Update tensorboard>=2.4.1 (#2576)

requirements.txt

@@ -8,12 +8,12 @@ opencv-python>=4.1.2
 Pillow
 PyYAML>=5.3.1
 scipy>=1.4.1
-tensorboard>=2.2
 torch>=1.7.0
 torchvision>=0.8.1
 tqdm>=4.41.0
 
 # logging -------------------------------------
+tensorboard>=2.4.1
 # wandb
 
 # plotting ------------------------------------

train.py

-
 import argparse
 import logging
 import math
@@ -34,7 +33,7 @@ from utils.google_utils import attempt_download
 from utils.loss import ComputeLoss
 from utils.plots import plot_images, plot_labels, plot_results, plot_evolution
 from utils.torch_utils import ModelEMA, select_device, intersect_dicts, torch_distributed_zero_first, is_parallel
-from utils.wandb_logging.wandb_utils import WandbLogger, resume_and_get_id, check_wandb_config_file
+from utils.wandb_logging.wandb_utils import WandbLogger, resume_and_get_id
 
 logger = logging.getLogger(__name__)
 
@@ -75,7 +74,7 @@ def train(hyp, opt, device, tb_writer=None):
         data_dict = wandb_logger.data_dict
         if wandb_logger.wandb:
             weights, epochs, hyp = opt.weights, opt.epochs, opt.hyp  # WandbLogger might update weights, epochs if resuming
-    
+
     nc = 1 if opt.single_cls else int(data_dict['nc'])  # number of classes
     names = ['item'] if opt.single_cls and len(data_dict['names']) != 1 else data_dict['names']  # class names
     assert len(names) == nc, '%g names found for nc=%g dataset in %s' % (len(names), nc, opt.data)  # check
@@ -405,7 +404,7 @@ def train(hyp, opt, device, tb_writer=None):
                         wandb_logger.log_model(
                             last.parent, opt, epoch, fi, best_model=best_fitness == fi)
                 del ckpt
-        
+
         # end epoch ----------------------------------------------------------------------------------------------------
     # end training
     if rank in [-1, 0]:
@@ -534,7 +533,8 @@ if __name__ == '__main__':
     if not opt.evolve:
         tb_writer = None  # init loggers
         if opt.global_rank in [-1, 0]:
-            logger.info(f'Start Tensorboard with "tensorboard --logdir {opt.project}", view at http://localhost:6006/')
+            prefix = colorstr('tensorboard: ')
+            logger.info(f"{prefix}Start with 'tensorboard --logdir {opt.project}', view at http://localhost:6006/")
             tb_writer = SummaryWriter(opt.save_dir)  # Tensorboard
         train(hyp, opt, device, tb_writer)