This error occurred when I calculated flops. What is the reason?

[fxooooooooo]

[12/11 22:09:15 adet.trainer]: Starting training from iteration 0
Traceback (most recent call last):
File "C:\Users\lin\Desktop\Cross_custom_dataset\tools\train_net.py", line 235, in
args=(args, ),
File "C:\Users\lin\Desktop\Cross_custom_dataset\detectron2\detectron2\engine\launch.py", line 82, in launch
main_func(*args)
File "C:\Users\lin\Desktop\Cross_custom_dataset\tools\train_net.py", line 223, in main
return trainer.train()
File "C:\Users\lin\Desktop\Cross_custom_dataset\tools\train_net.py", line 97, in train
self.train_loop(self.start_iter, self.max_iter)
File "C:\Users\lin\Desktop\Cross_custom_dataset\tools\train_net.py", line 87, in train_loop
self.run_step()
File "C:\Users\lin\Desktop\Cross_custom_dataset\detectron2\detectron2\engine\defaults.py", line 495, in run_step
self._trainer.run_step()
File "C:\Users\lin\Desktop\Cross_custom_dataset\detectron2\detectron2\engine\train_loop.py", line 274, in run_step
loss_dict = self.model(data)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "C:\Users\lin\Desktop\Cross_custom_dataset\adet\modeling\condinst\crossvis.py", line 140, in forward
return self.forward_train(batched_inputs)
File "C:\Users\lin\Desktop\Cross_custom_dataset\adet\modeling\condinst\crossvis.py", line 148, in forward_train
print("FLOPs: ", flops.total())
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\fvcore\nn\jit_analysis.py", line 248, in total
stats = self._analyze()
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\fvcore\nn\jit_analysis.py", line 551, in _analyze
graph = _get_scoped_trace_graph(self._model, self._inputs, self._aliases)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\fvcore\nn\jit_analysis.py", line 176, in _get_scoped_trace_graph
graph, _ = _get_trace_graph(module, inputs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\jit_trace.py", line 1139, in _get_trace_graph
outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\jit_trace.py", line 130, in forward
self._force_outplace,
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\jit_trace.py", line 116, in wrapper
outs.append(self.inner(*trace_inputs))
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\nn\modules\module.py", line 887, in _call_impl
result = self._slow_forward(*input, **kwargs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\nn\modules\module.py", line 860, in _slow_forward
result = self.forward(*input, **kwargs)
File "C:\Users\lin\Desktop\Cross_custom_dataset\adet\modeling\condinst\crossvis.py", line 140, in forward
return self.forward_train(batched_inputs)
File "C:\Users\lin\Desktop\Cross_custom_dataset\adet\modeling\condinst\crossvis.py", line 148, in forward_train
print("FLOPs: ", flops.total())
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\fvcore\nn\jit_analysis.py", line 248, in total
stats = self._analyze()
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\fvcore\nn\jit_analysis.py", line 551, in _analyze
graph = _get_scoped_trace_graph(self._model, self._inputs, self._aliases)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\fvcore\nn\jit_analysis.py", line 176, in _get_scoped_trace_graph
graph, _ = _get_trace_graph(module, inputs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\jit_trace.py", line 1139, in _get_trace_graph
outs = ONNXTracedModule(f, strict, _force_outplace, return_inputs, _return_inputs_states)(*args, **kwargs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\nn\modules\module.py", line 887, in _call_impl
result = self._slow_forward(*input, **kwargs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\nn\modules\module.py", line 860, in _slow_forward
result = self.forward(*input, **kwargs)
File "C:\Users\lin\anaconda3\envs\cross\lib\site-packages\torch\jit_trace.py", line 130, in forward
self._force_outplace,
RuntimeError: Tracing can't be nested

[ppwwyyxx]

FlopCounter cannot be used to count self inside a module. It has to be used outside the module.