Update 2 optimizer.py

modules/optimizer.py

@@ -72,7 +72,7 @@ class Optimizer(object):
                 total_length_loss = torch.mean(100.*torch.nn.ReLU()(detector_length - self.constraints['length'])**2)#constrain it to 25cm
             if 'lower' in self.constraints:
                 lbound = (torch.ones(12) * self.constraints['lower']).to(self.device)
-                lower_loss = torch.mean(1000.*torch.nn.ReLU()(lbound- raw_detector_parameters)**2)
+                lower_loss = torch.mean(100.*torch.nn.ReLU()(lbound- raw_detector_parameters)**2)
             if 'upper' in self.constraints:
                 ubound = (torch.ones(6) * self.constraints['upper']).to(self.device)
                 upper_loss = torch.mean(100.*torch.nn.ReLU()(material_parameters - ubound)**2)
@@ -114,8 +114,7 @@ class Optimizer(object):
         return total_length_loss +lower_loss + upper_loss + diff_loss + cost_loss
     
     def clamp_parameters(self):
-        return
-        self.detector_parameters = self.detector_parameters.clamp(1e-3) #DEBUG, NE
+        self.detector_parameters.data = self.detector_parameters.data.clamp(1e-3) #DEBUG, NE
 
     def adjust_generator_covariance(self, direction, min_scale=2.0):
         #stretches the box_covariance of the generator in the directon specified as input