input: Write a python function to create a Sequential model with an Embedding layer, a SpatialDropout1D layer, an LSTM layer, and a Dense output layer, then compile it. 
  assert create_model().loss == "categorical_crossentropy"
  assert create_model().optimizer._name == "adam"
  assert create_model().metrics[0]._name == "accuracy"
output: def create_model():
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Embedding, SpatialDropout1D, LSTM, Dense
      from tensorflow.keras.optimizers import Adam
  
      model = Sequential()
      model.add(Embedding(input_dim=10000, output_dim=128, input_length=100))
      model.add(SpatialDropout1D(0.2))
      model.add(LSTM(128, dropout=0.2, recurrent_dropout=0.2))
      model.add(Dense(10, activation='softmax'))
  
      model.compile(loss='categorical_crossentropy',
                    optimizer=Adam(),
                    metrics=['accuracy'])
      return model