Point Density-Aware Voxels for LiDAR 3D Object Detection (CVPR 2022)
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RuntimeError: The expanded size of the tensor (8) must match the existing size (10) at non-singleton dimension 1. Target sizes: [128, 8]. Tensor sizes: [128, 10] #15
when I train PDV on waymo dataset, I meet this error.
The yaml file is "cfgs/waymo_models/pdv.yaml". I have cost much time on this.
error details:
Traceback (most recent call last):
File "train.py", line 232, in
main()
File "train.py", line 176, in main
train_model(
File "/home/rcvlab/lly/PDV/tools/train_utils/train_utils.py", line 86, in train_model
accumulated_iter = train_one_epoch(
File "/home/rcvlab/lly/PDV/tools/train_utils/train_utils.py", line 38, in train_one_epoch
loss, tb_dict, disp_dict = model_func(model, batch)
File "/home/rcvlab/lly/PDV/pcdet/models/init.py", line 42, in model_func
ret_dict, tb_dict, disp_dict = model(batch_dict)
File "/home/rcvlab/anaconda3/envs/lly_torch17/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, *kwargs)
File "/home/rcvlab/lly/PDV/pcdet/models/detectors/pdv.py", line 11, in forward
batch_dict = cur_module(batch_dict)
File "/home/rcvlab/anaconda3/envs/lly_torch17/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(input, **kwargs)
File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/pdv_head.py", line 239, in forward
targets_dict = self.assign_targets(batch_dict)
File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/roi_head_template.py", line 110, in assign_targets
targets_dict = self.proposal_target_layer.forward(batch_dict)
File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/target_assigner/proposal_target_layer.py", line 32, in forward
batch_rois, batch_gt_of_rois, batch_roi_ious, batch_roi_scores, batch_roi_labels = self.sample_rois_for_rcnn(
File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/target_assigner/proposal_target_layer.py", line 113, in sample_rois_for_rcnn
batch_gt_of_rois[index] = cur_gt[gt_assignment[sampled_inds]]
RuntimeError: The expanded size of the tensor (8) must match the existing size (10) at non-singleton dimension 1. Target sizes: [128, 8]. Tensor sizes: [128, 10]
when I train PDV on waymo dataset, I meet this error. The yaml file is "cfgs/waymo_models/pdv.yaml". I have cost much time on this.
error details: Traceback (most recent call last): File "train.py", line 232, in main() File "train.py", line 176, in main train_model( File "/home/rcvlab/lly/PDV/tools/train_utils/train_utils.py", line 86, in train_model accumulated_iter = train_one_epoch( File "/home/rcvlab/lly/PDV/tools/train_utils/train_utils.py", line 38, in train_one_epoch loss, tb_dict, disp_dict = model_func(model, batch) File "/home/rcvlab/lly/PDV/pcdet/models/init.py", line 42, in model_func ret_dict, tb_dict, disp_dict = model(batch_dict) File "/home/rcvlab/anaconda3/envs/lly_torch17/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(*input, *kwargs) File "/home/rcvlab/lly/PDV/pcdet/models/detectors/pdv.py", line 11, in forward batch_dict = cur_module(batch_dict) File "/home/rcvlab/anaconda3/envs/lly_torch17/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(input, **kwargs) File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/pdv_head.py", line 239, in forward targets_dict = self.assign_targets(batch_dict) File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/roi_head_template.py", line 110, in assign_targets targets_dict = self.proposal_target_layer.forward(batch_dict) File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/target_assigner/proposal_target_layer.py", line 32, in forward batch_rois, batch_gt_of_rois, batch_roi_ious, batch_roi_scores, batch_roi_labels = self.sample_rois_for_rcnn( File "/home/rcvlab/lly/PDV/pcdet/models/roi_heads/target_assigner/proposal_target_layer.py", line 113, in sample_rois_for_rcnn batch_gt_of_rois[index] = cur_gt[gt_assignment[sampled_inds]] RuntimeError: The expanded size of the tensor (8) must match the existing size (10) at non-singleton dimension 1. Target sizes: [128, 8]. Tensor sizes: [128, 10]