code: def fix_get_goturn():
      from art.estimators.estimator import (
          BaseEstimator,
          LossGradientsMixin,
      )
      from art.estimators.object_tracking.object_tracker import (
          ObjectTrackerMixin,
      )
  
      class DummyObjectTracker(
          ObjectTrackerMixin, LossGradientsMixin, BaseEstimator
      ):
          def __init__(self):
              super().__init__(
                  model=None,
                  clip_values=(0, 1),
                  preprocessing_defences=None,
                  postprocessing_defences=None,
                  preprocessing=(0, 1),
              )
  
              import torch
  
              self.channels_first = False
              self._input_shape = None
              self.postprocessing_defences = None
              self.device = torch.device("cpu")
  
          def loss_gradient(self, x: np.ndarray, y: None, **kwargs):
              return np.ones_like(x)
  
          def fit(
              self,
              x: np.ndarray,
              y,
              batch_size: int = 128,
              nb_epochs: int = 20,
              **kwargs,
          ):
              raise NotImplementedError
  
          def predict(
              self, x: np.ndarray, batch_size: int = 128, **kwargs
          ):
              boxes_list = list()
              for i in range(x.shape[1]):
                  boxes_list.append([0.1, 0.2, 0.3, 0.4])
  
              dict_i = {
                  "boxes": np.array(boxes_list),
                  "labels": np.array([[2]]),
                  "scores": np.array([[0.8]]),
              }
              return [dict_i] * x.shape[0]
  
          @property
          def native_label_is_pytorch_format(self):
              return True
  
          @property
          def input_shape(self):
              return self._input_shape
  
      goturn = DummyObjectTracker()
      return goturn
  
imports: import importlib
  import json
  import logging
  import os
  import shutil
  import tempfile
  from typing import Dict, List, TYPE_CHECKING, Union
  import warnings
  import numpy
  import pytest
  import requests
  from art.data_generators import KerasDataGenerator, MXDataGenerator, PyTorchDataGenerator, TensorFlowDataGenerator, TensorFlowV2DataGenerator
  from art.defences.preprocessor import FeatureSqueezing, JpegCompression, SpatialSmoothing
  from art.estimators.classification import KerasClassifier
  from tests.utils import ARTTestFixtureNotImplemented, get_attack_classifier_pt, get_image_classifier_kr, get_image_classifier_kr_functional, get_image_classifier_kr_tf, get_image_classifier_kr_tf_functional, get_image_classifier_kr_tf_with_wildcard, get_image_classifier_mxnet_custom_ini, get_image_classifier_pt, get_image_classifier_pt_functional, get_image_classifier_tf, get_image_classifier_hf, get_image_gan_tf_v2, get_image_generator_tf_v2, get_tabular_classifier_kr, get_tabular_classifier_pt, get_tabular_classifier_scikit_list, get_tabular_classifier_tf, load_dataset, master_seed
label_desc: Use image node_id 45 for calling a global function with example usage: fix_get_goturn() and returns: goturn, np, unknown, True, self