def lstm_comp(df):
    model = Sequential()
    model.add(LSTM(256, activation='relu', batch_input_shape=(None, df.shape[1], df.shape[2])))
    model.add(Dropout(0.2))
    model.add(Dense(256, activation='relu'))
    model.add(Dropout(0.2))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model
def lstm_comp(df):
    model = Sequential()
    model.add(LSTM(256, activation='relu', batch_input_shape=(None, df.shape[1], df.shape[2])))
    model.add(Dropout(0.2))
    model.add(Dense(256, activation='relu'))
    model.add(Dropout(0.2))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model