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import cv2
import sys
sys.path.append('.')
import time
import torch
import torch.nn as nn
from model.RIFE import Model
model = Model()
model.eval()
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
torch.set_grad_enabled(False)
if torch.cuda.is_available():
torch.backends.cudnn.enabled = True
torch.backends.cudnn.benchmark = True
I0 = torch.rand(1, 3, 480, 640).to(device)
I1 = torch.rand(1, 3, 480, 640).to(device)
with torch.no_grad():
for i in range(100):
pred = model.inference(I0, I1)
if torch.cuda.is_available():
torch.cuda.synchronize()
time_stamp = time.time()
for i in range(100):
pred = model.inference(I0, I1)
if torch.cuda.is_available():
torch.cuda.synchronize()
print((time.time() - time_stamp) / 100)