input: Write a python function to create and compile a TensorFlow Sequential model with the given architecture.
  assert create_and_compile_model().layers[0].input_shape == (None, 128)
  assert create_and_compile_model().layers[1].units == 64
  assert create_and_compile_model().layers[2].activation.__name__ == 'relu'
  assert create_and_compile_model().layers[3].units == 3
  assert create_and_compile_model().layers[3].activation.__name__ == 'softmax'
output: def create_and_compile_model():
      import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense, Input
  
      model = Sequential([
          Input(shape=(128,)),
          Dense(64, activation='relu'),
          Dense(64, activation='relu'),
          Dense(3, activation='softmax')
      ])
      
      model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      return model