TypeError: SequentialWithIdx.forward() missing 1 required positional argument: 'indices'"

[KumoLiu]

Describe the bug
Quicknat not work as expected.

To Reproduce

from monai.networks.nets import Quicknat
import torch

model = Quicknat(
            num_classes=1,
            num_channels=1,
            num_filters=64,
            se_block=None
        ).to("cuda:0")
data = torch.rand((1, 1, 32, 32)).to("cuda:0")

out = model(data)

Error Log

{
	"name": "TypeError",
	"message": "SequentialWithIdx.forward() missing 1 required positional argument: 'indices'",
	"stack": "---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[2], line 14
      5 model = Quicknat(
      6             num_classes=1,
      7             num_channels=1,
   (...)
     10             se_block=None
     11         ).to(\"cuda:0\")
     12 data = torch.rand((1, 1, 32, 32)).to(\"cuda:0\")
---> 14 out = model(data)
     17 # export
     18 # convert_to_onnx(model, dataloader, filename='quicknat.onnx', verify=True, use_ort=True)

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1511, in Module._wrapped_call_impl(self, *args, **kwargs)
   1509     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   1510 else:
-> 1511     return self._call_impl(*args, **kwargs)

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1520, in Module._call_impl(self, *args, **kwargs)
   1515 # If we don't have any hooks, we want to skip the rest of the logic in
   1516 # this function, and just call forward.
   1517 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   1518         or _global_backward_pre_hooks or _global_backward_hooks
   1519         or _global_forward_hooks or _global_forward_pre_hooks):
-> 1520     return forward_call(*args, **kwargs)
   1522 try:
   1523     result = None

File /workspace/MONAI/monai/networks/nets/quicknat.py:438, in Quicknat.forward(self, input)
    437 def forward(self, input: torch.Tensor) -> torch.Tensor:
--> 438     input, _ = self.model(input, None)
    439     return input

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1511, in Module._wrapped_call_impl(self, *args, **kwargs)
   1509     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   1510 else:
-> 1511     return self._call_impl(*args, **kwargs)

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1520, in Module._call_impl(self, *args, **kwargs)
   1515 # If we don't have any hooks, we want to skip the rest of the logic in
   1516 # this function, and just call forward.
   1517 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   1518         or _global_backward_pre_hooks or _global_backward_hooks
   1519         or _global_forward_hooks or _global_forward_pre_hooks):
-> 1520     return forward_call(*args, **kwargs)
   1522 try:
   1523     result = None

File /workspace/MONAI/monai/networks/nets/quicknat.py:62, in SequentialWithIdx.forward(self, input, indices)
     60 def forward(self, input, indices):
     61     for module in self:
---> 62         input, indices = module(input, indices)
     63     return input, indices

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1511, in Module._wrapped_call_impl(self, *args, **kwargs)
   1509     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   1510 else:
-> 1511     return self._call_impl(*args, **kwargs)

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1520, in Module._call_impl(self, *args, **kwargs)
   1515 # If we don't have any hooks, we want to skip the rest of the logic in
   1516 # this function, and just call forward.
   1517 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   1518         or _global_backward_pre_hooks or _global_backward_hooks
   1519         or _global_forward_hooks or _global_forward_pre_hooks):
-> 1520     return forward_call(*args, **kwargs)
   1522 try:
   1523     result = None

File /workspace/MONAI/monai/networks/nets/quicknat.py:46, in SkipConnectionWithIdx.forward(self, input, indices)
     45 def forward(self, input, indices):
---> 46     return super().forward(input), indices

File /workspace/MONAI/monai/networks/layers/simplelayers.py:129, in SkipConnection.forward(self, x)
    128 def forward(self, x: torch.Tensor) -> torch.Tensor:
--> 129     y = self.submodule(x)
    131     if self.mode == \"cat\":
    132         return torch.cat([x, y], dim=self.dim)

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1511, in Module._wrapped_call_impl(self, *args, **kwargs)
   1509     return self._compiled_call_impl(*args, **kwargs)  # type: ignore[misc]
   1510 else:
-> 1511     return self._call_impl(*args, **kwargs)

File /usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py:1520, in Module._call_impl(self, *args, **kwargs)
   1515 # If we don't have any hooks, we want to skip the rest of the logic in
   1516 # this function, and just call forward.
   1517 if not (self._backward_hooks or self._backward_pre_hooks or self._forward_hooks or self._forward_pre_hooks
   1518         or _global_backward_pre_hooks or _global_backward_hooks
   1519         or _global_forward_hooks or _global_forward_pre_hooks):
-> 1520     return forward_call(*args, **kwargs)
   1522 try:
   1523     result = None

TypeError: SequentialWithIdx.forward() missing 1 required positional argument: 'indices'"
}

Quicknat is introduced by this PR.
Looks like the unit tests are always not tested since squeeze_and_excitation is not a required dependency.

MONAI/tests/test_quicknat.py

Line 39 in ff43028

@unittest.skipUnless(has_se, "squeeze_and_excitation not installed")

[KumoLiu]

Hi @vgonzalezd, @Al3xand1a, and @ge96lip, could you please help take a look at this issue?
Thanks in advance!