code: def test_multiclass_gd_acc():
      mlp = MLP(
          epochs=20,
          eta=0.05,
          hidden_layers=[10],
          minibatches=1,
          random_seed=1,
      )
      mlp.fit(X, y)
      assert round(mlp.cost_[0], 2) == 0.55, mlp.cost_[0]
      assert round(mlp.cost_[-1], 2) == 0.01, mlp.cost_[-1]
      assert (y == mlp.predict(X)).all()
  
file_path: mlxtend/mlxtend/classifier/tests/test_multilayerperceptron.py
imports: import numpy
  from sklearn.base import clone
  from mlxtend.classifier import MultiLayerPerceptron
  from mlxtend.data import iris_data
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 1 for calling a global function with example usage: test_multiclass_gd_acc() without return types