





"""simple docstring"""




import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

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


if TYPE_CHECKING:
      from transformers.pipelines.conversational import Conversation

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


__UpperCAmelCase	:       List[Any]    	=							{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

__UpperCAmelCase	:       int    	=							{
    "vocab_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json"},
    "merges_file": {"facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt"},
    "tokenizer_config_file": {
        "facebook/blenderbot-3B": "https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json"
    },
}

__UpperCAmelCase	:       Union[str, Any]    	=							{"facebook/blenderbot-3B": 128}







@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def       A__							(   )       ->   List[Any]:
  __snake_case:						str			  =						(
      list(range(ord("""!""") , ord("""~""") + 1)) + list(range(ord("""¡""") , ord("""¬""") + 1)) + list(range(ord("""®""") , ord("""ÿ""") + 1))
  )
  __snake_case:						Tuple			  =						bs[:]
  __snake_case:						Optional[int]			  =						0
  for b in range(2**8):
    if b not in bs:
      bs.append(__UpperCAmelCase)
      cs.append(2**8 + n)
      n += 1
  __snake_case:						Dict			  =						[chr(__UpperCAmelCase) for n in cs]
  return dict(zip(__UpperCAmelCase , __UpperCAmelCase))







def       A__							(   SCREAMING_SNAKE_CASE__)       ->   Dict:
  __snake_case:						Dict			  =						set()
  __snake_case:						Dict			  =						word[0]
  for char in word[1:]:
    pairs.add((prev_char, char))
    __snake_case:						Tuple			  =						char
  return pairs







class    __snake_case	(							_UpperCAmelCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					VOCAB_FILES_NAMES
       lowerCAmelCase__						=					PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__						=					["input_ids", "attention_mask"]




       def __init__(  self			:   Optional[Any]							,    A			:   Dict							,    A			:   Optional[int]							,    A			:   Optional[Any]="replace"							,    A			:   Tuple="<s>"							,    A			:   Any="</s>"							,    A			:   List[Any]="</s>"							,    A			:   Tuple="<s>"							,    A			:   int="<unk>"							,    A			:   Dict="<pad>"							,    A			:   int="<mask>"							,    A			:   Tuple=False							,    **A			:   int							,    ):
         __snake_case:						List[Any]			  =						AddedToken(_UpperCAmelCase							,    lstrip=_UpperCAmelCase							,    rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase							,    _UpperCAmelCase		) else bos_token
         __snake_case:						str			  =						AddedToken(_UpperCAmelCase							,    lstrip=_UpperCAmelCase							,    rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase							,    _UpperCAmelCase		) else eos_token
         __snake_case:						Dict			  =						AddedToken(_UpperCAmelCase							,    lstrip=_UpperCAmelCase							,    rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase							,    _UpperCAmelCase		) else sep_token
         __snake_case:						Dict			  =						AddedToken(_UpperCAmelCase							,    lstrip=_UpperCAmelCase							,    rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase							,    _UpperCAmelCase		) else cls_token
         __snake_case:						Optional[int]			  =						AddedToken(_UpperCAmelCase							,    lstrip=_UpperCAmelCase							,    rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase							,    _UpperCAmelCase		) else unk_token
         __snake_case:						str			  =						AddedToken(_UpperCAmelCase							,    lstrip=_UpperCAmelCase							,    rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase							,    _UpperCAmelCase		) else pad_token

