| import re | |
| import fasttext | |
| from functools import reduce | |
| FASTTEXT_MODEL_PATH = "/researchdisk/lid.176.bin" | |
| fasttext_model = fasttext.load_model(FASTTEXT_MODEL_PATH) | |
| def filter_stats(batch): | |
| filter_stats_funcs = [ | |
| _count_alphabet, | |
| _count_numbers, | |
| _count_upper, | |
| _count_str_len, | |
| _predict_lang, | |
| _calculate_alphabet_ratio, | |
| _calculate_number_ratio, | |
| _calculate_upper_ratio, | |
| ] | |
| return reduce(lambda x, y: y(x), filter_stats_funcs, batch) | |
| def _count_alphabet(batch): | |
| batch["alphabet_len"] = len(re.findall(r"[äÄöÖåÅa-zA-Z]", batch["text"])) | |
| return batch | |
| def _count_numbers(batch): | |
| batch["number_len"] = len(re.findall(r"[0-9]", batch["text"])) | |
| return batch | |
| def _count_upper(batch): | |
| batch["upper_len"] = len(re.findall(r"[ÄÖÅA-Z]", batch["text"])) | |
| return batch | |
| def _count_str_len(batch): | |
| batch["total_len"] = len(batch["text"]) | |
| return batch | |
| def _predict_lang(batch): | |
| pred = fasttext_model.predict(batch["text"]) | |
| batch["predicted_lang"] = pred[0][0] | |
| batch["predicted_lang_percentage"] = float(pred[1][0]) | |
| return batch | |
| def _calculate_alphabet_ratio(batch): | |
| batch["alphabet_ratio"] = int(batch["alphabet_len"]) / int(batch["total_len"]) | |
| return batch | |
| def _calculate_number_ratio(batch): | |
| batch["number_ratio"] = int(batch["number_len"]) / int(batch["total_len"]) | |
| return batch | |
| def _calculate_upper_ratio(batch): | |
| batch["upper_ratio"] = int(batch["upper_len"]) / int(batch["total_len"]) | |
| return batch | |