add accuracy metric and default to prior off, seems to not help anymore

score.py

@@ -11,6 +11,7 @@
 logger = logging.getLogger("Score")
 
 def print_scores(labels, predictions, classes):
+ accuracy = skm.accuracy_score(labels, predictions)
  report = skm.classification_report(
  labels, predictions,
  target_names=classes,
@@ -19,6 +20,7 @@ def print_scores(labels, predictions, classes):
  labels,
  predictions,
  average='macro')
+ logger.info("Accuracy {:.3f}".format(accuracy))
  logger.info("\n"+report)
  logger.info("Macro Average F1: {:.3f}".format(macro_scores[2]))
 
@@ -36,7 +38,7 @@ def load_model(model_path, is_verbose, batch_size):
 
  evl = evaler.Evaler(model_path, is_verbose,
  batch_size=batch_size,
- class_counts=ldr.class_counts)
+ class_counts=None)
 
  return evl, ldr