linear regression model.py

class LinearRegressionModel(nn.Module):

    def __init__(self):
        super(LinearRegressionModel, self).__init__() 
        
        # init the layers
        self.layers = nn.Sequential(
            
            # input linear layer
            nn.Linear(1, 10),
            
            # "rectified linear unit" or "replace negatives with zeroes"
            nn.ReLU(inplace=True),
            
            # batch norm
            nn.BatchNorm1d(num_features=10),
            
            # output linear layer
            nn.Linear(10, 1)
        )
    
    # fastai passes both x_cat and x_cont - we can just ignore x_cat
    def forward(self, x_cat: Tensor, x_cont: Tensor):
        # pass x_cont into the network
        return self.layers(x_cont);