def random_drop(data, p):
    for i in range(len(data)):
        for time in range(len(data[i])):
            for feature in range(len(data[i][time])):
                if (np.random.random_sample() < p):
                    data[i][time][feature] = 0
    return data
def random_drop(data, p):
    for i in range(len(data)):
        for time in range(len(data[i])):
            for feature in range(len(data[i][time])):
                if (np.random.random_sample() < p):
                    data[i][time][feature] = 0
    return data