I’m testing loading same model in gpu like this.
import model
import numpy as np

tt = np.zeros((512, 512, 3), dtype=np.uint8)
ms = {}
while True:
	for i in range(300):
		if not ms.get(i):
			ms.update({i:model.Model()})
			for k,v in ms.items():
				v.infer(tt)
			print(i, 'loaded')
			print(len(ms), 'length')

When I load just 1 model, it occupies 1G of GPU mem.
But when i load 160 model like above it occupies just 16G of gpu mem. why usage of gpu mem is not increasing linearly?