code: def run_initialization_matching_optimization_0(build_fn):
      optimizer = DummyOptPro(iterations=1)
      optimizer.forge_experiment(
          model_initializer=KerasClassifier,
          model_init_params=dict(build_fn=build_fn),
          model_extra_params=dict(epochs=1, batch_size=128, verbose=0),
      )
      optimizer.go()
      return optimizer
  
imports: from hyperparameter_hunter import Environment, CVExperiment, Real, Integer, Categorical
  from hyperparameter_hunter import DummyOptPro, BayesianOptPro
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data, get_diabetes_data
  import pandas
  import pytest
  from keras.callbacks import ReduceLROnPlateau
  from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPooling2D, Reshape
  from keras.models import Sequential
  from keras.wrappers.scikit_learn import KerasClassifier, KerasRegressor
  from keras.initializers import glorot_normal, orthogonal, Orthogonal
  from sklearn.datasets import load_digits
label_desc: Use image node_id 12 for calling a global function with example usage: run_initialization_matching_optimization_0(build_fn) and returns: optimizer