class_docstr: Configuration for running a :class:`TorchYoloNasModel`.
  
  See :class:`fiftyone.utils.torch.TorchImageModelConfig` for additional
  arguments.
  
  Args:
      model (None): a preloaded
          ``super_gradients.training.models.detection_models.yolo_nas`` model
          to use
      yolo_nas_model ("yolo_nas_l"): the name of a YOLO-NAS model to use
      pretrained ("coco"): the pretrained version to use
class_docstr_tok: ["Configuration","for","running","a",":","class",":","`","TorchYoloNasModel","`",".","See",":","class",":","`","fiftyone.utils.torch.TorchImageModelConfig","`","for","additional","arguments",".","Args",":","model","(","None",")",":","a","preloaded","``","super_gradients.training.models.detection_models.yolo_nas","``","model","to","use","yolo_nas_model","(","``","yolo_nas_l","''",")",":","the","name","of","a","YOLO-NAS","model","to","use","pretrained","(","``","coco","''",")",":","the","pretrained","version","to","use"]
code: def __init__(self, d):
      d = self.init(d)
      super().__init__(d)
  
      self.model = self.parse_raw(d, "model", default=None)
      self.yolo_nas_model = self.parse_string(
          d, "yolo_nas_model", default="yolo_nas_l"
      )
      self.pretrained = self.parse_string(
          d, "pretrained", default="coco"
      )
  
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 to create a new TorchYoloNasModelConfig object from inherited base classes: fout, fozm with example: obj = TorchYoloNasModelConfig(d)