import argparse
import sys
import time

import torch
from omegaconf import OmegaConf


sys.path.append(".")
from utils.build_utils import build_from_cfg


parser = argparse.ArgumentParser(
    prog="AMT",
    description="Speed&parameter benchmark",
)
parser.add_argument("-c", "--config", default="cfgs/AMT-S.yaml")
args = parser.parse_args()

cfg_path = args.config
network_cfg = OmegaConf.load(cfg_path).network
model = build_from_cfg(network_cfg)
model = model.cuda()
model.eval()

img0 = torch.randn(1, 3, 256, 448).cuda()
img1 = torch.randn(1, 3, 256, 448).cuda()
embt = torch.tensor(1 / 2).float().view(1, 1, 1, 1).cuda()

with torch.no_grad():
    for i in range(100):
        out = model(img0, img1, embt, eval=True)
    torch.cuda.synchronize()
    time_stamp = time.time()
    for i in range(1000):
        out = model(img0, img1, embt, eval=True)
    torch.cuda.synchronize()
    print("Time: {:.5f}s".format((time.time() - time_stamp) / 1))

total = sum([param.nelement() for param in model.parameters()])
print("Parameters: {:.2f}M".format(total / 1e6))