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New global TQDM_BAR_FORMAT (#10211)

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* 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>
This commit is contained in:
Glenn Jocherandpre-commit-ci[bot] authored and GitHub committed 2022-11-18 21:39:13 +01:00
1 parent 74b3886edd
commit 0322bb3196
9 files changed
+35 -33
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segment/train.py
+5 -5
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@@ -46,10 +46,10 @@ from utils.autoanchor import check_anchors
from utils.autobatch import check_train_batch_size
from utils.callbacks import Callbacks
from utils.downloads import attempt_download, is_url
from utils.general import (LOGGER, check_amp, check_dataset, check_file, check_git_status, check_img_size,
check_requirements, check_suffix, check_yaml, colorstr, get_latest_run, increment_path,
init_seeds, intersect_dicts, labels_to_class_weights, labels_to_image_weights, one_cycle,
print_args, print_mutation, strip_optimizer, yaml_save)
from utils.general import (LOGGER, TQDM_BAR_FORMAT, check_amp, check_dataset, check_file, check_git_status,
check_img_size, check_requirements, check_suffix, check_yaml, colorstr, get_latest_run,
increment_path, init_seeds, intersect_dicts, labels_to_class_weights,
labels_to_image_weights, one_cycle, print_args, print_mutation, strip_optimizer, yaml_save)
from utils.loggers import GenericLogger
from utils.plots import plot_evolve, plot_labels
from utils.segment.dataloaders import create_dataloader
@@ -277,7 +277,7 @@ def train(hyp, opt, device, callbacks): # hyp is path/to/hyp.yaml or hyp dictio
LOGGER.info(('\n' + '%11s' * 8) %
('Epoch', 'GPU_mem', 'box_loss', 'seg_loss', 'obj_loss', 'cls_loss', 'Instances', 'Size'))
if RANK in {-1, 0}:
pbar = tqdm(pbar, total=nb, bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}') # progress bar
pbar = tqdm(pbar, total=nb, bar_format=TQDM_BAR_FORMAT) # progress bar
optimizer.zero_grad()
for i, (imgs, targets, paths, _, masks) in pbar: # batch ------------------------------------------------------
# callbacks.run('on_train_batch_start')
segment/val.py
+4 -4
View File
@@ -42,9 +42,9 @@ import torch.nn.functional as F
from models.common import DetectMultiBackend
from models.yolo import SegmentationModel
from utils.callbacks import Callbacks
from utils.general import (LOGGER, NUM_THREADS, Profile, check_dataset, check_img_size, check_requirements, check_yaml,
coco80_to_coco91_class, colorstr, increment_path, non_max_suppression, print_args,
scale_boxes, xywh2xyxy, xyxy2xywh)
from utils.general import (LOGGER, NUM_THREADS, TQDM_BAR_FORMAT, Profile, check_dataset, check_img_size,
check_requirements, check_yaml, coco80_to_coco91_class, colorstr, increment_path,
non_max_suppression, print_args, scale_boxes, xywh2xyxy, xyxy2xywh)
from utils.metrics import ConfusionMatrix, box_iou
from utils.plots import output_to_target, plot_val_study
from utils.segment.dataloaders import create_dataloader
@@ -237,7 +237,7 @@ def run(
loss = torch.zeros(4, device=device)
jdict, stats = [], []
# callbacks.run('on_val_start')
pbar = tqdm(dataloader, desc=s, bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}') # progress bar
pbar = tqdm(dataloader, desc=s, bar_format=TQDM_BAR_FORMAT) # progress bar
for batch_i, (im, targets, paths, shapes, masks) in enumerate(pbar):
# callbacks.run('on_val_batch_start')
with dt[0]: