Fix nonzero warning (#330)

* fix nonzero warning with as_tuple * fix nonzero warning with as_tuple #320
open-mmlab · Mar 2, 2021 · df505fe · df505fe
1 parent ccd3047
commit df505fe
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Showing 6 changed files with 12 additions and 9 deletions.
diff --git a/docs/index.rst b/docs/index.rst
@@ -8,7 +8,7 @@ Welcome to MMDetection3D's documentation!
  getting_started.md
  model_zoo.md
  data_preparation.md
- 
+
 .. toctree::
  :maxdepth: 2
  :caption: Quick Run

diff --git a/mmdet3d/models/dense_heads/anchor3d_head.py b/mmdet3d/models/dense_heads/anchor3d_head.py
@@ -225,7 +225,8 @@ def loss_single(self, cls_score, bbox_pred, dir_cls_preds, labels,
 
  bg_class_ind = self.num_classes
  pos_inds = ((labels >= 0)
- & (labels < bg_class_ind)).nonzero().reshape(-1)
+ & (labels < bg_class_ind)).nonzero(
+ as_tuple=False).reshape(-1)
  num_pos = len(pos_inds)
 
  pos_bbox_pred = bbox_pred[pos_inds]

diff --git a/mmdet3d/models/dense_heads/ssd_3d_head.py b/mmdet3d/models/dense_heads/ssd_3d_head.py
@@ -519,7 +519,8 @@ def multiclass_nms_single(self, obj_scores, sem_scores, bbox, points,
 
  # filter empty boxes and boxes with low score
  scores_mask = (obj_scores >= self.test_cfg.score_thr)
- nonempty_box_inds = torch.nonzero(nonempty_box_mask).flatten()
+ nonempty_box_inds = torch.nonzero(
+ nonempty_box_mask, as_tuple=False).flatten()
  nonempty_mask = torch.zeros_like(bbox_classes).scatter(
  0, nonempty_box_inds[nms_selected], 1)
  selected = (nonempty_mask.bool() & scores_mask.bool())

diff --git a/mmdet3d/models/dense_heads/train_mixins.py b/mmdet3d/models/dense_heads/train_mixins.py
@@ -277,11 +277,11 @@ def anchor_target_single_assigner(self,
  neg_inds = sampling_result.neg_inds
  else:
  pos_inds = torch.nonzero(
- anchors.new_zeros((anchors.shape[0], ), dtype=torch.bool) > 0
- ).squeeze(-1).unique()
+ anchors.new_zeros((anchors.shape[0], ), dtype=torch.bool) > 0,
+  as_tuple=False).squeeze(-1).unique()
  neg_inds = torch.nonzero(
- anchors.new_zeros((anchors.shape[0], ), dtype=torch.bool) ==
- 0).squeeze(-1).unique()
+ anchors.new_zeros((anchors.shape[0], ), dtype=torch.bool) == 0,
+ as_tuple=False).squeeze(-1).unique()
 
  if gt_labels is not None:
  labels += num_classes

diff --git a/mmdet3d/models/roi_heads/bbox_heads/h3d_bbox_head.py b/mmdet3d/models/roi_heads/bbox_heads/h3d_bbox_head.py
@@ -525,7 +525,8 @@ def multiclass_nms_single(self, obj_scores, sem_scores, bbox, points,
 
  # filter empty boxes and boxes with low score
  scores_mask = (obj_scores > self.test_cfg.score_thr)
- nonempty_box_inds = torch.nonzero(nonempty_box_mask).flatten()
+ nonempty_box_inds = torch.nonzero(
+ nonempty_box_mask, as_tuple=False).flatten()
  nonempty_mask = torch.zeros_like(bbox_classes).scatter(
  0, nonempty_box_inds[nms_selected], 1)
  selected = (nonempty_mask.bool() & scores_mask.bool())

diff --git a/mmdet3d/models/roi_heads/mask_heads/primitive_head.py b/mmdet3d/models/roi_heads/mask_heads/primitive_head.py
@@ -369,7 +369,7 @@ def get_targets_single(self,
  pts_instance_mask[background_mask] = gt_labels_3d.shape[0]
 
  instance_flag = torch.nonzero(
- pts_semantic_mask != self.num_classes).squeeze(1)
+ pts_semantic_mask != self.num_classes, as_tuple=False).squeeze(1)
  instance_labels = pts_instance_mask[instance_flag].unique()
 
  with_yaw = gt_bboxes_3d.with_yaw