New global TQDM_BAR_FORMAT (#10211)

* New global TQDM_BAR_FORMAT

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

classify/train.py

@@ -40,8 +40,8 @@ from classify import val as validate
 from models.experimental import attempt_load
 from models.yolo import ClassificationModel, DetectionModel
 from utils.dataloaders import create_classification_dataloader
-from utils.general import (DATASETS_DIR, LOGGER, WorkingDirectory, check_git_status, check_requirements, colorstr,
-                           download, increment_path, init_seeds, print_args, yaml_save)
+from utils.general import (DATASETS_DIR, LOGGER, TQDM_BAR_FORMAT, WorkingDirectory, check_git_status,
+                           check_requirements, colorstr, download, increment_path, init_seeds, print_args, yaml_save)
 from utils.loggers import GenericLogger
 from utils.plots import imshow_cls
 from utils.torch_utils import (ModelEMA, model_info, reshape_classifier_output, select_device, smart_DDP,
@@ -174,7 +174,7 @@ def train(opt, device):
             trainloader.sampler.set_epoch(epoch)
         pbar = enumerate(trainloader)
         if RANK in {-1, 0}:
-            pbar = tqdm(enumerate(trainloader), total=len(trainloader), bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}')
+            pbar = tqdm(enumerate(trainloader), total=len(trainloader), bar_format=TQDM_BAR_FORMAT)
         for i, (images, labels) in pbar:  # progress bar
             images, labels = images.to(device, non_blocking=True), labels.to(device)
 

classify/val.py

@@ -36,7 +36,8 @@ ROOT = Path(os.path.relpath(ROOT, Path.cwd()))  # relative
 
 from models.common import DetectMultiBackend
 from utils.dataloaders import create_classification_dataloader
-from utils.general import LOGGER, Profile, check_img_size, check_requirements, colorstr, increment_path, print_args
+from utils.general import (LOGGER, TQDM_BAR_FORMAT, Profile, check_img_size, check_requirements, colorstr,
+                           increment_path, print_args)
 from utils.torch_utils import select_device, smart_inference_mode
 
 
@@ -100,7 +101,7 @@ def run(
     n = len(dataloader)  # number of batches
     action = 'validating' if dataloader.dataset.root.stem == 'val' else 'testing'
     desc = f"{pbar.desc[:-36]}{action:>36}" if pbar else f"{action}"
-    bar = tqdm(dataloader, desc, n, not training, bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}', position=0)
+    bar = tqdm(dataloader, desc, n, not training, bar_format=TQDM_BAR_FORMAT, position=0)
     with torch.cuda.amp.autocast(enabled=device.type != 'cpu'):
         for images, labels in bar:
             with dt[0]: