code: def test_layermapping_shape():
      mlp = BlankClassifier()
      w, b = mlp._layermapping(
          n_features=10, n_classes=11, hidden_layers=[8, 7, 6]
      )
  
      expect_b = {
          "1": [[8], "n_hidden_1"],
          "2": [[7], "n_hidden_2"],
          "3": [[6], "n_hidden_3"],
          "out": [[11], "n_classes"],
      }
  
      expect_w = {
          "1": [[10, 8], "n_features, n_hidden_1"],
          "2": [[8, 7], "n_hidden_1, n_hidden_2"],
          "3": [[7, 6], "n_hidden_2, n_hidden_3"],
          "out": [[6, 11], "n_hidden_3, n_classes"],
      }
  
      assert expect_b == b, b
      assert expect_w == w, w
  
imports: from mlxtend._base import _MultiLayer
label_desc: Use image node_id 1 for calling a global function with example usage: test_layermapping_shape() without return types