


'''simple docstring'''






import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class        __snake_case	(       _SCREAMING_SNAKE_CASE     ,unittest.TestCase):







    """simple docstring"""



    lowercase       			= BarthezTokenizer
    lowercase       			= BarthezTokenizerFast
    lowercase       			= True
    lowercase       			= True

    def __lowercase       (       self   :  Optional[Any]		)       ->  Tuple:
      super().setUp()

      lowerCAmelCase_      :				Dict      =       BarthezTokenizerFast.from_pretrained("""moussaKam/mbarthez"""		)
      tokenizer.save_pretrained(self.tmpdirname		)
      tokenizer.save_pretrained(self.tmpdirname   ,						legacy_format=lowerCamelCase		)
      lowerCAmelCase_      :				List[Any]      =       tokenizer

    def __lowercase       (       self   :  Any		)       ->  Optional[Any]:
      lowerCAmelCase_      :				str      =       """<pad>"""
      lowerCAmelCase_      :				Any      =       1

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

    def __lowercase       (       self   :  str		)       ->  str:
      lowerCAmelCase_      :				List[str]      =       list(self.get_tokenizer().get_vocab().keys()		)

      self.assertEqual(vocab_keys[0]   ,						"""<s>"""		)
      self.assertEqual(vocab_keys[1]   ,						"""<pad>"""		)
      self.assertEqual(vocab_keys[-1]   ,						"""<mask>"""		)
      self.assertEqual(len(lowerCamelCase		)   ,						10_11_22		)

    def __lowercase       (       self   :  Union[str, Any]		)       ->  Dict:
      self.assertEqual(self.get_tokenizer().vocab_size   ,						10_11_22		)

    @require_torch
    def __lowercase       (       self   :  str		)       ->  Tuple:
      lowerCAmelCase_      :				int      =       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
      lowerCAmelCase_      :				Any      =       [0, 57, 30_18, 7_03_07, 91, 2]

      lowerCAmelCase_      :				Any      =       self.tokenizer(
          lowerCamelCase   ,						max_length=len(lowerCamelCase		)   ,						padding=lowerCamelCase   ,						truncation=lowerCamelCase   ,						return_tensors="""pt"""		)
      self.assertIsInstance(lowerCamelCase   ,						lowerCamelCase		)

      self.assertEqual((2, 6)   ,						batch.input_ids.shape		)
      self.assertEqual((2, 6)   ,						batch.attention_mask.shape		)
      lowerCAmelCase_      :				Any      =       batch.input_ids.tolist()[0]
      self.assertListEqual(lowerCamelCase   ,						lowerCamelCase		)

    def __lowercase       (       self   :  Dict		)       ->  Any:
      if not self.test_rust_tokenizer:
        return

      lowerCAmelCase_      :				Union[str, Any]      =       self.get_tokenizer()
      lowerCAmelCase_      :				Union[str, Any]      =       self.get_rust_tokenizer()

      lowerCAmelCase_      :				Union[str, Any]      =       """I was born in 92000, and this is falsé."""

      lowerCAmelCase_      :				Dict      =       tokenizer.tokenize(lowerCamelCase		)
      lowerCAmelCase_      :				Optional[Any]      =       rust_tokenizer.tokenize(lowerCamelCase		)
      self.assertListEqual(lowerCamelCase   ,						lowerCamelCase		)

      lowerCAmelCase_      :				int      =       tokenizer.encode(lowerCamelCase   ,						add_special_tokens=lowerCamelCase		)
      lowerCAmelCase_      :				int      =       rust_tokenizer.encode(lowerCamelCase   ,						add_special_tokens=lowerCamelCase		)
      self.assertListEqual(lowerCamelCase   ,						lowerCamelCase		)

      lowerCAmelCase_      :				Optional[Any]      =       self.get_rust_tokenizer()
      lowerCAmelCase_      :				Optional[Any]      =       tokenizer.encode(lowerCamelCase		)
      lowerCAmelCase_      :				Any      =       rust_tokenizer.encode(lowerCamelCase		)
      self.assertListEqual(lowerCamelCase   ,						lowerCamelCase		)





