class_docstr: This module implements the task specific estimator for PyTorch object detection models following the input and
  output formats of torchvision.
class_docstr_tok: ["This","module","implements","the","task","specific","estimator","for","PyTorch","object","detection","models","following","the","input","and","output","formats","of","torchvision","."]
docstr: Are the native labels in PyTorch format [x1, y1, x2, y2]?
docstr_tok: ["Are","the","native","labels","in","PyTorch","format","[","x1",",","y1",",","x2",",","y2","]","?"]
code: def native_label_is_pytorch_format(self) -> bool:
      """
      Are the native labels in PyTorch format [x1, y1, x2, y2]?
      """
      return True
  
imports: import logging
  from typing import List, Dict, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from art.estimators.object_detection.object_detector import ObjectDetectorMixin
  from art.estimators.object_detection.utils import cast_inputs_to_pt
  from art.estimators.pytorch import PyTorchEstimator
label_desc: Use image node_id 2 for calling the PyTorchObjectDetector obj's underlying member method code with example usage: obj.native_label_is_pytorch_format() and returns: True