class_docstr: FiftyOne wrapper around YOLO-NAS from
  https://github.com/Deci-AI/super-gradients.
  
  Args:
      config: a :class:`TorchYoloNasModelConfig`
class_docstr_tok: ["FiftyOne","wrapper","around","YOLO-NAS","from","https",":","\/\/github.com\/Deci-AI\/super-gradients",".","Args",":","config",":","a",":","class",":","`","TorchYoloNasModelConfig","`"]
code: def _load_model(self, config):
      if config.model is not None:
          self._model = config.model
      else:
          if self._using_gpu:
              self._model = super_gradients.training.models.get(
                  config.yolo_nas_model,
                  pretrained_weights=config.pretrained,
              ).cuda()
          else:
              self._model = super_gradients.training.models.get(
                  config.yolo_nas_model,
                  pretrained_weights=config.pretrained,
              )
  
      return self._model
  
file_path: fiftyone/fiftyone/utils/super_gradients.py
imports: import logging
  import fiftyone
  import fiftyone.core.utils
  import fiftyone.utils.torch
  import fiftyone.zoo.models
  import torch
  import numpy
label_desc: Use image node_id 1 for calling the TorchYoloNasModel obj's underlying member method code with example usage: obj._load_model(config) and returns: self