change the NaN value to 'NaN' string for json format

mindinsight/explainer/manager/explain_loader.py

@@ -14,6 +14,7 @@
 # ============================================================================
 """ExplainLoader."""
 
+import math
 import os
 import re
 from collections import defaultdict
@@ -27,6 +28,7 @@ from mindinsight.datavisual.data_access.file_handler import FileHandler
 from mindinsight.datavisual.common.exceptions import TrainJobNotExistError
 from mindinsight.utils.exceptions import ParamValueError, UnknownError
 
+_NAN_CONSTANT = 'NaN'
 _NUM_DIGITS = 6
 
 _EXPLAIN_FIELD_NAMES = [
@@ -44,7 +46,10 @@ _SAMPLE_FIELD_NAMES = [
 
 def _round(score):
     """Take round of a number to given precision."""
-    return round(score, _NUM_DIGITS)
+    try:
+        return round(score, _NUM_DIGITS)
+    except TypeError:
+        return score
 
 
 class ExplainLoader:
@@ -405,7 +410,7 @@ class ExplainLoader:
             metric_score = benchmark.total_score
             label_score_event = benchmark.label_score
 
-            explainer_score[explainer][metric] = metric_score
+            explainer_score[explainer][metric] = _NAN_CONSTANT if math.isnan(metric_score) else metric_score
             new_label_score_dict = ExplainLoader._score_event_to_dict(label_score_event, metric)
             for label, scores_of_metric in new_label_score_dict.items():
                 if label not in label_score[explainer]:
@@ -551,5 +556,5 @@ class ExplainLoader:
         """Transfer metric scores per label to pre-defined structure."""
         new_label_score_dict = defaultdict(dict)
         for label_id, label_score in enumerate(label_score_event):
-            new_label_score_dict[label_id][metric] = label_score
+            new_label_score_dict[label_id][metric] = _NAN_CONSTANT if math.isnan(label_score) else label_score
         return new_label_score_dict