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# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import time
import torch
from mmengine import Config
from mmengine.device import get_device
from mmengine.registry import init_default_scope
from mmengine.runner import Runner, autocast, load_checkpoint
from mmdet3d.registry import MODELS
from tools.misc.fuse_conv_bn import fuse_module
def parse_args():
parser = argparse.ArgumentParser(description='MMDet benchmark a model')
parser.add_argument('config', help='test config file path')
parser.add_argument('checkpoint', help='checkpoint file')
parser.add_argument('--samples', default=2000, help='samples to benchmark')
parser.add_argument(
'--log-interval', default=50, help='interval of logging')
parser.add_argument(
'--amp',
action='store_true',
help='Whether to use automatic mixed precision inference')
parser.add_argument(
'--fuse-conv-bn',
action='store_true',
help='Whether to fuse conv and bn, this will slightly increase'
'the inference speed')
args = parser.parse_args()
return args
def main():
args = parse_args()
init_default_scope('mmdet3d')
# build config and set cudnn_benchmark
cfg = Config.fromfile(args.config)
if cfg.env_cfg.get('cudnn_benchmark', False):
torch.backends.cudnn.benchmark = True
# build dataloader
dataloader = Runner.build_dataloader(cfg.test_dataloader)
# build model and load checkpoint
model = MODELS.build(cfg.model)
load_checkpoint(model, args.checkpoint, map_location='cpu')
if args.fuse_conv_bn:
model = fuse_module(model)
model.to(get_device())
model.eval()
# the first several iterations may be very slow so skip them
num_warmup = 5
pure_inf_time = 0
# benchmark with several samples and take the average
for i, data in enumerate(dataloader):
torch.cuda.synchronize()
start_time = time.perf_counter()
with autocast(enabled=args.amp):
model.test_step(data)
torch.cuda.synchronize()
elapsed = time.perf_counter() - start_time
if i >= num_warmup:
pure_inf_time += elapsed
if (i + 1) % args.log_interval == 0:
fps = (i + 1 - num_warmup) / pure_inf_time
print(f'Done sample [{i + 1:<3}/ {args.samples}], '
f'fps: {fps:.1f} sample / s')
if (i + 1) == args.samples:
pure_inf_time += elapsed
fps = (i + 1 - num_warmup) / pure_inf_time
print(f'Overall fps: {fps:.1f} sample / s')
break
if __name__ == '__main__':
main()
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