import numpy as np

def get_initial_sample(unlabeled_data, num_query):

    # print(len(unlabeled_data))
    # print(unlabeled_data)  

    uncertain_samples = np.random.choice(len(unlabeled_data), size=num_query, replace=False)
    return uncertain_samples

def get_uncertain_sample(
    labeled_data, unlabeled_data, num_query
):
    # print(len(labeled_data))
    # print(labeled_data)

    # print(len(unlabeled_data))
    # print(unlabeled_data)    

    uncertain_samples = np.random.choice(len(unlabeled_data), size=num_query, replace=False)
    print(uncertain_samples)

    return uncertain_samples

def get_stopping_conditioon(
    labeled_data, eval_metrics
):
    print(eval_metrics)

    return True