
'''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


a__		: Optional[int]  							=							logging.get_logger(__name__)


a__		: Optional[int]  							=							{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all MVP models at https://huggingface.co/models?filter=mvp
a__		: Union[str, Any]  							=							{
    "vocab_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json",
    },
    "added_tokens.json": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json",
    },
    "merges_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt",
    },
}

a__		: Dict  							=							{
    "RUCAIBox/mvp": 1_0_2_4,
}





@lru_cache()
def 							snake_case				(		)->      Optional[int]:







      """simple docstring"""
      __A													=      (
          list(range(ord('!'						)   ,	ord('~'						) + 1						)						) + list(range(ord('¡'						)   ,	ord('¬'						) + 1						)						) + list(range(ord('®'						)   ,	ord('ÿ'						) + 1						)						)
      )
      __A													=      bs[:]
      __A													=      0
      for b in range(2**8						):
            if b not in bs:
                  bs.append(UpperCAmelCase						)
                  cs.append(2**8 + n						)
                  n += 1
      __A													=      [chr(UpperCAmelCase						) for n in cs]
      return dict(zip(UpperCAmelCase   ,	UpperCAmelCase						)						)





def 							snake_case				(		UpperCAmelCase						)->      List[Any]:







      """simple docstring"""
      __A													=      set()
      __A													=      word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)						)
            __A													=      char
      return pairs


class 			UpperCamelCase__	(     SCREAMING_SNAKE_CASE):
 UpperCAmelCase__     :     Optional[Any]    					=       VOCAB_FILES_NAMES
 UpperCAmelCase__     :     Dict    					=       PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase__     :     str    					=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase__     :     str    					=       ['input_ids', 'attention_mask']






 def __init__(      self	:Optional[Any]						,					_A	:List[str]						,					_A	:Optional[Any]						,					_A	:Optional[int]="replace"						,					_A	:str="<s>"						,					_A	:Union[str, Any]="</s>"						,					_A	:str="</s>"						,					_A	:Optional[int]="<s>"						,					_A	:List[Any]="<unk>"						,					_A	:int="<pad>"						,					_A	:Any="<mask>"						,					_A	:Any=False						,					**_A	:int						,					)					->      List[Any]:







       '''simple docstring'''



       __A													=      AddedToken(_A						,					lstrip=_A						,					rstrip=_A      ) if isinstance(_A						,					_A      ) else bos_token
       __A													=      AddedToken(_A						,					lstrip=_A						,					rstrip=_A      ) if isinstance(_A						,					_A      ) else eos_token
       __A													=      AddedToken(_A						,					lstrip=_A						,					rstrip=_A      ) if isinstance(_A						,					_A      ) else sep_token
       __A													=      AddedToken(_A						,					lstrip=_A						,					rstrip=_A      ) if isinstance(_A						,					_A      ) else cls_token
       __A													=      AddedToken(_A						,					lstrip=_A						,					rstrip=_A      ) if isinstance(_A						,					_A      ) else unk_token
       __A													=      AddedToken(_A						,					lstrip=_A						,					rstrip=_A      ) if isinstance(_A						,					_A      ) else pad_token

       # Mask token behave like a normal word, i.e. include the space before it
       __A													=      AddedToken(_A						,					lstrip=_A						,					rstrip=_A      ) if isinstance(_A						,					_A      ) else mask_token

       super().__init__(
           errors=_A						,					bos_token=_A						,					eos_token=_A						,					unk_token=_A						,					sep_token=_A						,					cls_token=_A						,					pad_token=_A						,					mask_token=_A						,					add_prefix_space=_A						,					**_A						,					)
       with open(_A						,					encoding='utf-8'      ) as vocab_handle:
             __A													=      json.load(_A      )
       __A													=      {v: k for k, v in self.encoder.items()}
       __A													=      errors  # how to handle errors in decoding
       __A													=      bytes_to_unicode()
       __A													=      {v: k for k, v in self.byte_encoder.items()}
       with open(_A						,					encoding='utf-8'      ) as merges_handle:
             __A													=      merges_handle.read().split('\n'      )[1:-1]
       __A													=      [tuple(merge.split()      ) for merge in bpe_merges]
       __A													=      dict(zip(_A						,					range(len(_A      )      )      )      )
       __A													=      {}
       __A													=      add_prefix_space

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






 @property
 def 						lowercase_    (      self	:Union[str, Any]      )					->      int:







       '''simple docstring'''



       return len(self.encoder      )






 def 						lowercase_    (      self	:Optional[Any]      )					->      Tuple:







       '''simple docstring'''



       return dict(self.encoder						,					**self.added_tokens_encoder      )






 def 						lowercase_    (      self	:int						,					_A	:Optional[int]      )					->      Optional[int]:







       '''simple docstring'''



       if token in self.cache:
             return self.cache[token]
       __A													=      tuple(_A      )
       __A													=      get_pairs(_A      )

       if not pairs:
             return token

       while True:
             __A													=      min(_A						,					key=lambda _A      : self.bpe_ranks.get(_A						,					float('inf'      )      )      )
             if bigram not in self.bpe_ranks:
                   break
             __A						,   __A													=      bigram
             __A													=      []
             __A													=      0
             while i < len(_A      ):
                   try:
                         __A													=      word.index(_A						,					_A      )
                   except ValueError:
                         new_word.extend(word[i:]      )
                         break
                   else:
                         new_word.extend(word[i:j]      )
                         __A													=      j

                   if word[i] == first and i < len(_A      ) - 1 and word[i + 1] == second:
                         new_word.append(first + second      )
                         i += 2
                   else:
                         new_word.append(word[i]      )
                         i += 1
             __A													=      tuple(_A      )
             __A													=      new_word
             if len(_A      ) == 1:
                   break
             else:
                   __A													=      get_pairs(_A      )
       __A													=      ' '.join(_A      )
       __A													=      word
       return word






 def 						lowercase_    (      self	:List[str]						,					_A	:List[Any]      )					->      Union[str, Any]:







       '''simple docstring'''



       __A													=      []
       for token in re.findall(self.pat						,					_A      ):
             __A													=      ''.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(_A      ).split(' '      )      )
       return bpe_tokens






 def 						lowercase_    (      self	:Any						,					_A	:List[str]      )					->      List[Any]:







       '''simple docstring'''



       return self.encoder.get(_A						,					self.encoder.get(self.unk_token      )      )






 def 						lowercase_    (      self	:int						,					_A	:List[str]      )					->      Optional[int]:







       '''simple docstring'''



       return self.decoder.get(_A      )






 def 						lowercase_    (      self	:Any						,					_A	:Optional[int]      )					->      Optional[Any]:







       '''simple docstring'''



       __A													=      ''.join(_A      )
       __A													=      bytearray([self.byte_decoder[c] for c in text]      ).decode('utf-8'						,					errors=self.errors      )
       return text






 def 						lowercase_    (      self	:Optional[Any]						,					_A	:str						,					_A	:Optional[str] = None      )					->      Tuple[str]:







       '''simple docstring'''



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

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

       __A													=      0
       with open(_A						,					'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!'      )
                         __A													=      token_index
                   writer.write(' '.join(_A      ) + '\n'      )
                   index += 1

       return vocab_file, merge_file






 def 						lowercase_    (      self	:List[str]						,					_A	:List[int]						,					_A	:Optional[List[int]] = None      )					->      List[int]:







       '''simple docstring'''



       if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       __A													=      [self.cls_token_id]
       __A													=      [self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep






 def 						lowercase_    (      self	:Optional[int]						,					_A	:List[int]						,					_A	:Optional[List[int]] = None						,					_A	:bool = False      )					->      List[int]:







       '''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 						lowercase_    (      self	:Tuple						,					_A	:List[int]						,					_A	:Optional[List[int]] = None      )					->      List[int]:







       '''simple docstring'''



       __A													=      [self.sep_token_id]
       __A													=      [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 						lowercase_    (      self	:int						,					_A	:str						,					_A	:Union[str, Any]=False						,					**_A	:Dict      )					->      int:







       '''simple docstring'''



       __A													=      kwargs.pop('add_prefix_space'						,					self.add_prefix_space      )
       if (is_split_into_words or add_prefix_space) and (len(_A      ) > 0 and not text[0].isspace()):
             __A													=      ' ' + text
       return (text, kwargs)














import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard
class 	a_(		unittest.TestCase	):



     """simple docstring"""



     def     __UpperCamelCase						(		self					:	Optional[int])							->	List[str]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		{
          'model_details': {
              'Organization': 'testing',
              'Model date': 'today',
              'Model version': 'v2.1, Developed by Test Corp in 2019.',
              'Architecture': 'Convolutional Neural Network.',
          },
          'metrics': 'BLEU and ROUGE-1',
          'evaluation_data': {
              'Datasets': {'BLEU': 'My-great-dataset-v1', 'ROUGE-1': 'My-short-dataset-v2.1'},
              'Preprocessing': 'See details on https://arxiv.org/pdf/1810.03993.pdf',
          },
          'training_data': {
              'Dataset': 'English Wikipedia dump dated 2018-12-01',
              'Preprocessing': (
                  'Using SentencePiece vocabulary of size 52k tokens. See details on'
                  ' https://arxiv.org/pdf/1810.03993.pdf'
              ),
          },
          'quantitative_analyses': {'BLEU': 55.1, 'ROUGE-1': 7_6},
      }





     def     __UpperCamelCase						(		self					:	Optional[Any])							->	Any:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'model_details'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'intended_use'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'factors'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'metrics'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'evaluation_data'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'training_data'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'quantitative_analyses'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'ethical_considerations'))
      self.assertTrue(hasattr(lowerCAmelCase__  ,  'caveats_and_recommendations'))





     def     __UpperCamelCase						(		self					:	Any)							->	Any:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)
      SCREAMING_SNAKE_CASE				    =		json.loads(modelcard.to_json_string())
      for key, value in self.inputs_dict.items():
       self.assertEqual(obj[key]  ,  lowerCAmelCase__)





     def     __UpperCamelCase						(		self					:	int)							->	Optional[Any]:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)

      with tempfile.TemporaryDirectory() as tmpdirname:
       SCREAMING_SNAKE_CASE				    =		os.path.join(lowerCAmelCase__  ,  'modelcard.json')
       model_card_first.to_json_file(lowerCAmelCase__)
       SCREAMING_SNAKE_CASE				    =		ModelCard.from_json_file(lowerCAmelCase__)

      self.assertEqual(model_card_second.to_dict()  ,  model_card_first.to_dict())





     def     __UpperCamelCase						(		self					:	Optional[int])							->	Any:

      """simple docstring"""
      SCREAMING_SNAKE_CASE				    =		ModelCard.from_dict(self.inputs_dict)

      with tempfile.TemporaryDirectory() as tmpdirname:
       model_card_first.save_pretrained(lowerCAmelCase__)
       SCREAMING_SNAKE_CASE				    =		ModelCard.from_pretrained(lowerCAmelCase__)

      self.assertEqual(model_card_second.to_dict()  ,  model_card_first.to_dict())




