| 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 |