I’m getting this error from a simple CNN construction:

`RuntimeError: Expected 3-dimensional tensor, but got 5-dimensional tensor for argument #1 'self' (while checking arguments for avg_pool1d)`

I’m sure I implemented something wrong.

The CNN is defined:

```
class ConvNet1DPaper(nn.Module):
def __init__(self, num_classes=7):
super(ConvNet1DPaper, self).__init__()
self.cnn = nn.Sequential(
nn.Conv1d(1, 80, kernel_size=(100, 1, 1), stride=5),
nn.AvgPool1d(kernel_size=(3, 1, 1), stride=2),
nn.Conv1d(1, 80, kernel_size=(50, 1, 80), stride=5),
nn.AvgPool1d(kernel_size=(3, 1, 1), stride=1),
nn.Conv1d(1, 80, kernel_size=(25, 1, 80), stride=2),
nn.AvgPool1d(kernel_size=(3, 1, 1), stride=1),
nn.Flatten(1)
)
self.fc = nn.Sequential(
nn.Linear(880, 700),
nn.Linear(700, 70),
nn.Linear(70, num_classes))
def forward(self, x):
out = self.cnn(x)
out = self.fc(out)
return out
```