问题遇到的现象和发生背景
复现CycN-Net时出现报错：RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation
用代码块功能插入代码，请勿粘贴截图
在loss.backward(retain_graph=True)处报错
Traceback (most recent call last):
File "/root/autodl-tmp/N-Net_and_CycNet-master/CycN-Net/main_train_CycNnet.py", line 158, in <module>
loss.backward(retain_graph=True)
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/_tensor.py", line 307, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/autograd/__init__.py", line 156, in backward
allow_unreachable=True, accumulate_grad=True) # allow_unreachable flag
运行结果及报错内容
第一行加入torch.set_grad_enabled(True)后，报错为
[W python_anomaly_mode.cpp:104] Warning: Error detected in PreluBackward0. Traceback of forward call that caused the error:
File "/root/autodl-tmp/N-Net_and_CycNet-master/CycN-Net/main_train_CycNnet.py", line 146, in <module>
prediction = model( img_seq_1, img_seq_2, img_seq_3, prior )
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/root/autodl-tmp/N-Net_and_CycNet-master/CycN-Net/model_CycNnet.py", line 302, in forward
out = self.finalconv(Tconv_7) # 508@16 --> 512@8 --> 512@1
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/nn/modules/container.py", line 141, in forward
input = module(input)
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/nn/modules/activation.py", line 1076, in forward
return F.prelu(input, self.weight)
File "/root/miniconda3/envs/my-env/lib/python3.6/site-packages/torch/nn/functional.py", line 1500, in prelu
return torch.prelu(input, weight)
(function _print_stack)
我的解答思路和尝试过的方法
搜索了PreluBackward0，但是没找到
