easytorch-training - ERROR RuntimeError: Expected 2D (unbatched) or 3D (batched) input to conv1d, but got input of size: [8, 32, 207, 13]

[1154761334]

感谢老哥之前的回复，我现在重新调整了环境，但是还是遇到了一些问题，不知道之前您这边遇到过吗？

`2022-12-07 13:27:34,613 - easytorch-training - INFO - Epoch 1 / 100
0%| | 0/2997 [00:08<?, ?it/s]
2022-12-07 13:27:42,909 - easytorch-training - ERROR - Traceback (most recent call last):
File "D:\python-venv\STEP\venv2\lib\site-packages\easytorch\launcher\launcher.py", line 52, in training_func
runner.train(cfg)
File "D:\python-venv\STEP\venv2\lib\site-packages\easytorch\core\runner.py", line 351, in train
loss = self.train_iters(epoch, iter_index, data)
File "D:\python-venv\STEP\basicts\runners\base_tsf_runner.py", line 237, in train_iters
forward_return = list(self.forward(data=data, epoch=epoch, iter_num=iter_num, train=True))
File "D:\python-venv\STEP\step\step_runner\step_runner.py", line 66, in forward
prediction, pred_adj, prior_adj, gsl_coefficient = self.model(history_data=history_data, long_history_data=long_history_data, future_data=None, batch_seen=iter_num, epoch=epoch)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "D:\python-venv\STEP\step\step_arch\step.py", line 65, in forward
y_hat = self.backend(short_term_history, hidden_states=hidden_states, sampled_adj=sampled_adj).transpose(1, 2)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "D:\python-venv\STEP\step\step_arch\graphwavenet\model.py", line 197, in forward
gate = self.gate_convsi
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\conv.py", line 313, in forward
return self._conv_forward(input, self.weight, self.bias)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\conv.py", line 309, in _conv_forward
return F.conv1d(input, weight, bias, self.stride,
RuntimeError: Expected 2D (unbatched) or 3D (batched) input to conv1d, but got input of size: [8, 32, 207, 13]

Traceback (most recent call last):
File "D:\python-venv\STEP\step\run.py", line 27, in
launch_training(args.cfg, args.gpus)
File "D:\python-venv\STEP\basicts\launcher.py", line 19, in launch_training
easytorch.launch_training(cfg=cfg, gpus=gpus, node_rank=node_rank)
File "D:\python-venv\STEP\venv2\lib\site-packages\easytorch\launcher\launcher.py", line 93, in launch_training
train_dist(cfg)
File "D:\python-venv\STEP\venv2\lib\site-packages\easytorch\launcher\launcher.py", line 56, in training_func
raise e
File "D:\python-venv\STEP\venv2\lib\site-packages\easytorch\launcher\launcher.py", line 52, in training_func
runner.train(cfg)
File "D:\python-venv\STEP\venv2\lib\site-packages\easytorch\core\runner.py", line 351, in train
loss = self.train_iters(epoch, iter_index, data)
File "D:\python-venv\STEP\basicts\runners\base_tsf_runner.py", line 237, in train_iters
forward_return = list(self.forward(data=data, epoch=epoch, iter_num=iter_num, train=True))
File "D:\python-venv\STEP\step\step_runner\step_runner.py", line 66, in forward
prediction, pred_adj, prior_adj, gsl_coefficient = self.model(history_data=history_data, long_history_data=long_history_data, future_data=None, batch_seen=iter_num, epoch=epoch)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "D:\python-venv\STEP\step\step_arch\step.py", line 65, in forward
y_hat = self.backend(short_term_history, hidden_states=hidden_states, sampled_adj=sampled_adj).transpose(1, 2)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "D:\python-venv\STEP\step\step_arch\graphwavenet\model.py", line 197, in forward
gate = self.gate_convsi
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\conv.py", line 313, in forward
return self._conv_forward(input, self.weight, self.bias)
File "D:\python-venv\STEP\venv2\lib\site-packages\torch\nn\modules\conv.py", line 309, in _conv_forward
return F.conv1d(input, weight, bias, self.stride,
RuntimeError: Expected 2D (unbatched) or 3D (batched) input to conv1d, but got input of size: [8, 32, 207, 13]
(venv2) PS D:\python-venv\STEP>
`

[zezhishao]

这个是torchc版本的问题，推荐使用1.10.0或者1.9.1，这俩我都测试过。更高版本的torch似乎不适配某些算子，就会导致出现这个问题。

[1154761334]

行了运行了一下程序：
(STEP) PS D:\python-venv\STEP> conda install pytorch==1.10.0 torchvision==0.11.0 torchaudio==0.10.0 cudatoolkit=11.3 -c conda-forge

pip install -r requirements.txt

[1154761334]

)
2022-12-07 15:07:14,588 - easytorch-training - INFO - Set lr_scheduler: <torch.optim.lr_scheduler.MultiStepLR object at 0x00000298A3100970>
2022-12-07 15:07:14,594 - easytorch-training - INFO - Initializing validation.
2022-12-07 15:07:14,594 - easytorch-training - INFO - Building val data loader.
val len: 3425
test len: 6850
2022-12-07 15:07:14,770 - easytorch-training - INFO - Epoch 1 / 100
31%|████████████████████████████████████████████████████████████████▌ | 935/2997 [06:52<14:51, 2.31it/s]

[zezhishao]

似乎已经顺利运行。

[wanjunhong0]

After torch 1.10, the kernel size of torch.nn.conv1d is restricted to 1d, which used to could take tuple. But intuitively, when the kernel is (1,1) 2D, it should be conv2d not conv1d, and pytorch changed that after 1.10.

The fix will be changing
nn.Conv1d(in_channels=dilation_channels, out_channels=skip_channels, kernel_size=(1, 1))
to
nn.Conv2d(in_channels=dilation_channels, out_channels=skip_channels, kernel_size=(1, 1))

[Polarstar671]

请问除了降版本没有其他方法了吗

[cypans]

graphwavenet.py中的3个nn.conv1d改成2d 就可以了