class_docstr: This class implements a model-specific object detector using DEtection TRansformer (DETR)
  and PyTorch following the input and output formats of torchvision.
class_docstr_tok: ["This","class","implements","a","model-specific","object","detector","using","DEtection","TRansformer","(","DETR",")","and","PyTorch","following","the","input","and","output","formats","of","torchvision","."]
code: def fit(
      self,
      x: np.ndarray,
      y,
      batch_size: int = 128,
      nb_epochs: int = 20,
      **kwargs,
  ) -> None:
      raise NotImplementedError
  
file_path: adversarial-robustness-toolbox/art/estimators/object_detection/pytorch_detection_transformer.py
imports: import logging
  from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union, Any
  import numpy
  from art.estimators.object_detection.object_detector import ObjectDetectorMixin
  from art.estimators.pytorch import PyTorchEstimator
label_desc: Use image node_id 9 for calling the PyTorchDetectionTransformer obj's underlying member method code with example usage: obj.fit(x, y, batch_size, nb_epochs) without return types