could not create a primitive

[oscarramirezs]

hello

thanks guys for this work,,

I am working on a segmentation task using Swin UNETR, and after the first epoch I got the following error => RuntimeError: could not create a primitive`

`
1/1, train_loss: 0.7774
epoch 1 average loss: 0.7774

RuntimeError Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_2596\3568985229.py in
77 #roi_size = (256, 256, 192)
78 sw_batch_size = 1
---> 79 val_outputs = sliding_window_inference(
80 val_inputs, roi_size, sw_batch_size, model)
81 val_outputs = [post_pred(i) for i in decollate_batch(val_outputs)]

C:\ProgramData\Anaconda3\lib\site-packages\monai\inferers\utils.py in sliding_window_inference(inputs, roi_size, sw_batch_size, predictor, overlap, mode, sigma_scale, padding_mode, cval, sw_device, device, progress, roi_weight_map, *args, **kwargs)
178 [convert_data_type(inputs[win_slice], torch.Tensor)[0] for win_slice in unravel_slice]
179 ).to(sw_device)
--> 180 seg_prob_out = predictor(window_data, *args, **kwargs) # batched patch segmentation
181
182 # convert seg_prob_out to tuple seg_prob_tuple, this does not allocate new memory.

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
1188 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1189 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1190 return forward_call(*input, **kwargs)
1191 # Do not call functions when jit is used
1192 full_backward_hooks, non_full_backward_hooks = [], []

C:\ProgramData\Anaconda3\lib\site-packages\monai\networks\nets\swin_unetr.py in forward(self, x_in)
296 def forward(self, x_in):
297 hidden_states_out = self.swinViT(x_in, self.normalize)
--> 298 enc0 = self.encoder1(x_in)
299 enc1 = self.encoder2(hidden_states_out[0])
300 enc2 = self.encoder3(hidden_states_out[1])

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
1188 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1189 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1190 return forward_call(*input, **kwargs)
1191 # Do not call functions when jit is used
1192 full_backward_hooks, non_full_backward_hooks = [], []

C:\ProgramData\Anaconda3\lib\site-packages\monai\networks\blocks\unetr_block.py in forward(self, inp)
256
257 def forward(self, inp):
--> 258 return self.layer(inp)

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
1188 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1189 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1190 return forward_call(*input, **kwargs)
1191 # Do not call functions when jit is used
1192 full_backward_hooks, non_full_backward_hooks = [], []

C:\ProgramData\Anaconda3\lib\site-packages\monai\networks\blocks\dynunet_block.py in forward(self, inp)
102 out = self.norm2(out)
103 if hasattr(self, "conv3"):
--> 104 residual = self.conv3(residual)
105 if hasattr(self, "norm3"):
106 residual = self.norm3(residual)

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
1188 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1189 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1190 return forward_call(*input, **kwargs)
1191 # Do not call functions when jit is used
1192 full_backward_hooks, non_full_backward_hooks = [], []

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\container.py in forward(self, input)
202 def forward(self, input):
203 for module in self:
--> 204 input = module(input)
205 return input
206

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
1188 if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
1189 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1190 return forward_call(*input, **kwargs)
1191 # Do not call functions when jit is used
1192 full_backward_hooks, non_full_backward_hooks = [], []

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\conv.py in forward(self, input)
611
612 def forward(self, input: Tensor) -> Tensor:
--> 613 return self._conv_forward(input, self.weight, self.bias)
614
615

C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\conv.py in _conv_forward(self, input, weight, bias)
606 self.groups,
607 )
--> 608 return F.conv3d(
609 input, weight, bias, self.stride, self.padding, self.dilation, self.groups
610 )

RuntimeError: could not create a primitive`

thank you for your help

Oscar

[tangy5]

Is this error occurs when running model on cpu device? Based on some references, it could be a limitation of specific CPU instructions, could you try confirm, if so, can you try run it on GPU? And if the problem still exists, a sample code for reproducing the error will be helpful for the team to dig into it.

Thanks!