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ultralytics 8.0.65 YOLOv8 Pose models (#1347)

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Ayush Chaurasia 2023-04-06 03:55:32 +05:30 • committed by GitHub
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commit 1cb92d7f42
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20
ultralytics/yolo/utils/torch_utils.py
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@ -240,8 +240,8 @@ def copy_attr(a, b, include=(), exclude=()):
def get_latest_opset():
# Return max supported ONNX opset by this version of torch
return max(int(k[14:]) for k in vars(torch.onnx) if 'symbolic_opset' in k) # opset
# Return second-most (for maturity) recently supported ONNX opset by this version of torch
return max(int(k[14:]) for k in vars(torch.onnx) if 'symbolic_opset' in k) - 1 # opset
def intersect_dicts(da, db, exclude=()):
@ -318,18 +318,18 @@ def strip_optimizer(f: Union[str, Path] = 'best.pt', s: str = '') -> None:
"""
Strip optimizer from 'f' to finalize training, optionally save as 's'.
Usage:
from ultralytics.yolo.utils.torch_utils import strip_optimizer
from pathlib import Path
for f in Path('/Users/glennjocher/Downloads/weights').glob('*.pt'):
strip_optimizer(f)
Args:
f (str): file path to model to strip the optimizer from. Default is 'best.pt'.
s (str): file path to save the model with stripped optimizer to. If not provided, 'f' will be overwritten.
Returns:
None
Usage:
from pathlib import Path
from ultralytics.yolo.utils.torch_utils import strip_optimizer
for f in Path('/Users/glennjocher/Downloads/weights').rglob('*.pt'):
strip_optimizer(f)
"""
x = torch.load(f, map_location=torch.device('cpu'))
args = {**DEFAULT_CFG_DICT, **x['train_args']} # combine model args with default args, preferring model args
@ -349,7 +349,9 @@ def strip_optimizer(f: Union[str, Path] = 'best.pt', s: str = '') -> None:
def profile(input, ops, n=10, device=None):
""" YOLOv8 speed/memory/FLOPs profiler
"""
YOLOv8 speed/memory/FLOPs profiler
Usage:
input = torch.randn(16, 3, 640, 640)
m1 = lambda x: x * torch.sigmoid(x)