hiyoung123 / SoftMaskedBert

Soft-Masked Bert 复现论文:https://arxiv.org/pdf/2005.07421.pdf
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RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: #8

Closed qq596588073 closed 4 years ago

qq596588073 commented 4 years ago

Start train 0 ford Calling BertTokenizer.from_pretrained() with the path to a single file or url is deprecated {'epoch': 0, 'iter': 0, 'avg_loss': 8.148957252502441, 'avg_acc': 0.0, 'loss': 8.148957252502441} EP_train:0: 0% 1/1723 [00:36<17:17:03, 36.13s/it]Traceback (most recent call last): File "train.py", line 182, in trainer.train(train_data_loader, e) File "train.py", line 33, in train return self.iteration(epoch, train_data) File "train.py", line 79, in iteration loss.backward(retain_graph=True) File "/usr/local/lib/python3.6/dist-packages/torch/tensor.py", line 198, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph) File "/usr/local/lib/python3.6/dist-packages/torch/autograd/init.py", line 100, in backward allow_unreachable=True) # allow_unreachable flag RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [768]] is at version 3; expected version 2 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True). EP_train:0: 0% 1/1723 [01:10<33:33:36, 70.16s/it] 一直出现这个问题,请问您有什么好的解决办法嘛

Dioxideme commented 4 years ago

你好,请问可以分享以下数据集吗

qq596588073 commented 4 years ago

你好,请问可以分享以下数据集吗

我的名字就是我的qq,加我发给你

XiaoxueGu commented 4 years ago

Start train 0 ford Calling BertTokenizer.from_pretrained() with the path to a single file or url is deprecated {'epoch': 0, 'iter': 0, 'avg_loss': 8.148957252502441, 'avg_acc': 0.0, 'loss': 8.148957252502441} EP_train:0: 0% 1/1723 [00:36<17:17:03, 36.13s/it]Traceback (most recent call last): File "train.py", line 182, in trainer.train(train_data_loader, e) File "train.py", line 33, in train return self.iteration(epoch, train_data) File "train.py", line 79, in iteration loss.backward(retain_graph=True) File "/usr/local/lib/python3.6/dist-packages/torch/tensor.py", line 198, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph) File "/usr/local/lib/python3.6/dist-packages/torch/autograd/init.py", line 100, in backward allow_unreachable=True) # allow_unreachable flag RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [768]] is at version 3; expected version 2 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True). EP_train:0: 0% 1/1723 [01:10<33:33:36, 70.16s/it] 一直出现这个问题,请问您有什么好的解决办法嘛

请问问题解决了么?我也出了这个问题。在本地跑正常,服务器上就会报错。本地pytorch版本1.4.0,服务器1.5.0

qq596588073 commented 4 years ago

Start train 0 ford Calling BertTokenizer.from_pretrained() with the path to a single file or url is deprecated {'epoch': 0, 'iter': 0, 'avg_loss': 8.148957252502441, 'avg_acc': 0.0, 'loss': 8.148957252502441} EP_train:0: 0% 1/1723 [00:36<17:17:03, 36.13s/it]Traceback (most recent call last): File "train.py", line 182, in trainer.train(train_data_loader, e) File "train.py", line 33, in train return self.iteration(epoch, train_data) File "train.py", line 79, in iteration loss.backward(retain_graph=True) File "/usr/local/lib/python3.6/dist-packages/torch/tensor.py", line 198, in backward torch.autograd.backward(self, gradient, retain_graph, create_graph) File "/usr/local/lib/python3.6/dist-packages/torch/autograd/init.py", line 100, in backward allow_unreachable=True) # allow_unreachable flag RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [768]] is at version 3; expected version 2 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True). EP_train:0: 0% 1/1723 [01:10<33:33:36, 70.16s/it] 一直出现这个问题,请问您有什么好的解决办法嘛

请问问题解决了么?我也出了这个问题。在本地跑正常,服务器上就会报错。本地pytorch版本1.4.0,服务器1.5.0

这个我一直没有解决,我一直没有运行出来