PyMLpipe - Pytorch model

class Model(torch.nn.Module):
    def __init__(self,col_size):
        super().__init__()
        # using sequencial
        self.seq=torch.nn.Sequential(
            torch.nn.Linear(col_size,15),
            torch.nn.ReLU(),
            torch.nn.Linear(15,10),
            torch.nn.ReLU(),
            torch.nn.Linear(10,1)
        )
        #using torch layers
        '''
        self.linear_layer_1=torch.nn.Linear(col_size,15)
        self.relu_1=torch.nn.ReLU()
        self.linear_layer_2=torch.nn.Linear(15,10)
        self.relu_2=torch.nn.ReLU()
        self.linear_layer_3=torch.nn.Linear(10,1)
        
        '''
        
        
    def forward(self,x):
        out=self.seq(x)
        '''
        out=self.relu_1(self.linear_layer_1(x))
        out=self.relu_12self.linear_layer_3(out))
        out=self.linear_layer_3(out)
        '''
        
        return torch.sigmoid(out)