code: def test_init_from_layermapping():
      mlp = BlankClassifier()
      wm, bm = mlp._layermapping(
          n_features=5, n_classes=4, hidden_layers=[3, 2]
      )
      w, b = mlp._init_params_from_layermapping(
          weight_maps=wm, bias_maps=bm, random_seed=1
      )
  
      assert len(w.keys()) == 3
      assert len(b.keys()) == 3
      assert set(w.keys()) == set(["1", "2", "out"])
      assert set(b.keys()) == set(["1", "2", "out"])
  
      assert w["1"].shape == (5, 3)
      assert w["2"].shape == (3, 2)
      assert w["out"].shape == (2, 4)
  
      assert b["1"].shape == (3,)
      assert b["2"].shape == (2,)
      assert b["out"].shape == (4,)
  
imports: from mlxtend._base import _MultiLayer
label_desc: Use image node_id 2 for calling a global function with example usage: test_init_from_layermapping() without return types