



'''simple docstring'''





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

import regex as re

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


_lowerCAmelCase      						=	logging.get_logger(__name__)


_lowerCAmelCase      						=	{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

# See all BART models at https://huggingface.co/models?filter=bart
_lowerCAmelCase      						=	{
    '''vocab_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/vocab.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/vocab.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/merges.txt''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/merges.txt''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt''',
    },
}

_lowerCAmelCase      						=	{
    '''facebook/bart-base''': 1024,
    '''facebook/bart-large''': 1024,
    '''facebook/bart-large-mnli''': 1024,
    '''facebook/bart-large-cnn''': 1024,
    '''facebook/bart-large-xsum''': 1024,
    '''yjernite/bart_eli5''': 1024,
}
@lru_cache()
def    _SCREAMING_SNAKE_CASE  (       ):



    """simple docstring"""





    lowerCAmelCase__ :  Union[str, Any]							      =					(
        list(range(ord("""!"""			)							,    ord("""~"""			) + 1			)			) + list(range(ord("""¡"""			)							,    ord("""¬"""			) + 1			)			) + list(range(ord("""®"""			)							,    ord("""ÿ"""			) + 1			)			)
    )
    lowerCAmelCase__ :  Union[str, Any]							      =					bs[:]
    lowerCAmelCase__ :  int							      =					0
    for b in range(2**8			):
        if b not in bs:
            bs.append(UpperCamelCase			)
            cs.append(2**8 + n			)
            n += 1
    lowerCAmelCase__ :  Any							      =					[chr(UpperCamelCase			) for n in cs]
    return dict(zip(UpperCamelCase							,    UpperCamelCase			)			)
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase			):



    """simple docstring"""





    lowerCAmelCase__ :  Union[str, Any]							      =					set()
    lowerCAmelCase__ :  List[Any]							      =					word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)			)
        lowerCAmelCase__ :  Optional[int]							      =					char
    return pairs






class        lowerCAmelCase_(				SCREAMING_SNAKE_CASE_     ):
  '''simple docstring'''




  __lowercase							:      Any				=      VOCAB_FILES_NAMES
  __lowercase							:      Dict				=      PRETRAINED_VOCAB_FILES_MAP
  __lowercase							:      Optional[Any]				=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __lowercase							:      Any				=      ['''input_ids''', '''attention_mask''']




  def __init__(    self  ,__UpperCAmelCase  ,__UpperCAmelCase  ,__UpperCAmelCase="replace"  ,__UpperCAmelCase="<s>"  ,__UpperCAmelCase="</s>"  ,__UpperCAmelCase="</s>"  ,__UpperCAmelCase="<s>"  ,__UpperCAmelCase="<unk>"  ,__UpperCAmelCase="<pad>"  ,__UpperCAmelCase="<mask>"  ,__UpperCAmelCase=False  ,**__UpperCAmelCase  ,)    ->		List[str]:
      lowerCAmelCase__ :  Optional[Any]							      =					AddedToken(__UpperCAmelCase  ,lstrip=__UpperCAmelCase  ,rstrip=__UpperCAmelCase      ) if isinstance(__UpperCAmelCase  ,__UpperCAmelCase      ) else bos_token
      lowerCAmelCase__ :  Any							      =					AddedToken(__UpperCAmelCase  ,lstrip=__UpperCAmelCase  ,rstrip=__UpperCAmelCase      ) if isinstance(__UpperCAmelCase  ,__UpperCAmelCase      ) else eos_token
      lowerCAmelCase__ :  Optional[Any]							      =					AddedToken(__UpperCAmelCase  ,lstrip=__UpperCAmelCase  ,rstrip=__UpperCAmelCase      ) if isinstance(__UpperCAmelCase  ,__UpperCAmelCase      ) else sep_token
      lowerCAmelCase__ :  List[str]							      =					AddedToken(__UpperCAmelCase  ,lstrip=__UpperCAmelCase  ,rstrip=__UpperCAmelCase      ) if isinstance(__UpperCAmelCase  ,__UpperCAmelCase      ) else cls_token
      lowerCAmelCase__ :  List[Any]							      =					AddedToken(__UpperCAmelCase  ,lstrip=__UpperCAmelCase  ,rstrip=__UpperCAmelCase      ) if isinstance(__UpperCAmelCase  ,__UpperCAmelCase      ) else unk_token
      lowerCAmelCase__ :  List[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
      lowerCAmelCase__ :  Union[str, 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:
          lowerCAmelCase__ :  int							      =					json.load(__UpperCAmelCase      )
      lowerCAmelCase__ :  Optional[Any]							      =					{v: k for k, v in self.encoder.items()}
      lowerCAmelCase__ :  List[str]							      =					errors  # how to handle errors in decoding
      lowerCAmelCase__ :  Optional[int]							      =					bytes_to_unicode()
      lowerCAmelCase__ :  List[Any]							      =					{v: k for k, v in self.byte_encoder.items()}
      with open(__UpperCAmelCase  ,encoding="""utf-8"""      ) as merges_handle:
          lowerCAmelCase__ :  List[str]							      =					merges_handle.read().split("""\n"""      )[1:-1]
      lowerCAmelCase__ :  Dict							      =					[tuple(merge.split()      ) for merge in bpe_merges]
      lowerCAmelCase__ :  Union[str, Any]							      =					dict(zip(__UpperCAmelCase  ,range(len(__UpperCAmelCase      )      )      )      )
      lowerCAmelCase__ :  List[Any]							      =					{}
      lowerCAmelCase__ :  Optional[Any]							      =					add_prefix_space

