updates

test.py

@@ -191,7 +191,7 @@ if __name__ == '__main__':
     parser.add_argument('--save-json', action='store_true', help='save a cocoapi-compatible JSON results file')
     parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
     opt = parser.parse_args()
-    print(opt, end='\n\n')
+    print(opt)
 
     with torch.no_grad():
         mAP = test(

train.py

@@ -294,7 +294,7 @@ if __name__ == '__main__':
     parser.add_argument('--evolve', action='store_true', help='run hyperparameter evolution')
     parser.add_argument('--var', default=0, type=int, help='debug variable')
     opt = parser.parse_args()
-    print(opt, end='\n\n')
+    print(opt)
 
     if opt.evolve:
         opt.notest = True  # save time by only testing final epoch

utils/torch_utils.py

@@ -25,6 +25,7 @@ def select_device(force_cpu=False):
                 print("           device%g _CudaDeviceProperties(name='%s', total_memory=%dMB)" %
                       (i, x[i].name, x[i].total_memory / c))
 
+    print('')  # skip a line
     return device
 
 

utils/utils.py

@@ -41,7 +41,7 @@ def model_info(model):
     # Plots a line-by-line description of a PyTorch model
     n_p = sum(x.numel() for x in model.parameters())  # number parameters
     n_g = sum(x.numel() for x in model.parameters() if x.requires_grad)  # number gradients
-    print('\n%5s %40s %9s %12s %20s %10s %10s' % ('layer', 'name', 'gradient', 'parameters', 'shape', 'mu', 'sigma'))
+    print('%5s %40s %9s %12s %20s %10s %10s' % ('layer', 'name', 'gradient', 'parameters', 'shape', 'mu', 'sigma'))
     for i, (name, p) in enumerate(model.named_parameters()):
         name = name.replace('module_list.', '')
         print('%5g %40s %9s %12g %20s %10.3g %10.3g' % (