input: Write a function to create a Sequential model using Keras with specified architecture.
  assert isinstance(create_model(), keras.models.Sequential)
  assert create_model().layers[0].input_shape==(None, 3)
  assert create_model().layers[2].rate==0.2
  assert create_model().layers[5].activation.__name__=='sigmoid'
output: def create_model():
      from keras.models import Sequential
      from keras.layers import Dense, Dropout
  
      model = Sequential()
      model.add(Dense(64, input_dim=3, activation='relu'))
      model.add(Dense(64, activation='relu'))
      model.add(Dropout(0.2))
      model.add(Dense(32, activation='relu'))
      model.add(Dense(32, activation='relu'))
      model.add(Dense(1, activation='sigmoid'))
  
      return model