code: def test_integrated_gradients_binary_classification_multi_layer_subclassed(
      ffn_model_subclass, method, baselines
  ):
      model = ffn_model_subclass
  
      layer = [model.layers[0], model.layers[1]]
  
      ig = IntegratedGradients(
          model, layer=layer, n_steps=50, method=method
      )
  
      explanations = ig.explain(
          X_test, baselines=baselines, target=test_labels
      )
  
      assert isinstance(explanations, Explanation)
  
imports: from functools import partial
  import numpy
  import pytest
  import tensorflow
  from numpy.testing import assert_allclose
  from tensorflow.keras import Model
  from alibi.api.interfaces import Explanation
  from alibi.explainers import IntegratedGradients
  from alibi.explainers.integrated_gradients import _get_target_from_target_fn, _run_forward_from_layer, _run_forward_to_layer, _check_target, _select_target
label_desc: Use image node_id 22 for calling a global function with example usage: test_integrated_gradients_binary_classification_multi_layer_subclassed(ffn_model_subclass, method, baselines) without return types