Getting TypeError: 'module' object is not callable in #41 lecture

[snehitha-t-m]

The x: torch.Tensor means that the forward() method is expecting x to be of type torch.Tensor.

And the -> torch.Tensor means that the forward() method returns a torch.Tensor too

torch.manual_seed(42)

#2 create an instance of the model / subclass of nn.Module
model_0 = LinearRegressionModel()

#3 checkout the parameters from the class / model
#list(model_0.parameters()) we can use this formula also. but if we need more clear output with named parameters we can use below one.
list(model_0.parameters())

TypeError Traceback (most recent call last)
/tmp/ipython-input-1580758094.py in <cell line: 0>()
2
3 #2 create an instance of the model / subclass of nn.Module
----> 4 model_0 = LinearRegressionModel()
5
6

/tmp/ipython-input-3563944508.py in init(self)
4
5 #initializing model parameters weight & bias.
----> 6 self.weight=nn.parameter(torch.randn(1, requires_grad=True, dtype=torch.float)) #here 1 means random weight. starts with random weight and try to adjust it to the ideal weight.
7 self.bias =nn.parameter(torch.randn(1, requires_grad=True, dtype=torch.float)) #requires_grad = True means pytorch will track the gradients of this specific parameter for use with torch.autograd & gradient descent. for many torch.nn modules, it is set by default..
8

TypeError: 'module' object is not callable

[snehitha-t-m]

Found the error. I used parameter (p is in lower case) instead of Parameter(P is in uppercase)