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yolo.py profiling updates #7178

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Mar 29, 2022
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yolo.py profiling updates #7178

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yolo.py profiling updates
glenn-jocher Mar 28, 2022
336ac80
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 28, 2022
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26 changes: 12 additions & 14 deletions models/yolo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,8 @@
from utils.autoanchor import check_anchor_order
from utils.general import LOGGER, check_version, check_yaml, make_divisible, print_args
from utils.plots import feature_visualization
from utils.torch_utils import fuse_conv_and_bn, initialize_weights, model_info, scale_img, select_device, time_sync
from utils.torch_utils import (fuse_conv_and_bn, initialize_weights, model_info, profile, scale_img, select_device,
time_sync)

try:
import thop # for FLOPs computation
Expand Down Expand Up @@ -300,33 +301,30 @@ def parse_model(d, ch): # model_dict, input_channels(3)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--cfg', type=str, default='yolov5s.yaml', help='model.yaml')
parser.add_argument('--batch-size', type=int, default=1, help='total batch size for all GPUs')
parser.add_argument('--device', default='', help='cuda device, i.e. 0 or 0,1,2,3 or cpu')
parser.add_argument('--profile', action='store_true', help='profile model speed')
parser.add_argument('--line-profile', action='store_true', help='profile model speed layer by layer')
parser.add_argument('--test', action='store_true', help='test all yolo*.yaml')
opt = parser.parse_args()
opt.cfg = check_yaml(opt.cfg) # check YAML
print_args(FILE.stem, opt)
device = select_device(opt.device)

# Create model
im = torch.rand(opt.batch_size, 3, 640, 640).to(device)
model = Model(opt.cfg).to(device)

# Profile
if opt.profile:
model.eval().fuse()
img = torch.rand(8 if torch.cuda.is_available() else 1, 3, 640, 640).to(device)
y = model(img, profile=True)
# Options
if opt.line_profile: # profile layer by layer
_ = model(im, profile=True)

# Test all models
if opt.test:
elif opt.profile: # profile forward-backward
results = profile(input=im, ops=[model], n=3)

elif opt.test: # test all models
for cfg in Path(ROOT / 'models').rglob('yolo*.yaml'):
try:
_ = Model(cfg)
except Exception as e:
print(f'Error in {cfg}: {e}')

# Tensorboard (not working https://github.com/ultralytics/yolov5/issues/2898)
# from torch.utils.tensorboard import SummaryWriter
# tb_writer = SummaryWriter('.')
# LOGGER.info("Run 'tensorboard --logdir=models' to view tensorboard at http://localhost:6006/")
# tb_writer.add_graph(torch.jit.trace(model, img, strict=False), []) # add model graph