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Sleeping
| # DEBUG ONLY | |
| import time | |
| import random | |
| from tqdm import tqdm | |
| from backend.section_infer_helper.base_helper import BaseHelper | |
| from backend.utils.data_process import split_to_file_diff, split_to_section | |
| class RandomHelper(BaseHelper): | |
| PREDEF_MODEL = ["Random"] | |
| MODELS_SUPPORTED_LANGUAGES = { | |
| "Random": ["C", "C++", "Java", "Python"] | |
| } | |
| def load_model(self, model_name): | |
| pass | |
| def infer(self, diff_code): | |
| file_diff_list = split_to_file_diff(diff_code, BaseHelper._get_lang_ext(self.MODELS_SUPPORTED_LANGUAGES["Random"])) | |
| results = {} | |
| for file_a, _, file_diff in tqdm(file_diff_list, desc="Inferencing", unit="file", total=len(file_diff_list)): | |
| time.sleep(0.1) | |
| sections = split_to_section(file_diff) | |
| file = file_a.removeprefix("a/") | |
| results[file] = [] | |
| for section in sections: | |
| results[file].append({ | |
| "section": section, | |
| "predict": random.choice([0, 1]), | |
| "conf": random.random() | |
| }) | |
| return results | |
| random_helper = RandomHelper() | |