updates

utils/torch_utils.py

@@ -17,7 +17,7 @@ def select_device(force_cpu=False):
 
         if torch.cuda.device_count() > 1:
             print('Found %g GPUs' % torch.cuda.device_count())
-            print('WARNING Using GPU0 Only: https://github.com/ultralytics/yolov3/issues/21')
+            print('WARNING Multi-GPU Issue: https://github.com/ultralytics/yolov3/issues/21')
         #    torch.cuda.set_device(0)  # OPTIONAL: Set your GPU if multiple available
         #    # print('Using ', torch.cuda.device_count(), ' GPUs')
 

utils/utils.py

@@ -242,12 +242,6 @@ def build_targets(target, anchor_vec, nA, nC, nG):
     tconf = torch.ByteTensor(nB, nA, nG, nG).fill_(0)
     tcls = torch.ByteTensor(nB, nA, nG, nG, nC).fill_(0)  # nC = number of classes
 
-    if anchor_vec.is_cuda:
-        txy = txy.cuda()
-        twh = twh.cuda()
-        tconf = tconf.cuda()
-        tcls = tcls.cuda()
-
     for b in range(nB):
         t = target[b]
         nTb = len(t)  # number of targets
@@ -263,8 +257,6 @@ def build_targets(target, anchor_vec, nA, nC, nG):
         box1 = gwh
         box2 = anchor_vec.unsqueeze(1)
 
-        print(box1.device, box2.device)
-
         inter_area = torch.min(box1, box2).prod(2)
         iou = inter_area / (box1.prod(1) + box2.prod(2) - inter_area + 1e-16)