Files
VRCT/models/translation/translation_translator.py

87 lines
3.5 KiB
Python

from deepl import Translator as deepl_Translator
from deepl_translate import translate as deepl_web_Translator
from translators import translate_text as other_web_Translator
from .translation_languages import translation_lang
from ctranslate2.converters import TransformersConverter
import ctranslate2
import transformers
TRANSLATE_MODELS = {
"small": "facebook/m2m100_418M",
"large": "facebook/m2m100_1.2B"
}
# Translator
class Translator():
def __init__(self):
pass
self.translator_status = {}
self.translator = ctranslate2.Translator("D:\\WORKSPACE\\WORK\\VRChatProject\\VRCT\\weight", device="cpu", device_index=0, compute_type="int8", inter_threads=1, intra_threads=4)
self.tokenizer = transformers.AutoTokenizer.from_pretrained("facebook/m2m100_418M")
def authentication(self, translator_name, authkey=None):
result = True
match translator_name:
case "DeepL_API":
try:
self.deepl_client = deepl_Translator(authkey)
self.deepl_client.translate_text(" ", target_lang="EN-US")
except Exception:
result = False
return result
def translate(self, translator_name, source_language, target_language, message):
try:
result = ""
source_language=translation_lang[translator_name]["source"][source_language]
target_language=translation_lang[translator_name]["target"][target_language]
match translator_name:
case "DeepL":
result = deepl_web_Translator(
source_language=source_language,
target_language=target_language,
text=message
)
case "DeepL_API":
result = self.deepl_client.translate_text(
message,
source_lang=source_language,
target_lang=target_language,
).text
case "Google":
result = other_web_Translator(
query_text=message,
translator="google",
from_language=source_language,
to_language=target_language,
)
case "Bing":
result = other_web_Translator(
query_text=message,
translator="bing",
from_language=source_language,
to_language=target_language,
)
except Exception:
import traceback
with open('error.log', 'a') as f:
traceback.print_exc(file=f)
result = False
return result
def translate_ctranslate2(self, translator_name, source_language, target_language, message):
source_language=translation_lang["ctranslate2"]["source"][source_language]
target_language=translation_lang["ctranslate2"]["target"][target_language]
self.tokenizer.src_lang = source_language
source = self.tokenizer.convert_ids_to_tokens(self.tokenizer.encode(message))
target_prefix = [self.tokenizer.lang_code_to_token[target_language]]
results = self.translator.translate_batch([source], target_prefix=[target_prefix])
target = results[0].hypotheses[0][1:]
result = self.tokenizer.decode(self.tokenizer.convert_tokens_to_ids(target))
print(result)
return result