HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

Ruff Docstring formatting (#15793)

Browse source 
Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
This commit is contained in:
Glenn Jocher 2024-08-25 04:27:55 +08:00 • committed by GitHub
parent d27664216b
commit 776ca86369
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
60 changed files with 241 additions and 309 deletions
Download patch file Download diff file Expand all files Collapse all files

11
ultralytics/utils/autobatch.py
View file

@ -16,13 +16,17 @@ def check_train_batch_size(model, imgsz=640, amp=True, batch=-1):
Args:
model (torch.nn.Module): YOLO model to check batch size for.
imgsz (int): Image size used for training.
amp (bool): If True, use automatic mixed precision (AMP) for training.
imgsz (int, optional): Image size used for training.
amp (bool, optional): Use automatic mixed precision if True.
batch (float, optional): Fraction of GPU memory to use. If -1, use default.
Returns:
(int): Optimal batch size computed using the autobatch() function.
"""
Note:
If 0.0 < batch < 1.0, it's used as the fraction of GPU memory to use.
Otherwise, a default fraction of 0.6 is used.
"""
with autocast(enabled=amp):
return autobatch(deepcopy(model).train(), imgsz, fraction=batch if 0.0 < batch < 1.0 else 0.6)
@ -40,7 +44,6 @@ def autobatch(model, imgsz=640, fraction=0.60, batch_size=DEFAULT_CFG.batch):
Returns:
(int): The optimal batch size.
"""
# Check device
prefix = colorstr("AutoBatch: ")
LOGGER.info(f"{prefix}Computing optimal batch size for imgsz={imgsz} at {fraction * 100}% CUDA memory utilization.")