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AutoBatch report include reserved+allocated (#9491) 

May resolve https://github.com/ultralytics/yolov5/issues/9287#issuecomment-1250767031

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
pull/9494/head
Glenn Jocher 2022-09-19 12:18:55 +02:00 committed by GitHub
parent fda8aa551d
commit f038ad7172
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1 changed files with 2 additions and 2 deletions
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utils/autobatch.py
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@ -19,7 +19,7 @@ def check_train_batch_size(model, imgsz=640, amp=True):
def autobatch(model, imgsz=640, fraction=0.8, batch_size=16): def autobatch(model, imgsz=640, fraction=0.8, batch_size=16):
# Automatically estimate best batch size to use `fraction` of available CUDA memory # Automatically estimate best YOLOv5 batch size to use `fraction` of available CUDA memory
# Usage: # Usage:
# import torch # import torch
# from utils.autobatch import autobatch # from utils.autobatch import autobatch
@ -67,6 +67,6 @@ def autobatch(model, imgsz=640, fraction=0.8, batch_size=16):
b = batch_size b = batch_size
LOGGER.warning(f'{prefix}WARNING ⚠️ CUDA anomaly detected, recommend restart environment and retry command.') LOGGER.warning(f'{prefix}WARNING ⚠️ CUDA anomaly detected, recommend restart environment and retry command.')
fraction = np.polyval(p, b) / t # actual fraction predicted fraction = (np.polyval(p, b) + r + a) / t # actual fraction predicted
LOGGER.info(f'{prefix}Using batch-size {b} for {d} {t * fraction:.2f}G/{t:.2f}G ({fraction * 100:.0f}%) ✅') LOGGER.info(f'{prefix}Using batch-size {b} for {d} {t * fraction:.2f}G/{t:.2f}G ({fraction * 100:.0f}%) ✅')
return b return b