         # Mask token behave like a normal word, i.e. include the space before it
         __snake_case:						Optional[Any]			  =						AddedToken(_UpperCAmelCase							,    lstrip=_UpperCAmelCase							,    rstrip=_UpperCAmelCase		) if isinstance(_UpperCAmelCase							,    _UpperCAmelCase		) else mask_token

         super().__init__(
             errors=_UpperCAmelCase							,    bos_token=_UpperCAmelCase							,    eos_token=_UpperCAmelCase							,    unk_token=_UpperCAmelCase							,    sep_token=_UpperCAmelCase							,    cls_token=_UpperCAmelCase							,    pad_token=_UpperCAmelCase							,    mask_token=_UpperCAmelCase							,    add_prefix_space=_UpperCAmelCase							,    **_UpperCAmelCase							,    )

         with open(_UpperCAmelCase							,    encoding="""utf-8"""		) as vocab_handle:
           __snake_case:						Any			  =						json.load(_UpperCAmelCase		)
         __snake_case:						Union[str, Any]			  =						{v: k for k, v in self.encoder.items()}
         __snake_case:						List[str]			  =						errors  # how to handle errors in decoding
         __snake_case:						Optional[int]			  =						bytes_to_unicode()
         __snake_case:						Optional[Any]			  =						{v: k for k, v in self.byte_encoder.items()}
         with open(_UpperCAmelCase							,    encoding="""utf-8"""		) as merges_handle:
           __snake_case:						List[Any]			  =						merges_handle.read().split("""\n"""		)[1:-1]
         __snake_case:						Dict			  =						[tuple(merge.split()		) for merge in bpe_merges]
         __snake_case:						List[str]			  =						dict(zip(_UpperCAmelCase							,    range(len(_UpperCAmelCase		)		)		)		)
         __snake_case:						Union[str, Any]			  =						{}
         __snake_case:						List[Any]			  =						add_prefix_space

         # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
         __snake_case:						Dict			  =						re.compile(r"""\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""		)




       @property
       # Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
       def 							UpperCAmelCase__			(  self			:   Optional[Any]		):
         return len(self.encoder		)




       def 							UpperCAmelCase__			(  self			:   Optional[int]		):
         return dict(self.encoder							,    **self.added_tokens_encoder		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]							,    A			:   List[str]		):
         if token in self.cache:
           return self.cache[token]
         __snake_case:						Any			  =						tuple(_UpperCAmelCase		)
         __snake_case:						Optional[int]			  =						get_pairs(_UpperCAmelCase		)

         if not pairs:
           return token

         while True:
           __snake_case:						str			  =						min(_UpperCAmelCase							,    key=lambda A		: self.bpe_ranks.get(_UpperCAmelCase							,    float("""inf"""		)		)		)
           if bigram not in self.bpe_ranks:
             break
           __snake_case:						str			  =						bigram
           __snake_case:						str			  =						[]
           __snake_case:						Optional[Any]			  =						0
           while i < len(_UpperCAmelCase		):
             try:
               __snake_case:						Any			  =						word.index(_UpperCAmelCase							,    _UpperCAmelCase		)
             except ValueError:
               new_word.extend(word[i:]		)
               break
             else:
               new_word.extend(word[i:j]		)
               __snake_case:						Tuple			  =						j

             if word[i] == first and i < len(_UpperCAmelCase		) - 1 and word[i + 1] == second:
               new_word.append(first + second		)
               i += 2
             else:
               new_word.append(word[i]		)
               i += 1
           __snake_case:						int			  =						tuple(_UpperCAmelCase		)
           __snake_case:						List[Any]			  =						new_word
           if len(_UpperCAmelCase		) == 1:
             break
           else:
             __snake_case:						Tuple			  =						get_pairs(_UpperCAmelCase		)
         __snake_case:						str			  =						''' '''.join(_UpperCAmelCase		)
         __snake_case:						Dict			  =						word
         return word




       def 							UpperCAmelCase__			(  self			:   Optional[Any]							,    A			:   str		):
         __snake_case:						List[Any]			  =						[]
         for token in re.findall(self.pat							,    _UpperCAmelCase		):
           __snake_case:						Optional[Any]			  =						''''''.join(
               self.byte_encoder[b] for b in token.encode("""utf-8"""		)		)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
           bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_UpperCAmelCase		).split(""" """		)		)
         return bpe_tokens




       def 							UpperCAmelCase__			(  self			:   int							,    A			:   int		):
         return self.encoder.get(_UpperCAmelCase							,    self.encoder.get(self.unk_token		)		)




       def 							UpperCAmelCase__			(  self			:   List[Any]							,    A			:   str		):
         return self.decoder.get(_UpperCAmelCase		)




       def 							UpperCAmelCase__			(  self			:   Optional[int]							,    A			:   Tuple		):
         __snake_case:						List[str]			  =						''''''.join(_UpperCAmelCase		)
         __snake_case:						int			  =						bytearray([self.byte_decoder[c] for c in text]		).decode("""utf-8"""							,    errors=self.errors		)
         return text




       def 							UpperCAmelCase__			(  self			:   Optional[Any]							,    A			:   Optional[int]							,    A			:   Union[str, Any] = None		):
         if not os.path.isdir(_UpperCAmelCase		):
           logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
           return
         __snake_case:						str			  =						os.path.join(
             _UpperCAmelCase							,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)
         __snake_case:						List[str]			  =						os.path.join(
             _UpperCAmelCase							,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]		)

         with open(_UpperCAmelCase							,    """w"""							,    encoding="""utf-8"""		) as f:
           f.write(json.dumps(self.encoder							,    indent=2							,    sort_keys=_UpperCAmelCase							,    ensure_ascii=_UpperCAmelCase		) + """\n"""		)

         __snake_case:						str			  =						0
         with open(_UpperCAmelCase							,    """w"""							,    encoding="""utf-8"""		) as writer:
           writer.write("""#version: 0.2\n"""		)
           for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							,    key=lambda A		: kv[1]		):
             if index != token_index:
               logger.warning(
                   f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                   """ Please check that the tokenizer is not corrupted!"""		)
               __snake_case:						str			  =						token_index
             writer.write(""" """.join(_UpperCAmelCase		) + """\n"""		)
             index += 1

         return vocab_file, merge_file




       def 							UpperCAmelCase__			(  self			:   int							,    A			:   Tuple							,    A			:   Optional[Any] = None							,    A			:   Union[str, Any] = False		):
         if already_has_special_tokens:
           return super().get_special_tokens_mask(
               token_ids_a=_UpperCAmelCase							,    token_ids_a=_UpperCAmelCase							,    already_has_special_tokens=_UpperCAmelCase		)

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




       def 							UpperCAmelCase__			(  self			:   Optional[Any]							,    A			:   Union[str, Any]							,    A			:   List[Any] = None		):
         __snake_case:						Optional[int]			  =						[self.sep_token_id]
         __snake_case:						List[Any]			  =						[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]




       def 							UpperCAmelCase__			(  self			:   Optional[Any]							,    A			:   int							,    A			:   List[Any]=False							,    **A			:   Union[str, Any]		):
         __snake_case:						Optional[Any]			  =						kwargs.pop("""add_prefix_space"""							,    self.add_prefix_space		)
         if (is_split_into_words or add_prefix_space) and (len(_UpperCAmelCase		) > 0 and not text[0].isspace()):
           __snake_case:						Any			  =						''' ''' + text
         return (text, kwargs)




       def 							UpperCAmelCase__			(  self			:   Any							,    A			:   Tuple							,    A			:   List[Any] = None		):
         return token_ids_a + [self.eos_token_id]






       def 							UpperCAmelCase__			(  self			:   Any							,    A			:   Dict		):
         __snake_case:						Optional[Any]			  =						[]
         for is_user, text in conversation.iter_texts():
           if is_user:
             # We need to space prefix as it's being done within blenderbot
             inputs.append(""" """ + text		)
           else:
             # Generated responses should contain them already.
             inputs.append(_UpperCAmelCase		)

         __snake_case:						Optional[int]			  =						'''  '''.join(_UpperCAmelCase		)
         __snake_case:						str			  =						self.encode(_UpperCAmelCase		)
         if len(_UpperCAmelCase		) > self.model_max_length:
           __snake_case:						Dict			  =						input_ids[-self.model_max_length :]
           logger.warning(f'''Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'''		)
         return input_ids













import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


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

if is_torch_available():
      from transformers.models.mbart.modeling_mbart import shift_tokens_right

__UpperCAmelCase	:       Any    	=							250_004
__UpperCAmelCase	:       List[str]    	=							250_020







@require_sentencepiece
@require_tokenizers
class    __snake_case	(							__lowerCamelCase       ,      unittest.TestCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					MBartaaTokenizer
       lowerCAmelCase__						=					MBartaaTokenizerFast
       lowerCAmelCase__						=					True
       lowerCAmelCase__						=					True




       def 							UpperCAmelCase__			(  self			:   Tuple		):
         super().setUp()

         # We have a SentencePiece fixture for testing
         __snake_case:						Optional[int]			  =						MBartaaTokenizer(A							,    src_lang="""en_XX"""							,    tgt_lang="""ro_RO"""							,    keep_accents=A		)
         tokenizer.save_pretrained(self.tmpdirname		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         __snake_case:						Any			  =						"""<s>"""
         __snake_case:						Tuple			  =						0

         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			:   Any		):
         __snake_case:						Dict			  =						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(A		)							,    1_054		)




       def 							UpperCAmelCase__			(  self			:   Any		):
         self.assertEqual(self.get_tokenizer().vocab_size							,    1_054		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         __snake_case:						Dict			  =						MBartaaTokenizer(A							,    src_lang="""en_XX"""							,    tgt_lang="""ro_RO"""							,    keep_accents=A		)

         __snake_case:						int			  =						tokenizer.tokenize("""This is a test"""		)
         self.assertListEqual(A							,    ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(A		)							,    [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]							,    )

         __snake_case:						Union[str, Any]			  =						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:						List[Any]			  =						tokenizer.convert_tokens_to_ids(A		)
         self.assertListEqual(
             A							,    [
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]							,    )

         __snake_case:						int			  =						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>""", """."""]							,    )




       @slow
       def 							UpperCAmelCase__			(  self			:   Optional[int]		):
         # fmt: off
         __snake_case:						List[str]			  =						{"""input_ids""": [[250_004, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [250_004, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 7, 5, 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, 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], [250_004, 581, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 5, 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, 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, 1, 1, 1, 1]], """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, 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, 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, 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, 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, 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, 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, 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, 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, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=A							,    model_name="""facebook/mbart-large-50"""							,    revision="""d3913889c59cd5c9e456b269c376325eabad57e2"""							,    )






       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         if not self.test_slow_tokenizer:
           # as we don't have a slow version, we can't compare the outputs between slow and fast versions
           return

         __snake_case:						Any			  =						(self.rust_tokenizer_class, """hf-internal-testing/tiny-random-mbart50""", {})
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
             __snake_case:						Optional[int]			  =						self.rust_tokenizer_class.from_pretrained(A							,    **A		)
             __snake_case:						Union[str, Any]			  =						self.tokenizer_class.from_pretrained(A							,    **A		)

             __snake_case:						List[str]			  =						tempfile.mkdtemp()

             __snake_case:						Tuple			  =						tokenizer_r.save_pretrained(A		)
             __snake_case:						Optional[int]			  =						tokenizer_p.save_pretrained(A		)

             # Checks it save with the same files + the tokenizer.json file for the fast one
             self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files		)		)
             __snake_case:						Dict			  =						tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f		)
             self.assertSequenceEqual(A							,    A		)

             # Checks everything loads correctly in the same way
             __snake_case:						Tuple			  =						tokenizer_r.from_pretrained(A		)
             __snake_case:						Optional[Any]			  =						tokenizer_p.from_pretrained(A		)

             # Check special tokens are set accordingly on Rust and Python
             for key in tokenizer_pp.special_tokens_map:
               self.assertTrue(hasattr(A							,    A		)		)
               # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
               # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

             shutil.rmtree(A		)

             # Save tokenizer rust, legacy_format=True
             __snake_case:						Tuple			  =						tempfile.mkdtemp()

             __snake_case:						Any			  =						tokenizer_r.save_pretrained(A							,    legacy_format=A		)
             __snake_case:						List[str]			  =						tokenizer_p.save_pretrained(A		)

             # Checks it save with the same files
             self.assertSequenceEqual(A							,    A		)

             # Checks everything loads correctly in the same way
             __snake_case:						List[Any]			  =						tokenizer_r.from_pretrained(A		)
             __snake_case:						Dict			  =						tokenizer_p.from_pretrained(A		)

             # Check special tokens are set accordingly on Rust and Python
             for key in tokenizer_pp.special_tokens_map:
               self.assertTrue(hasattr(A							,    A		)		)

             shutil.rmtree(A		)

             # Save tokenizer rust, legacy_format=False
             __snake_case:						List[str]			  =						tempfile.mkdtemp()

             __snake_case:						Any			  =						tokenizer_r.save_pretrained(A							,    legacy_format=A		)
             __snake_case:						Dict			  =						tokenizer_p.save_pretrained(A		)

             # Checks it saved the tokenizer.json file
             self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files		)		)

             # Checks everything loads correctly in the same way
             __snake_case:						Any			  =						tokenizer_r.from_pretrained(A		)
             __snake_case:						Any			  =						tokenizer_p.from_pretrained(A		)

             # Check special tokens are set accordingly on Rust and Python
             for key in tokenizer_pp.special_tokens_map:
               self.assertTrue(hasattr(A							,    A		)		)

             shutil.rmtree(A		)







@require_torch
@require_sentencepiece
@require_tokenizers
class    __snake_case	(							unittest.TestCase      ):





       '''simple docstring'''







       lowerCAmelCase__						=					"""facebook/mbart-large-50-one-to-many-mmt"""
       lowerCAmelCase__						=					[
           """ UN Chief Says There Is No Military Solution in Syria""",
           """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
       ]
       lowerCAmelCase__						=					[
           """Şeful ONU declară că nu există o soluţie militară în Siria""",
           """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
           """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
           """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
       ]
       lowerCAmelCase__						=					[EN_CODE, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]




       @classmethod
       def 							UpperCAmelCase__			(  cls			:   int		):
         __snake_case:						MBartaaTokenizer			  =						MBartaaTokenizer.from_pretrained(
             cls.checkpoint_name							,    src_lang="""en_XX"""							,    tgt_lang="""ro_RO"""		)
         __snake_case:						str			  =						1
         return cls




       def 							UpperCAmelCase__			(  self			:   Any		):
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ar_AR"""]							,    250_001		)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""en_EN"""]							,    250_004		)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""ro_RO"""]							,    250_020		)
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["""mr_IN"""]							,    250_038		)




       def 							UpperCAmelCase__			(  self			:   Optional[int]		):
         __snake_case:						List[str]			  =						self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
         self.assertListEqual(self.expected_src_tokens							,    A		)




       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         self.assertIn(A							,    self.tokenizer.all_special_ids		)
         __snake_case:						Dict			  =						[RO_CODE, 884, 9_019, 96, 9, 916, 86_792, 36, 18_743, 15_596, 5, 2]
         __snake_case:						str			  =						self.tokenizer.decode(A							,    skip_special_tokens=A		)
         __snake_case:						Union[str, Any]			  =						self.tokenizer.decode(generated_ids[1:]							,    skip_special_tokens=A		)
         self.assertEqual(A							,    A		)
         self.assertNotIn(self.tokenizer.eos_token							,    A		)




       def 							UpperCAmelCase__			(  self			:   Dict		):
         __snake_case:						List[str]			  =						["""this is gunna be a long sentence """ * 20]
         assert isinstance(src_text[0]							,    A		)
         __snake_case:						Union[str, Any]			  =						10
         __snake_case:						List[Any]			  =						self.tokenizer(A							,    max_length=A							,    truncation=A		).input_ids[0]
         self.assertEqual(ids[0]							,    A		)
         self.assertEqual(ids[-1]							,    2		)
         self.assertEqual(len(A		)							,    A		)




       def 							UpperCAmelCase__			(  self			:   Tuple		):
         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """ar_AR"""]		)							,    [250_053, 250_001]		)




       def 							UpperCAmelCase__			(  self			:   List[Any]		):
         __snake_case:						List[Any]			  =						tempfile.mkdtemp()
         __snake_case:						Any			  =						self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(A		)
         __snake_case:						Union[str, Any]			  =						MBartaaTokenizer.from_pretrained(A		)
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids							,    A		)




       @require_torch
       def 							UpperCAmelCase__			(  self			:   Optional[int]		):
         __snake_case:						List[str]			  =						self.tokenizer(self.src_text							,    text_target=self.tgt_text							,    padding=A							,    return_tensors="""pt"""		)
         __snake_case:						List[Any]			  =						shift_tokens_right(batch["""labels"""]							,    self.tokenizer.pad_token_id		)

         # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
         assert batch.input_ids[1][0] == EN_CODE
         assert batch.input_ids[1][-1] == 2
         assert batch.labels[1][0] == RO_CODE
         assert batch.labels[1][-1] == 2
         assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]




       @require_torch
       def 							UpperCAmelCase__			(  self			:   Optional[int]		):
         __snake_case:						int			  =						self.tokenizer(
             self.src_text							,    text_target=self.tgt_text							,    padding=A							,    truncation=A							,    max_length=len(self.expected_src_tokens		)							,    return_tensors="""pt"""							,    )
         __snake_case:						Optional[Any]			  =						shift_tokens_right(batch["""labels"""]							,    self.tokenizer.pad_token_id		)

         self.assertIsInstance(A							,    A		)

         self.assertEqual((2, 14)							,    batch.input_ids.shape		)
         self.assertEqual((2, 14)							,    batch.attention_mask.shape		)
         __snake_case:						List[str]			  =						batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens							,    A		)
         self.assertEqual(2							,    batch.decoder_input_ids[0, 0]		)  # decoder_start_token_id
         # Test that special tokens are reset
         self.assertEqual(self.tokenizer.prefix_tokens							,    [EN_CODE]		)
         self.assertEqual(self.tokenizer.suffix_tokens							,    [self.tokenizer.eos_token_id]		)




       def 							UpperCAmelCase__			(  self			:   str		):
         __snake_case:						List[Any]			  =						self.tokenizer(self.src_text							,    padding=A							,    truncation=A							,    max_length=3							,    return_tensors="""pt"""		)
         __snake_case:						Union[str, Any]			  =						self.tokenizer(
             text_target=self.tgt_text							,    padding=A							,    truncation=A							,    max_length=10							,    return_tensors="""pt"""		)
         __snake_case:						Dict			  =						targets["""input_ids"""]
         __snake_case:						Any			  =						shift_tokens_right(A							,    self.tokenizer.pad_token_id		)

         self.assertEqual(batch.input_ids.shape[1]							,    3		)
         self.assertEqual(batch.decoder_input_ids.shape[1]							,    10		)






       @require_torch
       def 							UpperCAmelCase__			(  self			:   Union[str, Any]		):
         __snake_case:						int			  =						self.tokenizer._build_translation_inputs(
             """A test"""							,    return_tensors="""pt"""							,    src_lang="""en_XX"""							,    tgt_lang="""ar_AR"""		)

         self.assertEqual(
             nested_simplify(A		)							,    {
                 # en_XX, A, test, EOS
                 """input_ids""": [[250_004, 62, 3_034, 2]],
                 """attention_mask""": [[1, 1, 1, 1]],
                 # ar_AR
                 """forced_bos_token_id""": 250_001,
             }							,    )






