code: def test_get_hidden_layer_output_sequential(
      load_mnist_model_tf, params
  ):
      model = TensorFlowModel(
          model=load_mnist_model_tf, channel_first=False
      )
      X = np.random.random((32, 28, 28, 1))
      result = model.get_hidden_representations(X, **params)
      assert isinstance(result, np.ndarray), "Must be a np.ndarray"
      assert len(result.shape) == 2, "Must be a batch of 1D tensors"
      assert (
          result.shape[0] == X.shape[0]
      ), "Must have same batch size as input"
  
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 5 for calling a global function with example usage: test_get_hidden_layer_output_sequential(load_mnist_model_tf, params) without return types