WIT: Fill in index labels when classification labels are blank

tensorboard/plugins/interactive_inference/tf_interactive_inference_dashboard/tf-interactive-inference-dashboard.html

@@ -2842,6 +2842,13 @@ <h2>Create a distance feature</h2>
         for (let i = 0; i < this.inferences.indices.length; i++) {
           if (isClassification) {
             const result = this.inferences.results.classificationResult;
+            // For models that don't return any labels for the classes, fill
+            // them out with class indicies.
+            for (let j = 0; j < result.classifications[i].classes.length; j++) {
+              if (result.classifications[i].classes[j].label == '') {
+                result.classifications[i].classes[j].label = j.toString();
+              }
+            }
             inferenceMap[this.inferences.indices[i]] =
                 result.classifications[i].classes.sort((a, b) => b.score - a.score);
           } else {

tensorboard/plugins/interactive_inference/utils/inference_utils.py

@@ -506,7 +506,11 @@ def make_json_formatted_for_single_chart(mutant_features,
         inference_result_proto.result.classifications)
     for mutant_feature, classification in zip(
         mutant_features, inference_result_proto.result.classifications):
-      for classification_class in classification.classes:
+      for class_index, classification_class in enumerate(
+        classification.classes):
+        # Fill in class index when labels are missing
+        if classification_class.label == '':
+          classification_class.label = str(class_index)
         # Special case to not include the "0" class in binary classification.
         # Since that just results in a chart that is symmetric around 0.5.
         if len(