Yolov8-Pose Model

[saim212]

I successfully optimized the yolo-pose model but getting an error when I try to save the model.

here is the output of optimized model: PytorchONNXTensorRTInferenceLearner(network_parameters=ModelParams(batch_size=1, input_infos=[<nebullvm.core.models.InputInfo object at 0x7fdc7d807370>], output_sizes=[(1, 17, 33600), (1, 65, 160, 160), (1, 65, 80, 80), (1, 65, 40, 40)], output_types=[<DataType.FLOAT32: 'float32'>, <DataType.FLOAT32: 'float32'>, <DataType.FLOAT32: 'float32'>, <DataType.FLOAT32: 'float32'>], dynamic_info=None), input_tfms=<nebullvm.tools.transformations.MultiStageTransformation object at 0x7fdc7b448cd0>, device=<nebullvm.core.models.Device object at 0x7fdc7d804fd0>, quantization_type=None)

error while save:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-19-c1d99eee9fe5> in <cell line: 3>()
      1 from speedster import optimize_model, save_model, load_model
      2 from ultralytics import YOLO
----> 3 save_model(optimized_model, path="/content/drive/MyDrive/yolov8")

1 frames
/usr/local/lib/python3.10/dist-packages/nebullvm/operations/inference_learners/tensor_rt.py in save(self, path, **kwargs)
    218         serialized_engine = self.engine.serialize()
    219         print("*********", serialized_engine)
--> 220         with open(path / NVIDIA_FILENAMES["engine"], "wb") as fout:
    221             fout.write(serialized_engine)
    222         metadata = self._get_metadata(**kwargs)

TypeError: a bytes-like object is required, not 'NoneType'