code: def create_keras_model():
      """
      This function compiles and returns a Keras model.
      Should be passed to KerasClassifier in the Keras scikit-learn API.
      """
  
      model = Sequential()
      model.add(
          Conv2D(
              32,
              kernel_size=(3, 3),
              activation="relu",
              input_shape=(28, 28, 1),
          )
      )
      model.add(Conv2D(64, (3, 3), activation="relu"))
      model.add(MaxPooling2D(pool_size=(2, 2)))
      model.add(Dropout(0.25))
      model.add(Flatten())
      model.add(Dense(128, activation="relu"))
      model.add(Dropout(0.5))
      model.add(Dense(10, activation="softmax"))
  
      model.compile(
          loss="categorical_crossentropy",
          optimizer="adadelta",
          metrics=["accuracy"],
      )
  
      return model
  
imports: import keras
  import numpy
  from keras.datasets import mnist
  from keras.layers import Conv2D, Dense, Dropout, Flatten, MaxPooling2D
  from keras.models import Sequential
  from keras.wrappers.scikit_learn import KerasClassifier
  from modAL.models import ActiveLearner
label_desc: Use image node_id 1 for calling a global function with example usage: create_keras_model() and returns: model