[...] from keras.layers import Dense, Dropout, LeakyReLU, LSTM, Activation, Dense, Dropout, Input, Embedding

def LSTM(X,Y):
    inputDimension = len(X[0])
    inputSize = len(X)

    # create the model
    model = Sequential()
    model.add(Embedding(input_length=inputDimension,input_dim=inputDimension,output_dim=256))
    model.add(LSTM(100))
    model.add(Dropout(0.2))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    model.fit(X,Y,epochs=3,batch_size=64)
    return model