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import typing as tp
from collections import namedtuple
from functools import partial
import torch
from transformers import pipeline
def get_translator():
return pipeline(
"translation_en_to_ru",
model="Helsinki-NLP/opus-mt-ru-en",
device="cuda" if torch.cuda.is_available() else "cpu",
torch_dtype="auto",
)
class TranslationModel:
def __init__(self, get_model):
self.translator = get_translator()
self.model = get_model()
def __call__(self, input, **kwargs):
def transform_input_dict_to_str(input):
if isinstance(input, tp.Dict):
return input["authors"] + " " + input["abstract"] + " " + input["title"]
if not isinstance(input, tp.Iterable) or isinstance(input, tp.Dict):
input = [input]
input = [transform_input_dict_to_str(i) for i in input]
translated_input = self.translator(input)
translated = [
translated_i["translation_text"] for translated_i in translated_input
]
out = self.model(translated)
if 1 == len(out):
return out[0]
return out
def create_translation_models(models):
return {
f"{name} (С помощью перевода)": partial(TranslationModel, get_model=get_model)
for name, get_model in models.items()
}
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