    @slow
    def __lowercase       (       self   :  Dict		)       ->  List[Any]:
      # fmt: off
      lowerCAmelCase_      :				int      =       {"""input_ids""": [[0, 4_90, 1_43_28, 45_07, 3_54, 47, 4_36_69, 95, 25, 7_81_17, 2_02_15, 1_97_79, 1_90, 22, 4_00, 4, 3_53_43, 8_03_10, 6_03, 86, 2_49_37, 1_05, 3_34_38, 9_47_62, 1_96, 3_96_42, 7, 15, 1_59_33, 1_73, 2, 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, 1_05_34, 87, 25, 66, 33_58, 1_96, 5_52_89, 8, 8_29_61, 81, 22_04, 7_52_03, 7, 15, 7_63, 1_29_56, 2_16, 1_78, 1_43_28, 95_95, 13_77, 6_96_93, 7, 4_48, 7_10_21, 1_96, 1_81_06, 14_37, 1_39_74, 1_08, 90_83, 4, 4_93_15, 7, 39, 86, 13_26, 27_93, 4_63_33, 4, 4_48, 1_96, 7_45_88, 7, 4_93_15, 7, 39, 21, 8_22, 3_84_70, 74, 21, 6_67_23, 6_24_80, 8, 2_20_50, 5, 2]], """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, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
      # fmt: on

      # moussaKam/mbarthez is a french model. So we also use french texts.
      lowerCAmelCase_      :				str      =       [
          """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="""moussaKam/mbarthez"""   ,						revision="""c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6"""   ,						sequences=lowerCamelCase   ,						)







'''simple docstring'''






import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


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

__A :  int    							=				{
    "vocab_file": {
        "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt",
    },
    "tokenizer_file": {
        "unc-nlp/lxmert-base-uncased": (
            "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json"
        ),
    },
}

__A :  List[Any]    							=				{
    "unc-nlp/lxmert-base-uncased": 512,
}

__A :  Optional[Any]    							=				{
    "unc-nlp/lxmert-base-uncased": {"do_lower_case": True},
}






class        __snake_case	(       _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase       			= VOCAB_FILES_NAMES
    lowercase       			= PRETRAINED_VOCAB_FILES_MAP
    lowercase       			= PRETRAINED_INIT_CONFIGURATION
    lowercase       			= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase       			= LxmertTokenizer

    def __init__(       self   :  Dict   ,						lowerCamelCase   :  Tuple=None   ,						lowerCamelCase   :  List[str]=None   ,						lowerCamelCase   :  Dict=True   ,						lowerCamelCase   :  List[Any]="[UNK]"   ,						lowerCamelCase   :  Tuple="[SEP]"   ,						lowerCamelCase   :  str="[PAD]"   ,						lowerCamelCase   :  Any="[CLS]"   ,						lowerCamelCase   :  str="[MASK]"   ,						lowerCamelCase   :  Dict=True   ,						lowerCamelCase   :  Union[str, Any]=None   ,						**lowerCamelCase   :  Optional[int]   ,						)       ->  Optional[Any]:
      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   ,						)

      lowerCAmelCase_      :				Optional[Any]      =       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
      ):
        lowerCAmelCase_      :				Tuple      =       getattr(lowerCamelCase   ,						normalizer_state.pop("""type"""		)		)
        lowerCAmelCase_      :				Optional[Any]      =       do_lower_case
        lowerCAmelCase_      :				Dict      =       strip_accents
        lowerCAmelCase_      :				List[Any]      =       tokenize_chinese_chars
        lowerCAmelCase_      :				List[Any]      =       normalizer_class(**lowerCamelCase		)

      lowerCAmelCase_      :				Tuple      =       do_lower_case

    def __lowercase       (       self   :  Tuple   ,						lowerCamelCase   :  str   ,						lowerCamelCase   :  Optional[Any]=None		)       ->  int:
      lowerCAmelCase_      :				Any      =       [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 __lowercase       (       self   :  str   ,						lowerCamelCase   :  List[int]   ,						lowerCamelCase   :  Optional[List[int]] = None		)       ->  List[int]:
      lowerCAmelCase_      :				str      =       [self.sep_token_id]
      lowerCAmelCase_      :				Optional[int]      =       [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 __lowercase       (       self   :  Tuple   ,						lowerCamelCase   :  str   ,						lowerCamelCase   :  Optional[str] = None		)       ->  Tuple[str]:
      lowerCAmelCase_      :				int      =       self._tokenizer.model.save(lowerCamelCase   ,						name=lowerCamelCase		)
      return tuple(lowerCamelCase		)



