'''simple docstring'''





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

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__snake_case			      =    logging.get_logger(__name__)

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

__snake_case			      =    {
    '''vocab_file''': {
        '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json''',
    },
    '''merges_file''': {'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt'''},
}

__snake_case			      =    {
    '''microsoft/biogpt''': 10_24,
}





def   lowerCAmelCase_ (				__lowerCAmelCase						)->  Dict:






      '''simple docstring'''





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







class 			__snake_case   (     __UpperCAmelCase   ):
 __lowerCamelCase    :   Dict     =      VOCAB_FILES_NAMES
 __lowerCamelCase    :   List[str]     =      PRETRAINED_VOCAB_FILES_MAP
 __lowerCamelCase    :   Optional[int]     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCamelCase    :   int     =      ["""input_ids""", """attention_mask"""]
 def __init__(  self		,   snake_case__		,   snake_case__		,   snake_case__="<unk>"		,   snake_case__="<s>"		,   snake_case__="</s>"		,   snake_case__="</s>"		,   snake_case__="<pad>"		,   **snake_case__		,   )	->							Optional[int]:
       '''simple docstring'''





       super().__init__(
           bos_token=lowercase_		,   eos_token=lowercase_		,   sep_token=lowercase_		,   unk_token=lowercase_		,   pad_token=lowercase_		,   **lowercase_		,   )

       try:
             import sacremoses
       except ImportError:
             raise ImportError(
                 '''You need to install sacremoses to use BioGptTokenizer. '''
                 '''See https://pypi.org/project/sacremoses/ for installation.'''						)

       UpperCAmelCase    : Optional[int]      ='''en'''
       UpperCAmelCase    : Optional[int]      =sacremoses
       # cache of sm.MosesTokenizer instance
       UpperCAmelCase    : Optional[int]      ={}
       UpperCAmelCase    : List[str]      ={}
       with open(lowercase_		,   encoding='''utf-8'''						) as vocab_handle:
             UpperCAmelCase    : List[Any]      =json.load(lowercase_						)
       UpperCAmelCase    : Dict      ={v: k for k, v in self.encoder.items()}
       with open(lowercase_		,   encoding='''utf-8'''						) as merges_handle:
             UpperCAmelCase    : Optional[int]      =merges_handle.read().split('''\n'''						)[:-1]
       UpperCAmelCase    : Optional[Any]      =[tuple(merge.split()[:2]						) for merge in merges]
       UpperCAmelCase    : List[str]      =dict(zip(lowercase_		,   range(len(lowercase_						)						)						)						)
       UpperCAmelCase    : Any      ={}
 @property
 def 	UpperCAmelCase__       (  self						)	->							List[Any]:
       '''simple docstring'''





       return len(self.encoder						)
 def 	UpperCAmelCase__       (  self						)	->							str:
       '''simple docstring'''





       return dict(self.encoder		,   **self.added_tokens_encoder						)
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__						)	->							Optional[int]:
       '''simple docstring'''





       if lang not in self.cache_moses_tokenizer:
             UpperCAmelCase    : Union[str, Any]      =self.sm.MosesTokenizer(lang=lowercase_						)
             UpperCAmelCase    : List[Any]      =moses_tokenizer
       return self.cache_moses_tokenizer[lang].tokenize(
           lowercase_		,   aggressive_dash_splits=lowercase_		,   return_str=lowercase_		,   escape=lowercase_						)
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__						)	->							List[Any]:
       '''simple docstring'''





       if lang not in self.cache_moses_detokenizer:
             UpperCAmelCase    : Dict      =self.sm.MosesDetokenizer(lang=lowercase_						)
             UpperCAmelCase    : List[Any]      =moses_detokenizer
       return self.cache_moses_detokenizer[lang].detokenize(lowercase_						)
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							List[str]:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      =tuple(token[:-1]						) + (token[-1] + '''</w>''',)
       if token in self.cache:
             return self.cache[token]
       UpperCAmelCase    : List[Any]      =get_pairs(lowercase_						)

       if not pairs:
             return token + "</w>"

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

                   if word[i] == first and i < len(lowercase_						) - 1 and word[i + 1] == second:
                         new_word.append(first + second						)
                         i += 2
                   else:
                         new_word.append(word[i]						)
                         i += 1
             UpperCAmelCase    : int      =tuple(lowercase_						)
             UpperCAmelCase    : List[str]      =new_word
             if len(lowercase_						) == 1:
                   break
             else:
                   UpperCAmelCase    : Optional[Any]      =get_pairs(lowercase_						)
       UpperCAmelCase    : int      =''' '''.join(lowercase_						)
       if word == "\n  </w>":
             UpperCAmelCase    : int      ='''\n</w>'''
       UpperCAmelCase    : Any      =word
       return word
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__=False						)	->							List[Any]:
       '''simple docstring'''





       if bypass_tokenizer:
             UpperCAmelCase    : Dict      =text.split()
       else:
             UpperCAmelCase    : Any      =self.moses_tokenize(lowercase_		,   self.lang						)

       UpperCAmelCase    : Any      =[]
       for token in text:
             if token:
                   split_tokens.extend(list(self.bpe(lowercase_						).split(''' '''						)						)						)

       return split_tokens
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							str:
       '''simple docstring'''





       return self.encoder.get(lowercase_		,   self.encoder.get(self.unk_token						)						)
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							Optional[int]:
       '''simple docstring'''





       return self.decoder.get(lowercase_		,   self.unk_token						)
 def 	UpperCAmelCase__       (  self		,   snake_case__						)	->							List[str]:
       '''simple docstring'''





       UpperCAmelCase    : Dict      =[t.replace(''' '''		,   ''''''						).replace('''</w>'''		,   ''' '''						) for t in tokens]
       UpperCAmelCase    : str      =''''''.join(lowercase_						).split()
       # detokenize
       UpperCAmelCase    : Union[str, Any]      =self.moses_detokenize(lowercase_		,   self.lang						)
       return text
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__ = None						)	->							List[int]:
       '''simple docstring'''





       if token_ids_a is None:
             return [self.sep_token_id] + token_ids_a
       UpperCAmelCase    : Any      =[self.sep_token_id]
       return sep + token_ids_a + sep + token_ids_a
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__ = None		,   snake_case__ = False						)	->							List[int]:
       '''simple docstring'''





       if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=lowercase_		,   token_ids_a=lowercase_		,   already_has_special_tokens=lowercase_						)
       # no bos used in fairseq
       if token_ids_a is not None:
             return [1] + ([0] * len(lowercase_						)) + [1] + ([0] * len(lowercase_						))
       return [1] + ([0] * len(lowercase_						))
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__ = None						)	->							List[int]:
       '''simple docstring'''





       UpperCAmelCase    : str      =[self.sep_token_id]

       # no bos used in fairseq
       if token_ids_a is None:
             return len(token_ids_a + sep						) * [0]
       return len(token_ids_a + sep						) * [0] + len(token_ids_a + sep						) * [1]
 def 	UpperCAmelCase__       (  self		,   snake_case__		,   snake_case__ = None						)	->							Tuple[str]:
       '''simple docstring'''





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

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

       UpperCAmelCase    : Optional[Any]      =0
       with open(lowercase_		,   '''w'''		,   encoding='''utf-8'''						) as writer:
             for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,   key=lambda snake_case__						: 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!'''						)
                         UpperCAmelCase    : List[str]      =token_index
                   writer.write(''' '''.join(lowercase_						) + '''\n'''						)
                   index += 1

       return vocab_file, merge_file
 def __getstate__(  self						)	->							List[str]:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      =self.__dict__.copy()
       UpperCAmelCase    : Any      =None
       return state






 def __setstate__(  self		,   snake_case__						)	->							List[str]:
       '''simple docstring'''





       UpperCAmelCase    : Optional[Any]      =d

       try:
             import sacremoses
       except ImportError:
             raise ImportError(
                 '''You need to install sacremoses to use XLMTokenizer. '''
                 '''See https://pypi.org/project/sacremoses/ for installation.'''						)

       UpperCAmelCase    : Optional[int]      =sacremoses

import json
import os
import tempfile
import unittest

from transformers.modelcard import ModelCard







class 			__snake_case   (     unittest.TestCase   ):
 def 	UpperCAmelCase__       (  self						)	->							Optional[Any]:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      ={
           '''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''': 76},
       }
 def 	UpperCAmelCase__       (  self						)	->							Dict:
       '''simple docstring'''





       UpperCAmelCase    : Optional[Any]      =ModelCard.from_dict(self.inputs_dict						)
       self.assertTrue(hasattr(snake_case__		,   '''model_details'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''intended_use'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''factors'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''metrics'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''evaluation_data'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''training_data'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''quantitative_analyses'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''ethical_considerations'''						)						)
       self.assertTrue(hasattr(snake_case__		,   '''caveats_and_recommendations'''						)						)
 def 	UpperCAmelCase__       (  self						)	->							Tuple:
       '''simple docstring'''





       UpperCAmelCase    : Optional[Any]      =ModelCard.from_dict(self.inputs_dict						)
       UpperCAmelCase    : int      =json.loads(modelcard.to_json_string()						)
       for key, value in self.inputs_dict.items():
             self.assertEqual(obj[key]		,   snake_case__						)
 def 	UpperCAmelCase__       (  self						)	->							Tuple:
       '''simple docstring'''





       UpperCAmelCase    : List[str]      =ModelCard.from_dict(self.inputs_dict						)

       with tempfile.TemporaryDirectory() as tmpdirname:
             UpperCAmelCase    : Optional[Any]      =os.path.join(snake_case__		,   '''modelcard.json'''						)
             model_card_first.to_json_file(snake_case__						)
             UpperCAmelCase    : Tuple      =ModelCard.from_json_file(snake_case__						)

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






 def 	UpperCAmelCase__       (  self						)	->							str:
       '''simple docstring'''





       UpperCAmelCase    : Optional[int]      =ModelCard.from_dict(self.inputs_dict						)

       with tempfile.TemporaryDirectory() as tmpdirname:
             model_card_first.save_pretrained(snake_case__						)
             UpperCAmelCase    : Dict      =ModelCard.from_pretrained(snake_case__						)

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