code: def mock_prediction_changed(mocker: MockerFixture):
      # Event tough it relies on numpy PRNG, because of setting seed manually, the sequence of
      # generated pseudo-logits will always stay the same.
      rng = np.random.default_rng(42)
  
      def mock_predict(self, x_batch, *args):
          # Event though technically, this is a stub, we called fixture and function `mock_`
          # to be aligned with pytest_mock naming.
          batch_size = len(x_batch)
          y_batch = rng.uniform(
              size=(batch_size, 10), low=-100, high=100
          )
          return y_batch
  
      mocker.patch(
          "quantus.helpers.model.tf_model.TensorFlowModel.predict",
          mock_predict,
      )
      mocker.patch(
          "quantus.helpers.model.pytorch_model.PyTorchModel.predict",
          mock_predict,
      )
      yield
      # Restore original behaviour after test finished execution.
      mocker.resetall()
  
label_desc: Use image node_id 1 for calling a global function with example usage: mock_prediction_changed(mocker) and returns: y_batch