code: def test_shape_input(
      data: np.ndarray,
      params: dict,
      expected: Union[float, dict, bool],
      load_mnist_model_tf,
  ):
      model = TensorFlowModel(
          load_mnist_model_tf, channel_first=params["channel_first"]
      )
      out = model.shape_input(**data)
      assert np.array_equal(out, expected), "Test failed."
  
file_path: Quantus/tests/helpers/test_tf_model.py
imports: from functools import reduce
  from operator import and_
  from typing import Union
  import tensorflow
  import numpy
  import pytest
  from pytest_lazyfixture import lazy_fixture
  from scipy.special import softmax
  from quantus.helpers.model.tf_model import TensorFlowModel
label_desc: Use image node_id 3 for calling a global function with example usage: test_shape_input(data, params, expected, load_mnist_model_tf) without return types