This is my class for implementing logistic regression and a code to instantiate this class.
 class LogisticRegression(torch.nn.Module):
     def __init__(self, input_dim):
        super(LogisticRegression, self).__init__()
        self.linear = torch.nn.Linear(input_dim, 1)
        #self.linear = torch.nn.Linear(2*input_dim, output_dim)
        #raise NotImplementedError()

    def forward(self, x):
        outputs = self.linear(x)
        outputs = nn.Sigmoid(outputs)
        return outputs


model = LogisticRegression(input_dim)

criterion = torch.nn.CrossEntropyLoss() 

optimizer = torch.optim.SGD(model.parameters(), lr=lr_rate)


output=model(data_X)

I am getting the following error, … I have passed only one argument to model, yet it is saying there is mismatch.
TypeError                                 Traceback (most recent call last)
 in ()
11         #print(data_X.shape, data_X.type())
12
—> 13         outputs = model(data_X)
14         labels = labels.squeeze_()
15         loss = criterion(outputs, labels)
1 frames
/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in call(self, *input, **kwargs)
539             result = self._slow_forward(*input, **kwargs)
540         else:
–> 541             result = self.forward(*input, **kwargs)
542         for hook in self._forward_hooks.values():
543             hook_result = hook(self, input, result)
 in forward(self, x)
17     def forward(self, x):
18         outputs = self.linear(x)
—> 19         outputs = nn.Sigmoid(outputs)
20         return outputs
TypeError: init() takes 1 positional argument but 2 were given
Any help is much appreciated.