text: from tensorflow.keras import layers, models, datasets, optimizers
  import numpy as np 
  
  def neural_network_spatial():
      input_ = layers.Input(shape=(32,32,3))
      cnn = layers.Conv2D(16, (3,3), activation="relu") (input_)
      cnn = layers.SpatialDropout2D(______) (cnn)
      cnn = layers.MaxPooling2D() (cnn)
      
      cnn = layers.Conv2D(32, (3,3), activation="relu") (cnn)
      cnn = layers.____________ (cnn)
      cnn = layers.MaxPooling2D() (cnn)
      
      flatten = layers.GlobalMaxPooling2D() (cnn)
      
      dense = layers.Dense(32, activation="relu") (flatten)
      dense = layers.Dropout(_______) (dense)
      dense = layers.Dense(16,  activation="relu") (dense)
      
      output = layers.Dense(10, activation="softmax") (dense)
      
      opt = optimizers.Adam()
      
      m= models.Model(input_, output)
      m.compile(optimizer=opt,
                loss='categorical_crossentropy',
                metrics=['accuracy'])
      
      return m
  
  model = neural_network_spatial() # get model
  print(model.summary())