code: def build_fn(input_shape=-1):
      model = Sequential(
          [
              Reshape((8, 8, -1), input_shape=(64,)),
              Conv2D(
                  filters=32,
                  kernel_size=(5, 5),
                  padding="same",
                  activation="relu",
              ),
              MaxPooling2D(pool_size=(2, 2)),
              Dropout(0.5),
              Flatten(),
              Dense(10, activation="softmax"),
          ]
      )
      model.compile(
          optimizer="adam",
          loss="categorical_crossentropy",
          metrics=["accuracy"],
      )
      return model
  
file_path: hyperparameter_hunter/examples/keras_examples/multi_classification_example.py
imports: from hyperparameter_hunter import Environment, CVExperiment
  import pandas
  from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPooling2D, Reshape
  from keras.models import Sequential
  from keras.wrappers.scikit_learn import KerasClassifier
  from sklearn.datasets import load_digits
label_desc: Use image node_id 2 for calling a global function with example usage: build_fn(input_shape) and returns: model