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AutoBatch cudnn.benchmark=True fix #9448

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merged 4 commits into from
Sep 16, 2022
Merged

AutoBatch cudnn.benchmark=True fix #9448

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378742e
AutoBatch `cudnn.benchmark=True` fix
glenn-jocher Sep 16, 2022
e9c4f8d
Update autobatch.py
glenn-jocher Sep 16, 2022
03c659d
Update autobatch.py
glenn-jocher Sep 16, 2022
9316e34
Update general.py
glenn-jocher Sep 16, 2022
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3 changes: 3 additions & 0 deletions utils/autobatch.py
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Expand Up @@ -33,6 +33,9 @@ def autobatch(model, imgsz=640, fraction=0.8, batch_size=16):
if device.type == 'cpu':
LOGGER.info(f'{prefix}CUDA not detected, using default CPU batch-size {batch_size}')
return batch_size
if torch.backends.cudnn.benchmark:
LOGGER.info(f'{prefix} ⚠️ Requires torch.backends.cudnn.benchmark=False, using default batch-size {batch_size}')
return batch_size

# Inspect CUDA memory
gb = 1 << 30 # bytes to GiB (1024 ** 3)
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2 changes: 1 addition & 1 deletion utils/general.py
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Expand Up @@ -223,7 +223,7 @@ def init_seeds(seed=0, deterministic=False):
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed) # for Multi-GPU, exception safe
torch.backends.cudnn.benchmark = True # for faster training
# torch.backends.cudnn.benchmark = True # AutoBatch problem https://github.com/ultralytics/yolov5/issues/9287
if deterministic and check_version(torch.__version__, '1.12.0'): # https://github.com/ultralytics/yolov5/pull/8213
torch.use_deterministic_algorithms(True)
torch.backends.cudnn.deterministic = True
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