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from loguru import logger | |
import torch | |
from torch import nn | |
from yolox.exp import get_exp | |
from yolox.models.network_blocks import SiLU | |
from yolox.utils import replace_module | |
import argparse | |
import os | |
def make_parser(): | |
parser = argparse.ArgumentParser("YOLOX onnx deploy") | |
parser.add_argument( | |
"--output-name", type=str, default="bytetrack_s.onnx", help="output name of models" | |
) | |
parser.add_argument( | |
"--input", default="images", type=str, help="input node name of onnx model" | |
) | |
parser.add_argument( | |
"--output", default="output", type=str, help="output node name of onnx model" | |
) | |
parser.add_argument( | |
"-o", "--opset", default=11, type=int, help="onnx opset version" | |
) | |
parser.add_argument("--no-onnxsim", action="store_true", help="use onnxsim or not") | |
parser.add_argument( | |
"-f", | |
"--exp_file", | |
default=None, | |
type=str, | |
help="expriment description file", | |
) | |
parser.add_argument("-expn", "--experiment-name", type=str, default=None) | |
parser.add_argument("-n", "--name", type=str, default=None, help="model name") | |
parser.add_argument("-c", "--ckpt", default=None, type=str, help="ckpt path") | |
parser.add_argument( | |
"opts", | |
help="Modify config options using the command-line", | |
default=None, | |
nargs=argparse.REMAINDER, | |
) | |
return parser | |
def main(): | |
args = make_parser().parse_args() | |
logger.info("args value: {}".format(args)) | |
exp = get_exp(args.exp_file, args.name) | |
exp.merge(args.opts) | |
if not args.experiment_name: | |
args.experiment_name = exp.exp_name | |
model = exp.get_model() | |
if args.ckpt is None: | |
file_name = os.path.join(exp.output_dir, args.experiment_name) | |
ckpt_file = os.path.join(file_name, "best_ckpt.pth.tar") | |
else: | |
ckpt_file = args.ckpt | |
# load the model state dict | |
ckpt = torch.load(ckpt_file, map_location="cpu") | |
model.eval() | |
if "model" in ckpt: | |
ckpt = ckpt["model"] | |
model.load_state_dict(ckpt) | |
model = replace_module(model, nn.SiLU, SiLU) | |
model.head.decode_in_inference = False | |
logger.info("loading checkpoint done.") | |
dummy_input = torch.randn(1, 3, exp.test_size[0], exp.test_size[1]) | |
torch.onnx._export( | |
model, | |
dummy_input, | |
args.output_name, | |
input_names=[args.input], | |
output_names=[args.output], | |
opset_version=args.opset, | |
) | |
logger.info("generated onnx model named {}".format(args.output_name)) | |
if not args.no_onnxsim: | |
import onnx | |
from onnxsim import simplify | |
# use onnxsimplify to reduce reduent model. | |
onnx_model = onnx.load(args.output_name) | |
model_simp, check = simplify(onnx_model) | |
assert check, "Simplified ONNX model could not be validated" | |
onnx.save(model_simp, args.output_name) | |
logger.info("generated simplified onnx model named {}".format(args.output_name)) | |
if __name__ == "__main__": | |
main() | |