Lines Matching full:loss

77           and systematically validated by assuring that the loss goes the right direction
197                     loss = (weight.mv(input) + bias).pow(2).sum()
198                     loss.backward()
204                     return loss
209                         loss = optimizer.step(closure)
211                         loss = closure()
216                             scheduler.step(loss)
256                     loss = (weight.mv(inpt).cuda(1) + bias).pow(2).sum()
257                     loss.backward()
263                     return loss
267                     loss = optimizer.step(closure)
270                             scheduler.step(loss)
297                 loss = (weight.mv(inpt) + bias).pow(2).sum()
298                 loss.backward()
304                 return loss
308                 loss = optimizer.step(closure)
311                         scheduler.step(loss)
348                 loss = (w.mv(i) + b).pow(2).sum()
349                 loss.backward()
355                 return loss
463                     loss = sum(rosenbrock(param) for param in params)
465                     loss = rosenbrock(params[0])
466                 loss.backward()
473                 return loss
544                 loss = torch.randn(1)
545                 grads_losses.append(loss.clone())
546                 return loss
621                 loss = rosenbrock(a1).abs()
622                 loss.backward()
630                 losses.add(loss)
632                 return loss
639                 loss = rosenbrock(a2).abs()
640                 losses.pop_check_set(loss, self)
641                 loss.backward()
644                 return loss
694                     loss = output.sum()
695                     loss.backward()
1191             loss = (weight.mv(input) + bias).pow(2).sum()
1192             initial_value = loss.item()
1195                 loss = (weight.mv(input) + bias).pow(2).sum()
1196                 loss.backward()
1204             # Test that the direction of loss moved appropriately
1206                 self.assertGreater(loss.item(), initial_value)
1208                 self.assertLess(loss.item(), initial_value)
1239             loss = (weight.mv(input) + bias).pow(2).sum()
1240             initial_value = loss.item()
1243                 loss = (weight.mv(input) + bias).pow(2).sum()
1244                 loss.backward()
1254             # Test that the direction of loss moved appropriately
1256                 self.assertGreater(loss.item(), initial_value)
1258                 self.assertLess(loss.item(), initial_value)
1361             loss = (w.mv(i) + b).pow(2).sum()
1362             loss.backward()
1368             return loss
1437                 loss = mod(i).sum()
1438                 loss.backward()
1439                 return loss
1482             loss = (w.mv(i) + b).pow(2).sum()
1483             loss.backward()
1487             return loss
2030             loss = output.sum()
2031             loss.backward()
2050             loss = output.sum()
2051             loss.backward()