AssertionError assert input.size(0) == target.size(0)

[Liuxueyi]

[rank0]: Traceback (most recent call last):
[rank0]: File "./adzoo/vad/train_momad.py", line 242, in
[rank0]: main()
[rank0]: File "./adzoo/vad/train_momad.py", line 231, in main
[rank0]: custom_train_model(
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/adzoo/bevformer/mmdet3d_plugin/bevformer/apis/train.py", line 25, in custom_train_model
[rank0]: custom_train_detector(
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/adzoo/bevformer/mmdet3d_plugin/bevformer/apis/mmdet_train.py", line 202, in custom_train_detector
[rank0]: runner.run(data_loaders, cfg.workflow)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/runner/epoch_based_runner.py", line 129, in run
[rank0]: epoch_runner(data_loaders[i], **kwargs)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/runner/epoch_based_runner.py", line 51, in train
[rank0]: self.run_iter(data_batch, train_mode=True, **kwargs)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/runner/epoch_based_runner.py", line 31, in run_iter
[rank0]: outputs = self.model(data_batch, return_loss=train_mode, **kwargs)
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
[rank0]: return self._call_impl(*args, **kwargs)
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
[rank0]: return forward_call(*args, **kwargs)
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/parallel/distributed.py", line 1636, in forward
[rank0]: else self._run_ddp_forward(*inputs, **kwargs)
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/parallel/distributed.py", line 1454, in _run_ddp_forward
[rank0]: return self.module(*inputs, **kwargs) # type: ignore[index]
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
[rank0]: return self._call_impl(*args, **kwargs)
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
[rank0]: return forward_call(*args, **kwargs)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/models/detectors/MomAD.py", line 171, in forward
[rank0]: losses = self.forward_train(**inputs)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/utils/fp16_utils.py", line 185, in new_func
[rank0]: return old_func(*args, **kwargs)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/models/detectors/MomAD.py", line 261, in forward_train
[rank0]: losses_pts = self.forward_pts_train(img_feats, gt_bboxes_3d, gt_labels_3d,
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/models/detectors/MomAD.py", line 151, in forward_pts_train
[rank0]: losses = self.pts_bbox_head.loss(*loss_inputs, img_metas=img_metas)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/utils/fp16_utils.py", line 185, in new_func
[rank0]: return old_func(*args, **kwargs)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/models/dense_heads/MomAD_head.py", line 1874, in loss
[rank0]: loss_planning_dict = self.loss_planning(*loss_plan_input)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/models/dense_heads/MomAD_head.py", line 1306, in loss_planning
[rank0]: cls_loss = self.loss_plan_cls(ego_fut_classification.flatten(end_dim=1),
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
[rank0]: return self._call_impl(*args, **kwargs)
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
[rank0]: return forward_call(*args, **kwargs)
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/models/losses/focal_loss.py", line 170, in forward
[rank0]: loss_cls = self.loss_weight * calculate_loss_func(
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/models/losses/focal_loss.py", line 85, in sigmoid_focal_loss
[rank0]: loss = _sigmoid_focal_loss(pred.contiguous(), target, gamma, alpha, None,
[rank0]: File "/data/liuxy/mamba/envs/momad/lib/python3.8/site-packages/torch/autograd/function.py", line 574, in apply
[rank0]: return super().apply(*args, **kwargs) # type: ignore[misc]
[rank0]: File "/data/liuxy/b2d/MomAD/close_loop/VAD_MomAD/Bench2DriveZoo/mmcv/ops/focal_loss.py", line 40, in forward
[rank0]: assert input.size(0) == target.size(0)
[rank0]: AssertionError