightCnt'] = global_right_cnt
         self.metrics['PN'] = self.pn
 
-    def calculate(self, global_metrics):
+    def _calculate(self, global_metrics):
         for key in self._global_communicate_var:
             if key not in global_metrics:
                 raise ValueError("%s not existed" % key)

core/metrics/recall_k.py

@@ -88,7 +88,7 @@ class RecallK(Metric):
         self.metrics[metric_name] = self.acc
 
     # self.metrics["batch_metrics"] = batch_metrics
-    def calculate(self, global_metrics):
+    def _calculate(self, global_metrics):
         for key in self._global_metric_state_vars:
             if key not in global_metrics:
                 raise ValueError("%s not existed" % key)

core/trainers/framework/runner.py

@@ -356,7 +356,7 @@ class SingleRunner(RunnerBase):
                 metrics_result = []
                 for key in metrics:
                     if isinstance(metrics[key], Metric):
-                        _str = metrics[key].cal_global_metrics(
+                        _str = metrics[key].calc_global_metrics(
                             None,
                             context["model"][model_dict["name"]]["scope"])
                         metrics_result.append(_str)
@@ -404,7 +404,7 @@ class PSRunner(RunnerBase):
                 metrics_result = []
                 for key in metrics:
                     if isinstance(metrics[key], Metric):
-                        _str = metrics[key].cal_global_metrics(
+                        _str = metrics[key].calc_global_metrics(
                             context["fleet"],
                             context["model"][model_dict["name"]]["scope"])
                         metrics_result.append(_str)
@@ -536,7 +536,7 @@ class SingleInferRunner(RunnerBase):
                 metrics_result = []
                 for key in metrics:
                     if isinstance(metrics[key], Metric):
-                        _str = metrics[key].cal_global_metrics(
+                        _str = metrics[key].calc_global_metrics(
                             None,
                             context["model"][model_dict["name"]]["scope"])
                         metrics_result.append(_str)