



import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE     				=						get_tests_dir("fixtures/test_sentencepiece.model")
SCREAMING_SNAKE_CASE     				=						get_tests_dir("fixtures/test_sentencepiece_bpe.model")

SCREAMING_SNAKE_CASE     				=						"pt" if is_torch_available() else "tf"



@require_sentencepiece
@require_tokenizers
class 	lowerCamelCase      (						lowercase__,     unittest.TestCase  ):







					'''simple docstring'''







					lowerCAmelCase_				:    int									=  CamembertTokenizer
					lowerCAmelCase_				:    int									=  CamembertTokenizerFast
					lowerCAmelCase_				:    Tuple									=  True
					lowerCAmelCase_				:    Union[str, Any]									=  True



					def    A__		(			self     ):
							super().setUp()

							# We have a SentencePiece fixture for testing
							UpperCAmelCase_						=				CamembertTokenizer(lowerCAmelCase     )
							tokenizer.save_pretrained(self.tmpdirname     )



					def    A__		(			self     ):
							UpperCAmelCase_						=				"<pad>"
							UpperCAmelCase_						=				1

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase     )    ,	lowerCAmelCase     )
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase     )    ,	lowerCAmelCase     )



					def    A__		(			self     ):
							UpperCAmelCase_						=				list(self.get_tokenizer().get_vocab().keys()     )

							self.assertEqual(vocab_keys[0]    ,	"<s>NOTUSED"     )
							self.assertEqual(vocab_keys[1]    ,	"<pad>"     )
							self.assertEqual(vocab_keys[-1]    ,	"<mask>"     )
							self.assertEqual(len(lowerCAmelCase     )    ,	1004     )



					def    A__		(			self     ):
							self.assertEqual(self.get_tokenizer().vocab_size    ,	1005     )



					def    A__		(			self     ):
							UpperCAmelCase_						=				CamembertTokenizer(lowerCAmelCase     )
							tokenizer.save_pretrained(self.tmpdirname     )
							UpperCAmelCase_						=				CamembertTokenizerFast.from_pretrained(self.tmpdirname     )

							UpperCAmelCase_						=				"I was born in 92000, and this is falsé."

							UpperCAmelCase_						=				tokenizer.encode(lowerCAmelCase     )
							UpperCAmelCase_						=				rust_tokenizer.encode(lowerCAmelCase     )
							self.assertListEqual(lowerCAmelCase    ,	lowerCAmelCase     )

							UpperCAmelCase_						=				tokenizer.encode(lowerCAmelCase    ,	add_special_tokens=lowerCAmelCase     )
							UpperCAmelCase_						=				rust_tokenizer.encode(lowerCAmelCase    ,	add_special_tokens=lowerCAmelCase     )
							self.assertListEqual(lowerCAmelCase    ,	lowerCAmelCase     )

							# <unk> tokens are not the same for `rust` than for `slow`.
							# Because spm gives back raw token instead of `unk` in EncodeAsPieces
							# tokens = tokenizer.tokenize(sequence)
							UpperCAmelCase_						=				tokenizer.convert_ids_to_tokens(lowerCAmelCase     )
							UpperCAmelCase_						=				rust_tokenizer.tokenize(lowerCAmelCase     )
							self.assertListEqual(lowerCAmelCase    ,	lowerCAmelCase     )



					def    A__		(			self     ):
							if not self.test_rust_tokenizer:
									return

							UpperCAmelCase_						=				self.get_tokenizer()
							UpperCAmelCase_						=				self.get_rust_tokenizer()

							UpperCAmelCase_						=				"I was born in 92000, and this is falsé."

