updates

models.py

@@ -88,6 +88,7 @@ def create_modules(module_defs, img_size):
                 bias = module_list[-1][0].bias.view(len(mask), -1)  # 255 to 3x85
                 bias[:, 4] += b[0]  # obj
                 bias[:, 5:] += b[1]  # cls
+                # bias = torch.load('weights/yolov3-spp.bias.pt')[yolo_index]  # list of tensors [3x85, 3x85, 3x85]
                 module_list[-1][0].bias = torch.nn.Parameter(bias.view(-1))
                 # utils.print_model_biases(model)
             except:

train.py

@@ -332,7 +332,7 @@ def train(cfg,
                          'training_results': file.read(),
                          'model': model.module.state_dict() if type(
                              model) is nn.parallel.DistributedDataParallel else model.state_dict(),
-                         'optimizer': optimizer.state_dict()}
+                         'optimizer': None if final_epoch else optimizer.state_dict()}
 
             # Save last checkpoint
             torch.save(chkpt, last)

utils/utils.py

@@ -17,7 +17,7 @@ from . import torch_utils  # , google_utils
 matplotlib.rc('font', **{'size': 11})
 
 # Set printoptions
-torch.set_printoptions(linewidth=1320, precision=5, profile='long')
+torch.set_printoptions(linewidth=320, precision=5, profile='long')
 np.set_printoptions(linewidth=320, formatter={'float_kind': '{:11.5g}'.format})  # format short g, %precision=5
 
 # Prevent OpenCV from multithreading (to use PyTorch DataLoader)