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Update autobatch.py #5538

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Merged
glenn-jocher merged 3 commits into from
Nov 6, 2021
Merged

Update autobatch.py #5538

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aaf1223
Update autobatch.py
glenn-jocher Nov 6, 2021
047094a
Update autobatch.py
glenn-jocher Nov 6, 2021
49e79e9
Update autobatch.py
glenn-jocher Nov 6, 2021
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11 changes: 6 additions & 5 deletions utils/autobatch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,11 +35,12 @@ def autobatch(model, imgsz=640, fraction=0.9, batch_size=16):
return batch_size

d = str(device).upper() # 'CUDA:0'
t = torch.cuda.get_device_properties(device).total_memory / 1024 ** 3 # (GB)
r = torch.cuda.memory_reserved(device) / 1024 ** 3 # (GB)
a = torch.cuda.memory_allocated(device) / 1024 ** 3 # (GB)
properties = torch.cuda.get_device_properties(device) # device properties
t = properties.total_memory / 1024 ** 3 # (GiB)
r = torch.cuda.memory_reserved(device) / 1024 ** 3 # (GiB)
a = torch.cuda.memory_allocated(device) / 1024 ** 3 # (GiB)
f = t - (r + a) # free inside reserved
print(f'{prefix}{d} {t:.3g}G total, {r:.3g}G reserved, {a:.3g}G allocated, {f:.3g}G free')
print(f'{prefix}{d} ({properties.name}) {t:.2f}G total, {r:.2f}G reserved, {a:.2f}G allocated, {f:.2f}G free')

batch_sizes = [1, 2, 4, 8, 16]
try:
Expand All @@ -52,5 +53,5 @@ def autobatch(model, imgsz=640, fraction=0.9, batch_size=16):
batch_sizes = batch_sizes[:len(y)]
p = np.polyfit(batch_sizes, y, deg=1) # first degree polynomial fit
b = int((f * fraction - p[1]) / p[0]) # y intercept (optimal batch size)
print(f'{prefix}Using batch-size {b} for {d} {t * fraction:.3g}G/{t:.3g}G ({fraction * 100:.0f}%)')
print(f'{prefix}Using batch-size {b} for {d} {t * fraction:.2f}G/{t:.2f}G ({fraction * 100:.0f}%)')
return b