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I encountered an issue while trying to train the model on my custom dataset. The error message I received is as follows:
Traceback (most recent call last):
File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 302, in
launch(
File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/engine/launch.py", line 84, in launch
main_func(*args)
File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 295, in main
do_train(cfg, model, resume=args.resume)
File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 200, in do_train
optimizer.step()
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/optim/lr_scheduler.py", line 68, in wrapper
return wrapped(*args, **kwargs)
File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/solver/build.py", line 73, in optimizer_wgc_step
per_param_clipper(p)
File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/solver/build.py", line 46, in clip_grad_value
torch.nn.utils.clip_grad_value_(p, cfg.CLIP_VALUE)
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/nn/utils/clip_grad.py", line 122, in clip_grad_value_
grouped_grads = _group_tensors_by_device_and_dtype([grads])
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/utils/_foreach_utils.py", line 42, in _group_tensors_by_device_and_dtype
torch._C._group_tensors_by_device_and_dtype(tensorlistlist, with_indices).items()
RuntimeError: Expected nested_tensorlist[0].size() > 0 to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)
The text was updated successfully, but these errors were encountered:
I encountered an issue while trying to train the model on my custom dataset. The error message I received is as follows: Traceback (most recent call last): File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 302, in launch( File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/engine/launch.py", line 84, in launch main_func(*args) File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 295, in main do_train(cfg, model, resume=args.resume) File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 200, in do_train optimizer.step() File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/optim/lr_scheduler.py", line 68, in wrapper return wrapped(*args, **kwargs) File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/solver/build.py", line 73, in optimizer_wgc_step per_param_clipper(p) File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/solver/build.py", line 46, in clip_grad_value torch.nn.utils.clip_grad_value_(p, cfg.CLIP_VALUE) File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/nn/utils/clip_grad.py", line 122, in clip_grad_value_ grouped_grads = _group_tensors_by_device_and_dtype([grads]) File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(*args, **kwargs) File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/utils/_foreach_utils.py", line 42, in _group_tensors_by_device_and_dtype torch._C._group_tensors_by_device_and_dtype(tensorlistlist, with_indices).items() RuntimeError: Expected nested_tensorlist[0].size() > 0 to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)
the pytorch version should be <=2.0.1, and 2.0.1 is OK
I encountered an issue while trying to train the model on my custom dataset. The error message I received is as follows:
Traceback (most recent call last):
File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 302, in
launch(
File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/engine/launch.py", line 84, in launch
main_func(*args)
File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 295, in main
do_train(cfg, model, resume=args.resume)
File "/mnt/d/Pycharm_Projects/UniDet/train_net.py", line 200, in do_train
optimizer.step()
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/optim/lr_scheduler.py", line 68, in wrapper
return wrapped(*args, **kwargs)
File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/solver/build.py", line 73, in optimizer_wgc_step
per_param_clipper(p)
File "/mnt/d/Pycharm_Projects/detectron2-main/detectron2/solver/build.py", line 46, in clip_grad_value
torch.nn.utils.clip_grad_value_(p, cfg.CLIP_VALUE)
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/nn/utils/clip_grad.py", line 122, in clip_grad_value_
grouped_grads = _group_tensors_by_device_and_dtype([grads])
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/root/anaconda3/envs/Detectron2/lib/python3.10/site-packages/torch/utils/_foreach_utils.py", line 42, in _group_tensors_by_device_and_dtype
torch._C._group_tensors_by_device_and_dtype(tensorlistlist, with_indices).items()
RuntimeError: Expected nested_tensorlist[0].size() > 0 to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.)
The text was updated successfully, but these errors were encountered: