






"""simple docstring"""





import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase_	:				str										= get_tests_dir("""fixtures/test_sentencepiece.model""")


@require_sentencepiece
@require_tokenizers
class      _lowercase (     lowerCAmelCase		,  unittest.TestCase							):
      _a   :     List[str]								=   ReformerTokenizer
      _a   :     Dict								=   ReformerTokenizerFast
      _a   :     str								=   True
      _a   :     Optional[int]								=   False
      _a   :     Optional[Any]								=   True


      def _UpperCamelCase						(    self				:	str						):





            """simple docstring"""







            super().setUp()

            __snake_case      :    Optional[int]  			=ReformerTokenizer(a							,   keep_accents=a						)
            tokenizer.save_pretrained(self.tmpdirname						)


      def _UpperCamelCase						(    self				:	Union[str, Any]						):





            """simple docstring"""







            __snake_case      :    Union[str, Any]  			='''<s>'''
            __snake_case      :    int  			=1

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


      def _UpperCamelCase						(    self				:	Optional[int]						):





            """simple docstring"""







            __snake_case      :    Dict  			=list(self.get_tokenizer().get_vocab().keys()						)

            self.assertEqual(vocab_keys[0]							,   '''<unk>'''						)
            self.assertEqual(vocab_keys[1]							,   '''<s>'''						)
            self.assertEqual(vocab_keys[-1]							,   '''j'''						)
            self.assertEqual(len(a						)							,   1_0_0_0						)


      def _UpperCamelCase						(    self				:	Union[str, Any]						):





            """simple docstring"""







            self.assertEqual(self.get_tokenizer().vocab_size							,   1_0_0_0						)


      def _UpperCamelCase						(    self				:	Tuple						):





            """simple docstring"""







            if not self.test_rust_tokenizer:
                  return

            __snake_case      :    List[str]  			=self.get_tokenizer()
            __snake_case      :    Optional[Any]  			=self.get_rust_tokenizer()

            __snake_case      :    List[Any]  			='''I was born in 92000, and this is falsé.'''

            __snake_case      :    List[Any]  			=tokenizer.tokenize(a						)
            __snake_case      :    str  			=rust_tokenizer.tokenize(a						)
            self.assertListEqual(a							,   a						)

            __snake_case      :    Optional[Any]  			=tokenizer.encode(a							,   add_special_tokens=a						)
            __snake_case      :    Union[str, Any]  			=rust_tokenizer.encode(a							,   add_special_tokens=a						)
            self.assertListEqual(a							,   a						)

            __snake_case      :    str  			=self.get_rust_tokenizer()
            __snake_case      :    Dict  			=tokenizer.encode(a						)
            __snake_case      :    List[str]  			=rust_tokenizer.encode(a						)
            self.assertListEqual(a							,   a						)


      def _UpperCamelCase						(    self				:	Dict							,   a				:	Optional[Any]=1_5						):





            """simple docstring"""







            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                  with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
                        __snake_case      :    List[str]  			=self.rust_tokenizer_class.from_pretrained(a							,   **a						)

                        # Simple input
                        __snake_case      :    Optional[int]  			='''This is a simple input'''
                        __snake_case      :    Optional[int]  			=['''This is a simple input 1''', '''This is a simple input 2''']
                        __snake_case      :    int  			=('''This is a simple input''', '''This is a pair''')
                        __snake_case      :    int  			=[
                            ('''This is a simple input 1''', '''This is a simple input 2'''),
                            ('''This is a simple pair 1''', '''This is a simple pair 2'''),
                        ]

                        # Simple input tests
                        self.assertRaises(a							,   tokenizer_r.encode							,   a							,   max_length=a							,   padding='''max_length'''						)

                        # Simple input
                        self.assertRaises(a							,   tokenizer_r.encode_plus							,   a							,   max_length=a							,   padding='''max_length'''						)

                        # Simple input
                        self.assertRaises(
                            a							,   tokenizer_r.batch_encode_plus							,   a							,   max_length=a							,   padding='''max_length'''							,   )

                        # Pair input
                        self.assertRaises(a							,   tokenizer_r.encode							,   a							,   max_length=a							,   padding='''max_length'''						)

                        # Pair input
                        self.assertRaises(a							,   tokenizer_r.encode_plus							,   a							,   max_length=a							,   padding='''max_length'''						)

                        # Pair input
                        self.assertRaises(
                            a							,   tokenizer_r.batch_encode_plus							,   a							,   max_length=a							,   padding='''max_length'''							,   )


      def _UpperCamelCase						(    self				:	Optional[Any]						):





            """simple docstring"""







            pass


      def _UpperCamelCase						(    self				:	Optional[Any]						):





            """simple docstring"""







            __snake_case      :    str  			=ReformerTokenizer(a							,   keep_accents=a						)

            __snake_case      :    Tuple  			=tokenizer.tokenize('''This is a test'''						)
            self.assertListEqual(a							,   ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']						)

            self.assertListEqual(
                tokenizer.convert_tokens_to_ids(a						)							,   [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]							,   )

            __snake_case      :    Tuple  			=tokenizer.tokenize('''I was born in 92000, and this is falsé.'''						)
            self.assertListEqual(
                a							,   [
                    SPIECE_UNDERLINE + '''I''',
                    SPIECE_UNDERLINE + '''was''',
                    SPIECE_UNDERLINE + '''b''',
                    '''or''',
                    '''n''',
                    SPIECE_UNDERLINE + '''in''',
                    SPIECE_UNDERLINE + '''''',
                    '''9''',
                    '''2''',
                    '''0''',
                    '''0''',
                    '''0''',
                    ''',''',
                    SPIECE_UNDERLINE + '''and''',
                    SPIECE_UNDERLINE + '''this''',
                    SPIECE_UNDERLINE + '''is''',
                    SPIECE_UNDERLINE + '''f''',
                    '''al''',
                    '''s''',
                    '''é''',
                    '''.''',
                ]							,   )
            __snake_case      :    str  			=tokenizer.convert_tokens_to_ids(a						)
            self.assertListEqual(
                a							,   [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]							,   )

            __snake_case      :    Union[str, Any]  			=tokenizer.convert_ids_to_tokens(a						)
            self.assertListEqual(
                a							,   [
                    SPIECE_UNDERLINE + '''I''',
                    SPIECE_UNDERLINE + '''was''',
                    SPIECE_UNDERLINE + '''b''',
                    '''or''',
                    '''n''',
                    SPIECE_UNDERLINE + '''in''',
                    SPIECE_UNDERLINE + '''''',
                    '''<unk>''',
                    '''2''',
                    '''0''',
                    '''0''',
                    '''0''',
                    ''',''',
                    SPIECE_UNDERLINE + '''and''',
                    SPIECE_UNDERLINE + '''this''',
                    SPIECE_UNDERLINE + '''is''',
                    SPIECE_UNDERLINE + '''f''',
                    '''al''',
                    '''s''',
                    '''<unk>''',
                    '''.''',
                ]							,   )


      @cached_property
      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







            return ReformerTokenizer.from_pretrained('''google/reformer-crime-and-punishment'''						)


      @slow
      def _UpperCamelCase						(    self				:	Dict						):





            """simple docstring"""







            __snake_case      :    List[Any]  			='''Hello World!'''
            __snake_case      :    List[Any]  			=[1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

            self.assertListEqual(a							,   self.big_tokenizer.encode(a						)						)


      @slow
      def _UpperCamelCase						(    self				:	int						):





            """simple docstring"""







            __snake_case      :    Tuple  			=(
                '''This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'''
                ''' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'''
            )
            __snake_case      :    List[Any]  			=[
                1_0_8,
                2_6_5,
                2_4,
                1_1_1,
                4,
                2_5_8,
                1_5_6,
                3_5,
                2_8,
                2_7_5,
                3,
                2_5_9,
                2_9_7,
                2_6_0,
                8_4,
                4,
                3_5,
                1_1_0,
                4_4,
                8,
                2_5_9,
                9_1,
                2_6_8,
                2_1,
                1_1,
                2_0_9,
                2_7_4,
                1_0_9,
                2_6_6,
                2_7_7,
                1_1_7,
                8_6,
                9_3,
                3_1_5,
                2_5_8,
                2_7_8,
                2_5_8,
                2_7_7,
                2_5_8,
                0,
                2_5_8,
                2_8_8,
                2_5_8,
                3_1_9,
                2_5_8,
                0,
                2_5_8,
                0,
                2_5_8,
                0,
                2_5_8,
                0,
                2_5_8,
                2_8_7,
                2_5_8,
                3_1_5,
                2_5_8,
                2_8_9,
                2_5_8,
                2_7_8,
                9_9,
                2_6_9,
                2_6_6,
                2_6_2,
                8,
                2_5_9,
                2_4_1,
                4,
                2_1_7,
                2_3_0,
                2_6_8,
                2_6_6,
                5_5,
                1_6_8,
                1_0_6,
                7_5,
                1_9_3,
                2_6_6,
                2_2_3,
                2_7,
                4_9,
                2_6,
                2_8_2,
                2_5,
                2_6_4,
                2_9_9,
                1_9,
                2_6,
                0,
                2_5_8,
                2_7_7,
                1_1_7,
                8_6,
                9_3,
                1_7_6,
                1_8_3,
                2_7_0,
                1_1,
                2_6_2,
                4_2,
                6_1,
                2_6_5,
            ]

            self.assertListEqual(a							,   self.big_tokenizer.encode(a						)						)


      @require_torch
      @slow
      def _UpperCamelCase						(    self				:	Optional[Any]						):





            """simple docstring"""







            import torch

            from transformers import ReformerConfig, ReformerModel

            # Build sequence
            __snake_case      :    Optional[int]  			=list(self.big_tokenizer.get_vocab().keys()						)[:1_0]
            __snake_case      :    Union[str, Any]  			=''' '''.join(a						)
            __snake_case      :    Optional[int]  			=self.big_tokenizer.encode_plus(a							,   return_tensors='''pt'''						)
            __snake_case      :    Optional[int]  			=self.big_tokenizer.batch_encode_plus([sequence, sequence]							,   return_tensors='''pt'''						)

            __snake_case      :    Optional[int]  			=ReformerConfig()
            # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
            __snake_case      :    Optional[Any]  			=encoded_sequence['''input_ids'''].shape
            __snake_case      :    Tuple  			=ReformerModel(a						)

            # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
            assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

            with torch.no_grad():
                  model(**a						)
                  model(**a						)







      @slow
      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







            __snake_case      :    List[str]  			={'''input_ids''': [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], '''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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
            # fmt: on

            # This tokenizer does not know some characters like ")".
            # That is the reason why we use very simple texts here.
            # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
            __snake_case      :    Union[str, Any]  			=[
                '''This is a very simple sentence.''',
                '''The quick brown fox jumps over the lazy dog.''',
            ]

            self.tokenizer_integration_test_util(
                expected_encoding=a							,   model_name='''google/reformer-crime-and-punishment'''							,   revision='''0e6c3decb8211d49bf881013425dc8b0448b3f5a'''							,   padding=a							,   sequences=a							,   )










"""simple docstring"""





import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


UpperCamelCase_	:				Optional[Any]										= logging.get_logger(__name__)

UpperCamelCase_	:				Union[str, Any]										= {"""vocab_file""": """sentencepiece.bpe.model"""}

UpperCamelCase_	:				Optional[Any]										= {
    """vocab_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"""
        ),
    },
}

UpperCamelCase_	:				int										= {
    """moussaKam/mbarthez""": 1024,
    """moussaKam/barthez""": 1024,
    """moussaKam/barthez-orangesum-title""": 1024,
}

UpperCamelCase_	:				Optional[int]										= """▁"""


class      _lowercase (     lowerCAmelCase						):
      _a   :     int								=   VOCAB_FILES_NAMES
      _a   :     int								=   PRETRAINED_VOCAB_FILES_MAP
      _a   :     Union[str, Any]								=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _a   :     Optional[int]								=   ['''input_ids''', '''attention_mask''']


      def __init__(    self				:	str							,   a				:	Optional[Any]							,   a				:	Optional[Any]="<s>"							,   a				:	Dict="</s>"							,   a				:	Any="</s>"							,   a				:	Optional[int]="<s>"							,   a				:	Optional[Any]="<unk>"							,   a				:	int="<pad>"							,   a				:	Tuple="<mask>"							,   a				:	Optional[Dict[str, Any]] = None							,   **a				:	List[Any]							,   ):





            """simple docstring"""







            __snake_case      :    Dict  			=AddedToken(a							,   lstrip=a							,   rstrip=a						) if isinstance(a							,   a						) else mask_token

            __snake_case      :    List[str]  			={} if sp_model_kwargs is None else sp_model_kwargs

            super().__init__(
                bos_token=a							,   eos_token=a							,   unk_token=a							,   sep_token=a							,   cls_token=a							,   pad_token=a							,   mask_token=a							,   sp_model_kwargs=self.sp_model_kwargs							,   **a							,   )

            __snake_case      :    Optional[int]  			=vocab_file
            __snake_case      :    Dict  			=spm.SentencePieceProcessor(**self.sp_model_kwargs						)
            self.sp_model.Load(str(a						)						)

            __snake_case      :    Optional[Any]  			={'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

            __snake_case      :    Optional[int]  			=len(self.sp_model						) - 1
            __snake_case      :    Union[str, Any]  			={v: k for k, v in self.fairseq_tokens_to_ids.items()}


      def _UpperCamelCase						(    self				:	Tuple							,   a				:	List[int]							,   a				:	Optional[List[int]] = None						):





            """simple docstring"""







            if token_ids_a is None:
                  return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
            __snake_case      :    Dict  			=[self.cls_token_id]
            __snake_case      :    List[str]  			=[self.sep_token_id]
            return cls + token_ids_a + sep + sep + token_ids_a + sep


      def _UpperCamelCase						(    self				:	str							,   a				:	List[int]							,   a				:	Optional[List[int]] = None							,   a				:	bool = False						):





            """simple docstring"""







            if already_has_special_tokens:
                  return super().get_special_tokens_mask(
                      token_ids_a=a							,   token_ids_a=a							,   already_has_special_tokens=a						)

            if token_ids_a is None:
                  return [1] + ([0] * len(a						)) + [1]
            return [1] + ([0] * len(a						)) + [1, 1] + ([0] * len(a						)) + [1]


      def _UpperCamelCase						(    self				:	Dict							,   a				:	List[int]							,   a				:	Optional[List[int]] = None						):





            """simple docstring"""







            __snake_case      :    Optional[int]  			=[self.sep_token_id]
            __snake_case      :    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 + sep + token_ids_a + sep						) * [0]


      @property
      def _UpperCamelCase						(    self				:	List[Any]						):





            """simple docstring"""







            return len(self.sp_model						)


      def _UpperCamelCase						(    self				:	Union[str, Any]						):





            """simple docstring"""







            __snake_case      :    List[Any]  			={self.convert_ids_to_tokens(a						): i for i in range(self.vocab_size						)}
            vocab.update(self.added_tokens_encoder						)
            return vocab


      def _UpperCamelCase						(    self				:	str							,   a				:	str						):





            """simple docstring"""







            return self.sp_model.encode(a							,   out_type=a						)


      def _UpperCamelCase						(    self				:	int							,   a				:	Union[str, Any]						):





            """simple docstring"""







            if token in self.fairseq_tokens_to_ids:
                  return self.fairseq_tokens_to_ids[token]
            __snake_case      :    List[Any]  			=self.sp_model.PieceToId(a						)

            return spm_id if spm_id else self.unk_token_id


      def _UpperCamelCase						(    self				:	List[str]							,   a				:	Dict						):





            """simple docstring"""







            if index in self.fairseq_ids_to_tokens:
                  return self.fairseq_ids_to_tokens[index]
            return self.sp_model.IdToPiece(a						)


      def _UpperCamelCase						(    self				:	Optional[int]							,   a				:	int						):





            """simple docstring"""







            __snake_case      :    int  			=[]
            __snake_case      :    Optional[int]  			=''''''
            __snake_case      :    Optional[int]  			=False
            for token in tokens:
                  # make sure that special tokens are not decoded using sentencepiece model
                  if token in self.all_special_tokens:
                        if not prev_is_special:
                              out_string += " "
                        out_string += self.sp_model.decode(a						) + token
                        __snake_case      :    str  			=True
                        __snake_case      :    int  			=[]
                  else:
                        current_sub_tokens.append(a						)
                        __snake_case      :    Tuple  			=False
            out_string += self.sp_model.decode(a						)
            return out_string.strip()


      def __getstate__(    self				:	Optional[int]						):





            """simple docstring"""







            __snake_case      :    List[Any]  			=self.__dict__.copy()
            __snake_case      :    Optional[Any]  			=None
            return state


      def __setstate__(    self				:	Optional[int]							,   a				:	Optional[Any]						):





            """simple docstring"""







            __snake_case      :    Any  			=d

            # for backward compatibility
            if not hasattr(self							,   '''sp_model_kwargs'''						):
                  __snake_case      :    Tuple  			={}

            __snake_case      :    int  			=spm.SentencePieceProcessor(**self.sp_model_kwargs						)
            self.sp_model.Load(self.vocab_file						)







      def _UpperCamelCase						(    self				:	Optional[Any]							,   a				:	str							,   a				:	Optional[str] = None						):





            """simple docstring"""







            if not os.path.isdir(a						):
                  logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
                  return
            __snake_case      :    int  			=os.path.join(
                a							,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)

            if os.path.abspath(self.vocab_file						) != os.path.abspath(a						) and os.path.isfile(self.vocab_file						):
                  copyfile(self.vocab_file							,   a						)
            elif not os.path.isfile(self.vocab_file						):
                  with open(a							,   '''wb'''						) as fi:
                        __snake_case      :    List[Any]  			=self.sp_model.serialized_model_proto()
                        fi.write(a						)

            return (out_vocab_file,)


