diff --git a/slim/prune/prune.py b/slim/prune/prune.py
index 4ccdb274af92c508ad7ea70269f748ec56be2934..d5fd5f8b35309405f00bfa428650417bd9d20489 100644
--- a/slim/prune/prune.py
+++ b/slim/prune/prune.py
@@ -34,7 +34,6 @@ from ppdet.utils.stats import TrainingStats
 from ppdet.utils.cli import ArgsParser
 from ppdet.utils.check import check_gpu, check_version
 import ppdet.utils.checkpoint as checkpoint
-from ppdet.modeling.model_input import create_feed
 
 import logging
 FORMAT = '%(asctime)s-%(levelname)s: %(message)s'
@@ -142,9 +141,9 @@ def main():
         if cfg.metric == 'COCO':
             extra_keys = ['im_info', 'im_id', 'im_shape']
         if cfg.metric == 'VOC':
-            extra_keys = ['gt_box', 'gt_label', 'is_difficult']
+            extra_keys = ['gt_bbox', 'gt_class', 'is_difficult']
         if cfg.metric == 'WIDERFACE':
-            extra_keys = ['im_id', 'im_shape', 'gt_box']
+            extra_keys = ['im_id', 'im_shape', 'gt_bbox']
         eval_keys, eval_values, eval_cls = parse_fetches(fetches, eval_prog,
                                                          extra_keys)
 
@@ -306,8 +305,14 @@ def main():
                 if 'mask' in results[0]:
                     resolution = model.mask_head.resolution
                 box_ap_stats = eval_results(
-                    results, eval_feed, cfg.metric, cfg.num_classes, resolution,
-                    is_bbox_normalized, FLAGS.output_eval, map_type)
+                    results,
+                    cfg.metric,
+                    cfg.num_classes,
+                    resolution,
+                    is_bbox_normalized,
+                    FLAGS.output_eval,
+                    map_type,
+                    dataset=dataset)
 
                 # use tb_paddle to log mAP
                 if FLAGS.use_tb: