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.