You could create an own layer for that:
class PrintLayer(nn.Module):
    def __init__(self):
        super(PrintLayer, self).__init__()
    
    def forward(self, x):
        # Do your print / debug stuff here
        print(x)
        return x
    
model = nn.Sequential(
        nn.Linear(1, 5),
        PrintLayer(), # Add Print layer for debug
        nn.ReLU(),
        nn.Linear(5,1),
        nn.LogSigmoid(),
        )

x = Variable(torch.randn(10, 1))
output = model(x)

I hope this helps!