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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
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