only compute vlr region when distill (#7437)

configs/slim/distill/gfl_ld_distill.yml

@@ -15,3 +15,11 @@ ResNet:
   freeze_at: 0
   return_idx: [1,2,3]
   num_stages: 4
+
+TrainReader:
+  batch_transforms:
+  - PadBatch: {pad_to_stride: 32}
+  - Gt2GFLTarget:
+      downsample_ratios: [8, 16, 32, 64, 128]
+      grid_cell_scale: 8
+      compute_vlr_region: True
\ No newline at end of file

ppdet/data/transform/batch_operators.py

@@ -500,12 +500,14 @@ class Gt2GFLTarget(BaseOperator):
                  num_classes=80,
                  downsample_ratios=[8, 16, 32, 64, 128],
                  grid_cell_scale=4,
-                 cell_offset=0):
+                 cell_offset=0,
+                 compute_vlr_region=False):
         super(Gt2GFLTarget, self).__init__()
         self.num_classes = num_classes
         self.downsample_ratios = downsample_ratios
         self.grid_cell_scale = grid_cell_scale
         self.cell_offset = cell_offset
+        self.compute_vlr_region = compute_vlr_region
 
         self.assigner = ATSSAssigner()
 
@@ -585,9 +587,11 @@ class Gt2GFLTarget(BaseOperator):
                                               gt_bboxes, gt_bboxes_ignore,
                                               gt_labels)
 
-            vlr_region = self.assigner.get_vlr_region(
-                grid_cells, num_level_cells, gt_bboxes, gt_bboxes_ignore,
-                gt_labels)
+            if self.compute_vlr_region:
+                vlr_region = self.assigner.get_vlr_region(
+                    grid_cells, num_level_cells, gt_bboxes, gt_bboxes_ignore,
+                    gt_labels)
+                sample['vlr_regions'] = vlr_region
 
             pos_inds, neg_inds, pos_gt_bboxes, pos_assigned_gt_inds = self.get_sample(
                 assign_gt_inds, gt_bboxes)
@@ -615,7 +619,6 @@ class Gt2GFLTarget(BaseOperator):
             sample['label_weights'] = label_weights
             sample['bbox_targets'] = bbox_targets
             sample['pos_num'] = max(pos_inds.size, 1)
-            sample['vlr_regions'] = vlr_region
             sample.pop('is_crowd', None)
             sample.pop('difficult', None)
             sample.pop('gt_class', None)