[First try]

main.py

@@ -7,6 +7,11 @@ import losses
 import optimizers
 import torch
 import logging
+import torch.optim
+
+def optimizer(cfg, model):
+    result = {"Adam" : torch.optim.Adam(model.parameters())}
+    return result[cfg["Optimizer"]]
 
 if __name__ == "__main__":
     logging.basicConfig(filename='logs/main_unit_test.log', level=logging.INFO)
@@ -43,7 +48,7 @@ if __name__ == "__main__":
 
     f_loss = losses.RMSLELoss()
 
-    optimizer = optimizers.optimizer(cfg, model)
+    optimizer = optimizer(cfg, model)
   
     for t in range(cfg["Training"]["Epochs"]):
         print("Epoch {}".format(t))

model.py

@@ -15,8 +15,7 @@ class LinearRegression(nn.Module):
         self.activate = nn.ReLU()
     def forward(self, x):
         y = self.regressor(x).view((x.shape[0],-1))
-        y = self.activate(y)
-        return y
+        return self.activate(y)
 
 def build_model(cfg, input_size):    
     return eval(f"{cfg['Model']['Name']}(cfg, input_size)")

optimizers.py

 import torch.optim
 
 def optimizer(cfg, model):
-    result = {"Adam" : torch.optim.Adam(model.parameters())}
+    result = {"Adam" : torch.optim.Adam(model.parameters(), lr = 1e-2)}
     return result[cfg["Optimizer"]]

train.py

@@ -30,4 +30,7 @@ def train(model, loader, f_loss, optimizer, device):
         # Backward and optimize
         optimizer.zero_grad()
         loss.backward()
-        optimizer.step()
\ No newline at end of file
+        optimizer.step()
+
+        print(model.regressor.weight)
+        print(model.regressor.bias)
\ No newline at end of file