Refactor argparser printing to print_args() (#4850)

* Refactor argparser printing to `print_args()`

* Cleanup

detect.py

@@ -19,12 +19,12 @@ FILE = Path(__file__).resolve()
 sys.path.append(FILE.parents[0].as_posix())  # add yolov5/ to path
 
 from models.experimental import attempt_load
-from utils.datasets import LoadStreams, LoadImages
-from utils.general import check_img_size, check_imshow, check_requirements, check_suffix, colorstr, is_ascii, \
-    non_max_suppression, apply_classifier, scale_coords, xyxy2xywh, strip_optimizer, set_logging, increment_path, \
-    save_one_box
+from utils.datasets import LoadImages, LoadStreams
+from utils.general import apply_classifier, check_img_size, check_imshow, check_requirements, check_suffix, colorstr, \
+    increment_path, is_ascii, non_max_suppression, print_args, save_one_box, scale_coords, set_logging, \
+    strip_optimizer, xyxy2xywh
 from utils.plots import Annotator, colors
-from utils.torch_utils import select_device, load_classifier, time_sync
+from utils.torch_utils import load_classifier, select_device, time_sync
 
 
 @torch.no_grad()
@@ -279,11 +279,11 @@ def parse_opt():
     parser.add_argument('--half', action='store_true', help='use FP16 half-precision inference')
     opt = parser.parse_args()
     opt.imgsz *= 2 if len(opt.imgsz) == 1 else 1  # expand
+    print_args(FILE.stem, opt)
     return opt
 
 
 def main(opt):
-    print(colorstr('detect: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
     check_requirements(exclude=('tensorboard', 'thop'))
     run(**vars(opt))
 

export.py

@@ -41,7 +41,8 @@ from models.experimental import attempt_load
 from models.yolo import Detect
 from utils.activations import SiLU
 from utils.datasets import LoadImages
-from utils.general import colorstr, check_dataset, check_img_size, check_requirements, file_size, set_logging, url2file
+from utils.general import colorstr, check_dataset, check_img_size, check_requirements, file_size, print_args, \
+    set_logging, url2file
 from utils.torch_utils import select_device
 
 
@@ -322,12 +323,12 @@ def parse_opt():
                         default=['torchscript', 'onnx'],
                         help='available formats are (torchscript, onnx, coreml, saved_model, pb, tflite, tfjs)')
     opt = parser.parse_args()
+    print_args(FILE.stem, opt)
     return opt
 
 
 def main(opt):
     set_logging()
-    print(colorstr('export: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
     run(**vars(opt))
 
 

models/tf.py

@@ -27,9 +27,9 @@ import torch.nn as nn
 from tensorflow import keras
 
 from models.common import Conv, Bottleneck, SPP, DWConv, Focus, BottleneckCSP, Concat, autopad, C3
-from models.experimental import MixConv2d, CrossConv, attempt_load
+from models.experimental import CrossConv, MixConv2d, attempt_load
 from models.yolo import Detect
-from utils.general import colorstr, make_divisible, set_logging
+from utils.general import make_divisible, print_args, set_logging
 from utils.activations import SiLU
 
 LOGGER = logging.getLogger(__name__)
@@ -434,12 +434,12 @@ def parse_opt():
     parser.add_argument('--dynamic', action='store_true', help='dynamic batch size')
     opt = parser.parse_args()
     opt.imgsz *= 2 if len(opt.imgsz) == 1 else 1  # expand
+    print_args(FILE.stem, opt)
     return opt
 
 
 def main(opt):
     set_logging()
-    print(colorstr('tf.py: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
     run(**vars(opt))
 
 

train.py

@@ -36,7 +36,7 @@ from utils.autoanchor import check_anchors
 from utils.datasets import create_dataloader
 from utils.general import labels_to_class_weights, increment_path, labels_to_image_weights, init_seeds, \
     strip_optimizer, get_latest_run, check_dataset, check_git_status, check_img_size, check_requirements, \
-    check_file, check_yaml, check_suffix, print_mutation, set_logging, one_cycle, colorstr, methods
+    check_file, check_yaml, check_suffix, print_args, print_mutation, set_logging, one_cycle, colorstr, methods
 from utils.downloads import attempt_download
 from utils.loss import ComputeLoss
 from utils.plots import plot_labels, plot_evolve
@@ -470,9 +470,8 @@ def parse_opt(known=False):
 
 def main(opt, callbacks=Callbacks()):
     # Checks
-    set_logging(RANK)
     if RANK in [-1, 0]:
-        print(colorstr('train: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
+        print_args(FILE.stem, opt)
         check_git_status()
         check_requirements(requirements=FILE.parent / 'requirements.txt', exclude=['thop'])
 
@@ -508,7 +507,7 @@ def main(opt, callbacks=Callbacks()):
     if not opt.evolve:
         train(opt.hyp, opt, device, callbacks)
         if WORLD_SIZE > 1 and RANK == 0:
-            _ = [print('Destroying process group... ', end=''), dist.destroy_process_group(), print('Done.')]
+            _ = LOGGER.info('Destroying process group... ', end=''), dist.destroy_process_group(), LOGGER.info('Done.')
 
     # Evolve hyperparameters (optional)
     else:

utils/general.py

@@ -89,6 +89,11 @@ def set_logging(rank=-1, verbose=True):
         level=logging.INFO if (verbose and rank in [-1, 0]) else logging.WARN)
 
 
+def print_args(name, opt):
+    # Print argparser arguments
+    print(colorstr(f'{name}: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
+
+
 def init_seeds(seed=0):
     # Initialize random number generator (RNG) seeds https://pytorch.org/docs/stable/notes/randomness.html
     # cudnn seed 0 settings are slower and more reproducible, else faster and less reproducible

val.py

@@ -24,7 +24,7 @@ from models.experimental import attempt_load
 from utils.datasets import create_dataloader
 from utils.general import coco80_to_coco91_class, check_dataset, check_img_size, check_requirements, \
     check_suffix, check_yaml, box_iou, non_max_suppression, scale_coords, xyxy2xywh, xywh2xyxy, set_logging, \
-    increment_path, colorstr
+    increment_path, colorstr, print_args
 from utils.metrics import ap_per_class, ConfusionMatrix
 from utils.plots import output_to_target, plot_images, plot_val_study
 from utils.torch_utils import select_device, time_sync
@@ -295,7 +295,7 @@ def run(data,
 
 
 def parse_opt():
-    parser = argparse.ArgumentParser(prog='val.py')
+    parser = argparse.ArgumentParser()
     parser.add_argument('--data', type=str, default='data/coco128.yaml', help='dataset.yaml path')
     parser.add_argument('--weights', nargs='+', type=str, default='yolov5s.pt', help='model.pt path(s)')
     parser.add_argument('--batch-size', type=int, default=32, help='batch size')
@@ -319,12 +319,12 @@ def parse_opt():
     opt.save_json |= opt.data.endswith('coco.yaml')
     opt.save_txt |= opt.save_hybrid
     opt.data = check_yaml(opt.data)  # check YAML
+    print_args(FILE.stem, opt)
     return opt
 
 
 def main(opt):
     set_logging()
-    print(colorstr('val: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
     check_requirements(requirements=FILE.parent / 'requirements.txt', exclude=('tensorboard', 'thop'))
 
     if opt.task in ('train', 'val', 'test'):  # run normally