input: from typing import Tuple
  
  def construct_neural_network() -> Tuple[keras.Model, keras.Model]:
      """Construct a neural network model in Python to classify the MNIST data set correctly.
      The function should return the compiled model.
      Example:
      >>> model, compiled_model = construct_neural_network()
      >>> model.summary()
      """
      import keras
  
      # Input layer
      input_layer = keras.layers.Input(shape=(784,))
  
      # Hidden layer
      hidden_layer = keras.layers.Dense(128, activation='relu')(input_layer)
  
      # Output layer
      output_layer = keras.layers.Dense(10, activation='softmax')(hidden_layer)
  
      # Model
      model = keras.Model(inputs=input_layer, outputs=output_layer)
  
      # Compile model
      compiled_model = keras.Model(inputs=input_layer, outputs=output_layer)
      compiled_model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      
      return model, compiled_model
output:     import keras
  
      # Input layer
      input_layer = keras.layers.Input(shape=(784,))
  
      # Hidden layer
      hidden_layer = keras.layers.Dense(128, activation='relu')(input_layer)
  
      # Output layer
      output_layer = keras.layers.Dense(10, activation='softmax')(hidden_layer)
  
      # Model
      model = keras.Model(inputs=input_layer, outputs=output_layer)
  
      # Compile model
      compiled_model = keras.Model(inputs=input_layer, outputs=output_layer)
      compiled_model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      
      return model, compiled_model