code: def test_graph_manipulation(parameters, iotype):
      model, op, node, expected, skip_layers_check = (
          parameters[0],
          parameters[1],
          parameters[2],
          parameters[3],
          parameters[4],
      )
      odir = str(
          test_root_path
          / f"hls4mlprj_graph_{model.__name__}_{op}_{node}"
      )
      model = model(odir, iotype)
      original_layers = np.array(
          [layer.name for layer in list(model.get_layers())]
      )
      model, expected_layers = graph_ops[op](
          model, node, original_layers
      )
      model.compile()
      hls4ml.utils.plot_model(
          model,
          show_shapes=True,
          show_precision=True,
          to_file=f"{odir}/model.png",
      )
      X = np.zeros((1, 1))
      y = model.predict(X)
      # check the output
      expected = np.array(expected)
      np.testing.assert_array_equal(y, expected)
      # check the order
      actual_layers = np.array(
          [layer.name for layer in list(model.get_layers())]
      )
      if (
          not skip_layers_check
      ):  # skip check for this model since order changes
          np.testing.assert_array_equal(expected_layers, actual_layers)
  
file_path: hls4ml/test/pytest/test_graph.py
imports: from pathlib import Path
  import numpy
  import pytest
  import tensorflow
  import hls4ml
label_desc: Use image node_id 7 for calling a global function with example usage: test_graph_manipulation(parameters, iotype) without return types