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




  @property
  def 							UpperCAmelCase_	(    self      )    ->		str:
      return len(self.encoder      )




  def 							UpperCAmelCase_	(    self      )    ->		Tuple:
      return dict(self.encoder  ,**self.added_tokens_encoder      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		Optional[int]:
      if token in self.cache:
          return self.cache[token]
      lowerCAmelCase__ :  Tuple							      =					tuple(__UpperCAmelCase      )
      lowerCAmelCase__ :  List[Any]							      =					get_pairs(__UpperCAmelCase      )

      if not pairs:
          return token

      while True:
          lowerCAmelCase__ :  Any							      =					min(__UpperCAmelCase  ,key=lambda __UpperCAmelCase      : self.bpe_ranks.get(__UpperCAmelCase  ,float("""inf"""      )      )      )
          if bigram not in self.bpe_ranks:
              break
          lowerCAmelCase__      ,   lowerCAmelCase__ :  int							      =					bigram
          lowerCAmelCase__ :  Optional[int]							      =					[]
          lowerCAmelCase__ :  List[Any]							      =					0
          while i < len(__UpperCAmelCase      ):
              try:
                  lowerCAmelCase__ :  Union[str, Any]							      =					word.index(__UpperCAmelCase  ,__UpperCAmelCase      )
              except ValueError:
                  new_word.extend(word[i:]      )
                  break
              else:
                  new_word.extend(word[i:j]      )
                  lowerCAmelCase__ :  Any							      =					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
          lowerCAmelCase__ :  Tuple							      =					tuple(__UpperCAmelCase      )
          lowerCAmelCase__ :  List[Any]							      =					new_word
          if len(__UpperCAmelCase      ) == 1:
              break
          else:
              lowerCAmelCase__ :  Any							      =					get_pairs(__UpperCAmelCase      )
      lowerCAmelCase__ :  Union[str, Any]							      =					""" """.join(__UpperCAmelCase      )
      lowerCAmelCase__ :  int							      =					word
      return word




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		Optional[Any]:
      lowerCAmelCase__ :  int							      =					[]
      for token in re.findall(self.pat  ,__UpperCAmelCase      ):
          lowerCAmelCase__ :  Union[str, 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  ,__UpperCAmelCase      )    ->		Dict:
      return self.encoder.get(__UpperCAmelCase  ,self.encoder.get(self.unk_token      )      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		str:
      return self.decoder.get(__UpperCAmelCase      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		Dict:
      lowerCAmelCase__ :  List[Any]							      =					"""""".join(__UpperCAmelCase      )
      lowerCAmelCase__ :  Tuple							      =					bytearray([self.byte_decoder[c] for c in text]      ).decode("""utf-8"""  ,errors=self.errors      )
      return text




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		Tuple[str]:
      if not os.path.isdir(__UpperCAmelCase      ):
          logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
          return
      lowerCAmelCase__ :  int							      =					os.path.join(
          __UpperCAmelCase  ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )
      lowerCAmelCase__ :  Union[str, Any]							      =					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"""      )

      lowerCAmelCase__ :  Tuple							      =					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 __UpperCAmelCase      : 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!"""      )
                  lowerCAmelCase__ :  List[str]							      =					token_index
              writer.write(""" """.join(__UpperCAmelCase      ) + """\n"""      )
              index += 1

      return vocab_file, merge_file




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		List[int]:
      if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      lowerCAmelCase__ :  List[str]							      =					[self.cls_token_id]
      lowerCAmelCase__ :  Tuple							      =					[self.sep_token_id]
      return cls + token_ids_a + sep + sep + token_ids_a + sep




