class_docstr: Implementation of the ObjectSeeker certifiable robust defense applied to object detection models.
  The original implementation is https://github.com/inspire-group/ObjectSeeker
  
  | Paper link: https://arxiv.org/abs/2202.01811
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docstr: Compute the loss of the neural network for samples `x`.
  
  :param x: Samples of shape NCHW or NHWC.
  :param y: Target values of format `List[Dict[str, Union[np.ndarray, torch.Tensor]]]`, one for each input image.
            The fields of the Dict are as follows:
  
            - boxes [N, 4]: the boxes in [x1, y1, x2, y2] format, with 0 <= x1 < x2 <= W and 0 <= y1 < y2 <= H.
            - labels [N]: the labels for each image.
  :return: Loss.
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code: def compute_loss(  # type: ignore
      self,
      x: np.ndarray,
      y: List[Dict[str, Union[np.ndarray, "torch.Tensor"]]],
      **kwargs,
  ) -> Union[np.ndarray, "torch.Tensor"]:
      """
      Compute the loss of the neural network for samples `x`.
  
      :param x: Samples of shape NCHW or NHWC.
      :param y: Target values of format `List[Dict[str, Union[np.ndarray, torch.Tensor]]]`, one for each input image.
                The fields of the Dict are as follows:
  
                - boxes [N, 4]: the boxes in [x1, y1, x2, y2] format, with 0 <= x1 < x2 <= W and 0 <= y1 < y2 <= H.
                - labels [N]: the labels for each image.
      :return: Loss.
      """
      return self.detector.compute_loss(
          x=x,
          y=y,
          **kwargs,
      )
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import sys
  from typing import List, Dict, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from art.estimators.certification.object_seeker.object_seeker import ObjectSeekerMixin
  from art.estimators.object_detection import ObjectDetectorMixin, PyTorchObjectDetector, PyTorchFasterRCNN, PyTorchYolo
  from art.estimators.pytorch import PyTorchEstimator
label_desc: Use image node_id 15 for calling the PyTorchObjectSeeker obj's underlying member method code with example usage: obj.compute_loss(x, y) and returns: self