D-FINE/tools/benchmark/get_info.py

"""
Copyright (c) 2024 The D-FINE Authors. All Rights Reserved.
"""

import os
import sys

sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "../.."))

import argparse

import torch
import torch.nn as nn
from calflops import calculate_flops

from src.core import YAMLConfig


def custom_repr(self):
    return f"{{Tensor:{tuple(self.shape)}}} {original_repr(self)}"


original_repr = torch.Tensor.__repr__
torch.Tensor.__repr__ = custom_repr


def main(
    args,
):
    """main"""
    cfg = YAMLConfig(args.config, resume=None)

    class Model_for_flops(nn.Module):
        def __init__(
            self,
        ) -> None:
            super().__init__()
            self.model = cfg.model.deploy()

        def forward(self, images):
            outputs = self.model(images)
            return outputs

    model = Model_for_flops().eval()

    flops, macs, _ = calculate_flops(
        model=model, input_shape=(1, 3, 640, 640), output_as_string=True, output_precision=4
    )
    params = sum(p.numel() for p in model.parameters())
    print("Model FLOPs:%s   MACs:%s   Params:%s \n" % (flops, macs, params))


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--config", "-c", default="configs/dfine/dfine_hgnetv2_l_coco.yml", type=str
    )
    args = parser.parse_args()

    main(args)