Hello, I am new to machine learning and pytorch so I am starting with linear regression.

This is my code:

```
class LinearRegressionModel(torch.nn.Module):
def __init__(self):
super(LinearRegressionModel, self).__init__()
self.linear = torch.nn.Linear(4, 1) # four input and one output
def forward(self, x):
y_pred = self.linear(x)
return y_pred
our_model = LinearRegressionModel()
#changed size_average = False to reduction = 'sum' because of depracated value
criterion = torch.nn.MSELoss(reduction = 'sum')
optimizer = torch.optim.SGD(our_model.parameters(), lr = 0.01)
#running into issue with data being either double or float
#converted all data into float
for epoch in range(500):
pred_y = our_model(X)
loss = criterion(pred_y, ynew)
optimizer.zero_grad()
loss.backward()
optimizer.step()
print('epoch {}, loss {}'.format(epoch, loss.item()))
```

I keep getting returned Nan even when the LR is reduced to increased or when the number of epochs is increased.