


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


__UpperCamelCase    		=       logging.get_logger(__name__)

__UpperCamelCase    		=       {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

__UpperCamelCase    		=       {
    'vocab_file': {
        'yjernite/retribert-base-uncased': (
            'https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'yjernite/retribert-base-uncased': (
            'https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json'
        ),
    },
}

__UpperCamelCase    		=       {
    'yjernite/retribert-base-uncased': 5_1_2,
}


__UpperCamelCase    		=       {
    'yjernite/retribert-base-uncased': {'do_lower_case': True},
}







class        lowerCamelCase__	(							UpperCAmelCase      ):






			"""simple docstring"""






			_UpperCamelCase		:					Dict    =		VOCAB_FILES_NAMES
			_UpperCamelCase		:					Any    =		PRETRAINED_VOCAB_FILES_MAP
			_UpperCamelCase		:					Optional[int]    =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			_UpperCamelCase		:					str    =		PRETRAINED_INIT_CONFIGURATION
			_UpperCamelCase		:					int    =		RetriBertTokenizer
			_UpperCamelCase		:					Optional[Any]    =		['input_ids', 'attention_mask']




			def __init__(							self      ,						snake_case=None      ,						snake_case=None      ,						snake_case=True      ,						snake_case="[UNK]"      ,						snake_case="[SEP]"      ,						snake_case="[PAD]"      ,						snake_case="[CLS]"      ,						snake_case="[MASK]"      ,						snake_case=True      ,						snake_case=None      ,						**snake_case      ,						):

						'''simple docstring'''


						super().__init__(
						    snake_case      ,						tokenizer_file=snake_case      ,						do_lower_case=snake_case      ,						unk_token=snake_case      ,						sep_token=snake_case      ,						pad_token=snake_case      ,						cls_token=snake_case      ,						mask_token=snake_case      ,						tokenize_chinese_chars=snake_case      ,						strip_accents=snake_case      ,						**snake_case      ,						)

						UpperCamelCase__					=       json.loads(self.backend_tokenizer.normalizer.__getstate__()     )
						if (
						    normalizer_state.get("lowercase"      ,						snake_case     ) != do_lower_case
						    or normalizer_state.get("strip_accents"      ,						snake_case     ) != strip_accents
						    or normalizer_state.get("handle_chinese_chars"      ,						snake_case     ) != tokenize_chinese_chars
						):
									UpperCamelCase__					=       getattr(snake_case      ,						normalizer_state.pop("type"     )     )
									UpperCamelCase__					=       do_lower_case
									UpperCamelCase__					=       strip_accents
									UpperCamelCase__					=       tokenize_chinese_chars
									UpperCamelCase__					=       normalizer_class(**snake_case     )

						UpperCamelCase__					=       do_lower_case




			def 				snake_case__				(							self      ,						snake_case      ,						snake_case=None     ):

						'''simple docstring'''


						UpperCamelCase__					=       [self.cls_token_id] + token_ids_a + [self.sep_token_id]

						if token_ids_a:
									output += token_ids_a + [self.sep_token_id]

						return output




			def 				snake_case__				(							self      ,						snake_case      ,						snake_case = None     ):

						'''simple docstring'''


						UpperCamelCase__					=       [self.sep_token_id]
						UpperCamelCase__					=       [self.cls_token_id]
						if token_ids_a is None:
									return len(cls + token_ids_a + sep     ) * [0]
						return len(cls + token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1]







			def 				snake_case__				(							self      ,						snake_case      ,						snake_case = None     ):

						'''simple docstring'''


						UpperCamelCase__					=       self._tokenizer.model.save(snake_case      ,						name=snake_case     )
						return tuple(snake_case     )






import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property







@unittest.skipUnless(os.path.exists(UpperCAmelCase      )					,	'Tatoeba directory does not exist.'      )
class        lowerCamelCase__	(							unittest.TestCase      ):






			"""simple docstring"""






			@cached_property
			def 				snake_case__				(							self     ):

						'''simple docstring'''


						UpperCamelCase__					=       tempfile.mkdtemp()
						return TatoebaConverter(save_dir=snake_case     )




			@slow
			def 				snake_case__				(							self     ):

						'''simple docstring'''


						self.resolver.convert_models(["heb-eng"]     )







			@slow
			def 				snake_case__				(							self     ):

						'''simple docstring'''


						UpperCamelCase__,      UpperCamelCase__					=       self.resolver.write_model_card("opus-mt-he-en"      ,						dry_run=snake_case     )
						assert mmeta["long_pair"] == "heb-eng"


