I am noticing something strange when I am inferencing from a TensorsRT graph. As I inference more frames in **series** the overall time per frame reduces. The data is as follows,

1frame- 6sec --0.1FPS

3frames-12sec --0.25FPS

30frames- 6sec --5FPS

100frames- 7.25sec --13.7FPS

1000frames- 31.337sec --32FPS

10000frames- 175.118sec --57FPS

100000frames-1664.778sec --60FPS

I have also calculated the time ignoring the first 15 inferences calls and it appears to follow the same pattern. So this rules out the time to initialize the graph for the first few inferences.

This model is a simple MobileNetV2 and running on a jetson nano 4gb.

code snippet of inference

```
start_time=time.time()
for i in range(n_frames):
output = frozen_func(get_img_tensor(i))[0].numpy()
ans_arr.append(output)
end_time=time.time()
print("time taken - ",end_time-start_time)
```

keen to know what is happening here and do let me know if additional info is required.

Thank You