							UpperCAmelCase_						=				tokenizer.tokenize(lowerCAmelCase     )
							UpperCAmelCase_						=				rust_tokenizer.tokenize(lowerCAmelCase     )
							self.assertListEqual(lowerCAmelCase    ,	lowerCAmelCase     )

							UpperCAmelCase_						=				tokenizer.encode(lowerCAmelCase    ,	add_special_tokens=lowerCAmelCase     )
							UpperCAmelCase_						=				rust_tokenizer.encode(lowerCAmelCase    ,	add_special_tokens=lowerCAmelCase     )
							self.assertListEqual(lowerCAmelCase    ,	lowerCAmelCase     )

							UpperCAmelCase_						=				self.get_rust_tokenizer()
							UpperCAmelCase_						=				tokenizer.encode(lowerCAmelCase     )
							UpperCAmelCase_						=				rust_tokenizer.encode(lowerCAmelCase     )
							self.assertListEqual(lowerCAmelCase    ,	lowerCAmelCase     )



					@slow
					def    A__		(			self     ):
							# fmt: off
							UpperCAmelCase_						=				{"input_ids": [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 2_7575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9088, 20, 1517, 8, 2_2804, 1_8818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 1_0326, 24, 2267, 20, 416, 5072, 1_5612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 8, 930, 9, 6]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
							# fmt: on

							# camembert is a french model. So we also use french texts.
							UpperCAmelCase_						=				[
							    "Le transformeur est un modèle d'apprentissage profond introduit en 2017, "
							    "utilisé principalement dans le domaine du traitement automatique des langues (TAL).",
							    "À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus "
							    "pour gérer des données séquentielles, telles que le langage naturel, pour des tâches "
							    "telles que la traduction et la synthèse de texte.",
							]

							self.tokenizer_integration_test_util(
							    expected_encoding=lowerCAmelCase    ,	model_name="camembert-base"    ,	revision="3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"    ,	sequences=lowerCAmelCase    ,	)






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


SCREAMING_SNAKE_CASE     				=						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE     				=						{"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

SCREAMING_SNAKE_CASE     				=						{
    "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"
        ),
    },
}

SCREAMING_SNAKE_CASE     				=						{
    "yjernite/retribert-base-uncased": 512,
}


SCREAMING_SNAKE_CASE     				=						{
    "yjernite/retribert-base-uncased": {"do_lower_case": True},
}



class 	lowerCamelCase      (						lowercase__  ):







					'''simple docstring'''







					lowerCAmelCase_				:    List[str]									=  VOCAB_FILES_NAMES
					lowerCAmelCase_				:    int									=  PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase_				:    Any									=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase_				:    Dict									=  PRETRAINED_INIT_CONFIGURATION
					lowerCAmelCase_				:    List[str]									=  RetriBertTokenizer
					lowerCAmelCase_				:    Union[str, Any]									=  ['input_ids', 'attention_mask']



					def __init__(			self    ,	lowerCAmelCase=None    ,	lowerCAmelCase=None    ,	lowerCAmelCase=True    ,	lowerCAmelCase="[UNK]"    ,	lowerCAmelCase="[SEP]"    ,	lowerCAmelCase="[PAD]"    ,	lowerCAmelCase="[CLS]"    ,	lowerCAmelCase="[MASK]"    ,	lowerCAmelCase=True    ,	lowerCAmelCase=None    ,	**lowerCAmelCase    ,	):
							super().__init__(
							    lowerCAmelCase    ,	tokenizer_file=lowerCAmelCase    ,	do_lower_case=lowerCAmelCase    ,	unk_token=lowerCAmelCase    ,	sep_token=lowerCAmelCase    ,	pad_token=lowerCAmelCase    ,	cls_token=lowerCAmelCase    ,	mask_token=lowerCAmelCase    ,	tokenize_chinese_chars=lowerCAmelCase    ,	strip_accents=lowerCAmelCase    ,	**lowerCAmelCase    ,	)

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

							UpperCAmelCase_						=				do_lower_case



					def    A__		(			self    ,	lowerCAmelCase    ,	lowerCAmelCase=None     ):
							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    A__		(			self    ,	lowerCAmelCase    ,	lowerCAmelCase = None     ):
							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    A__		(			self    ,	lowerCAmelCase    ,	lowerCAmelCase = None     ):
							UpperCAmelCase_						=				self._tokenizer.model.save(lowerCAmelCase    ,	name=lowerCAmelCase     )
							return tuple(lowerCAmelCase     )

