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when I changed the warmup steps from 300 to 30, an error occurred.
See original GitHub issueTraceback (most recent call last):
File "tools/train.py", line 92, in <module>
main(args)
File "tools/train.py", line 87, in main
trainer.run(train_dataloader, val_dataloader, evaluator)
File "/zzz/prj/nanodet/nanodet/trainer/trainer.py", line 123, in run
self.warm_up(train_loader)
File "/zzz/prj/nanodet/nanodet/trainer/trainer.py", line 191, in warm_up
output, loss, loss_stats = self.run_step(model, batch)
File "/zzz/prj/nanodet/nanodet/trainer/trainer.py", line 57, in run_step
loss.backward()
File "/usr/local/lib/python3.6/dist-packages/torch/tensor.py", line 221, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/usr/local/lib/python3.6/dist-packages/torch/autograd/__init__.py", line 132, in backward
allow_unreachable=True) # allow_unreachable flag
RuntimeError: element 0 of tensors does not require grad and does not have a grad_fn
Issue Analytics
- State:
- Created 3 years ago
- Comments:5 (2 by maintainers)
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I ran into the similar issue. Solved it by add “requires_grad=True” in the three lines. https://github.com/RangiLyu/nanodet/blob/5a7a50108d4c6815fc4bbcc382d08c8679143449/nanodet/model/head/gfl_head.py#L306-L308
Thanks. This bug has fixed in commit a444d72