input: Write a python function to create and compile a Keras Sequential model with specified layers and configurations.
  assert create_model().summary() == model.summary()
  assert create_model().optimizer.__class__.__name__ == 'RMSprop'
  assert create_model().loss == 'binary_crossentropy'
output: def create_model():
      from keras.models import Sequential
      from keras.layers import Dense
      from keras.optimizers import RMSprop
  
      model = Sequential()
      model.add(Dense(64, activation='relu', input_dim=100))
      model.add(Dense(1, activation='sigmoid'))
  
      model.compile(optimizer=RMSprop(),
                    loss='binary_crossentropy',
                    metrics=['accuracy'])
      
      return model