fix issue amdegroot#173

layers/modules/multibox_loss.py

@@ -94,8 +94,8 @@ def forward(self, predictions, targets):
         loss_c = log_sum_exp(batch_conf) - batch_conf.gather(1, conf_t.view(-1, 1))
 
         # Hard Negative Mining
-        loss_c[pos] = 0  # filter out pos boxes for now
         loss_c = loss_c.view(num, -1)
+        loss_c[pos] = 0  # filter out pos boxes for now
         _, loss_idx = loss_c.sort(1, descending=True)
         _, idx_rank = loss_idx.sort(1)
         num_pos = pos.long().sum(1, keepdim=True)
@@ -111,7 +111,7 @@ def forward(self, predictions, targets):
 
         # Sum of losses: L(x,c,l,g) = (Lconf(x, c) + αLloc(x,l,g)) / N
 
-        N = num_pos.data.sum()
-        loss_l /= N
-        loss_c /= N
+        N = num_pos.data.sum().double()
+        loss_l = loss_l.double() / N
+        loss_c = loss_c.double() / N
         return loss_l, loss_c

train.py

@@ -180,15 +180,15 @@ def train():
         loss.backward()
         optimizer.step()
         t1 = time.time()
-        loc_loss += loss_l.data[0]
-        conf_loss += loss_c.data[0]
+        loc_loss += loss_l.item()
+        conf_loss += loss_c.item()
 
         if iteration % 10 == 0:
             print('timer: %.4f sec.' % (t1 - t0))
-            print('iter ' + repr(iteration) + ' || Loss: %.4f ||' % (loss.data[0]), end=' ')
+            print('iter ' + repr(iteration) + ' || Loss: %.4f ||' % (loss.item()), end=' ')
 
         if args.visdom:
-            update_vis_plot(iteration, loss_l.data[0], loss_c.data[0],
+            update_vis_plot(iteration, loss_l.item(), loss_c.item(),
                             iter_plot, epoch_plot, 'append')
 
         if iteration != 0 and iteration % 5000 == 0: