input: Write a python function to create and compile an LSTM model using Keras, with a specified input shape.
  assert isinstance(create_model((10, 1)), Sequential)
  assert isinstance(create_model((20, 1)), Sequential)
  assert create_model((10, 1)).layers[0].input_shape == [(None, 10, 1)]
  assert create_model((20, 1)).layers[0].input_shape == [(None, 20, 1)]
output: def create_model(input_shape):
      from keras.models import Sequential
      from keras.layers import LSTM, Dense
      
      model = Sequential()
      model.add(LSTM(50, input_shape=input_shape))
      model.add(Dense(1))
      model.compile(optimizer='adam', loss='mean_squared_error')
      
      return model