code: def build_model(input_shape):
      
      model = Sequential()
  
      model.add(Conv2D(32, kernel_size=(3, 3),
                       activation='relu',
                       input_shape=input_shape))
      model.add(Conv2D(64, kernel_size=(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(num_classes, activation='softmax'))
  
      model.compile(loss=keras.losses.categorical_crossentropy,
                    optimizer=keras.optimizers.Adadelta(),
                    metrics=['accuracy'])
      return model
docs: Create a compiled Keras model.
  
      Parameters
      ----------
      input_shape : tuple, len=3
          Shape of each image sample.
  
      Returns
      -------
      model : keras.Model
          Constructed model.