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None  ,__UpperCAmelCase = False      )    ->		List[int]:
      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  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		List[int]:
      lowerCAmelCase__ :  Tuple							      =					[self.sep_token_id]
      lowerCAmelCase__ :  Tuple							      =					[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  ,__UpperCAmelCase  ,__UpperCAmelCase=False  ,**__UpperCAmelCase      )    ->		Any:
      lowerCAmelCase__ :  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()):
          lowerCAmelCase__ :  Union[str, Any]							      =					""" """ + text
      return (text, kwargs)







'''simple docstring'''





import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow


if is_torch_available():
 import torch

 from transformers import XLMRobertaModel






@require_sentencepiece
@require_tokenizers
@require_torch
class        lowerCAmelCase_(				unittest.TestCase     ):
  '''simple docstring'''




  @slow
  def 							UpperCAmelCase_	(    self      )    ->		Union[str, Any]:
      lowerCAmelCase__ :  Tuple							      =					XLMRobertaModel.from_pretrained("""xlm-roberta-base"""      )
      lowerCAmelCase__ :  Optional[int]							      =					torch.tensor([[0, 581, 1_0269, 83, 9_9942, 136, 6_0742, 23, 70, 8_0583, 1_8276, 2]]      )
      # The dog is cute and lives in the garden house

      lowerCAmelCase__ :  str							      =					torch.Size((1, 12, 768)      )  # batch_size, sequence_length, embedding_vector_dim
      lowerCAmelCase__ :  Dict							      =					torch.tensor(
          [[-0.0_1_0_1, 0.1_2_1_8, -0.0_8_0_3, 0.0_8_0_1, 0.1_3_2_7, 0.0_7_7_6, -0.1_2_1_5, 0.2_3_8_3, 0.3_3_3_8, 0.3_1_0_6, 0.0_3_0_0, 0.0_2_5_2]]      )
      #  xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')
      #  xlmr.eval()
      #  expected_output_values_last_dim = xlmr.extract_features(input_ids[0])[:, :, -1]
      with torch.no_grad():
          lowerCAmelCase__ :  Optional[int]							      =					model(__UpperCAmelCase      )["""last_hidden_state"""].detach()
      self.assertEqual(output.shape  ,__UpperCAmelCase      )
      # compare the actual values for a slice of last dim
      self.assertTrue(torch.allclose(output[:, :, -1]  ,__UpperCAmelCase  ,atol=1E-3      )      )






  @slow
  def 							UpperCAmelCase_	(    self      )    ->		int:
      lowerCAmelCase__ :  Union[str, Any]							      =					XLMRobertaModel.from_pretrained("""xlm-roberta-large"""      )
      lowerCAmelCase__ :  Optional[Any]							      =					torch.tensor([[0, 581, 1_0269, 83, 9_9942, 136, 6_0742, 23, 70, 8_0583, 1_8276, 2]]      )
      # The dog is cute and lives in the garden house

      lowerCAmelCase__ :  Dict							      =					torch.Size((1, 12, 1024)      )  # batch_size, sequence_length, embedding_vector_dim
      lowerCAmelCase__ :  Union[str, Any]							      =					torch.tensor(
          [[-0.0_6_9_9, -0.0_3_1_8, 0.0_7_0_5, -0.1_2_4_1, 0.0_9_9_9, -0.0_5_2_0, 0.1_0_0_4, -0.1_8_3_8, -0.4_7_0_4, 0.1_4_3_7, 0.0_8_2_1, 0.0_1_2_6]]      )
      #  xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.large')
      #  xlmr.eval()
      #  expected_output_values_last_dim = xlmr.extract_features(input_ids[0])[:, :, -1]
      with torch.no_grad():
          lowerCAmelCase__ :  Union[str, Any]							      =					model(__UpperCAmelCase      )["""last_hidden_state"""].detach()
      self.assertEqual(output.shape  ,__UpperCAmelCase      )
      # compare the actual values for a slice of last dim
      self.assertTrue(torch.allclose(output[:, :, -1]  ,__UpperCAmelCase  ,atol=1E-3      )      )


