Error: assert len(module.recorded_input) > 0

[yourbikun]

Describe the bug

02/10 19:02:07 - mmengine - INFO - Checkpoints will be saved to /gemini/prun.
/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py:1053: UserWarning: Using a non-full backward hook when the forward contains multiple autograd Nodes is deprecated and will be removed in future versions. This hook will be missing some grad_input. Please use register_full_backward_hook to get the documented behavior.
warnings.warn("Using a non-full backward hook when the forward contains multiple autograd Nodes "
Traceback (most recent call last):
File "tools/train.py", line 121, in
main()
File "tools/train.py", line 117, in main
runner.train()
File "/usr/local/lib/python3.8/dist-packages/mmengine/runner/runner.py", line 1706, in train
model = self.train_loop.run() # type: ignore
File "/usr/local/lib/python3.8/dist-packages/mmengine/runner/loops.py", line 278, in run
self.run_iter(data_batch)
File "/usr/local/lib/python3.8/dist-packages/mmengine/runner/loops.py", line 301, in run_iter
outputs = self.runner.model.train_step(
File "/gemini/code/mmrazor/mmrazor/implementations/pruning/group_fisher/algorithm.py", line 61, in train_step
return self._train_step(data, optim_wrapper)
File "/gemini/code/mmrazor/mmrazor/implementations/pruning/group_fisher/algorithm.py", line 69, in _train_step
self.mutator.update_imp()
File "/gemini/code/mmrazor/mmrazor/implementations/pruning/group_fisher/mutator.py", line 82, in update_imp
unit.update_fisher_info()
File "/usr/local/lib/python3.8/dist-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/gemini/code/mmrazor/mmrazor/implementations/pruning/group_fisher/unit.py", line 144, in update_fisher_info
batch_fisher_sum = self.current_batch_fisher
File "/gemini/code/mmrazor/mmrazor/implementations/pruning/group_fisher/unit.py", line 158, in current_batch_fisher
fisher = fisher + self._fisher_of_a_module(module)
File "/usr/local/lib/python3.8/dist-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/gemini/code/mmrazor/mmrazor/implementations/pruning/group_fisher/unit.py", line 171, in _fisher_of_a_module
assert len(module.recorded_input) > 0 and \

[here]

To Reproduce

python tools/train.py /gemini/code/mmrazor/configs/pruning/mmdet/group_fisher/degnet/prun.py

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