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

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


lowercase_											=	logging.get_logger(__name__)

lowercase_											=	{
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
}

lowercase_											=	{
    """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"""},
}

lowercase_											=	{
    """microsoft/biogpt""": 1_024,
}


def     a__			(    snake_case    ):





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





class   __UpperCamelCase				(    lowerCAmelCase__   ):






     """simple docstring"""







     lowerCAmelCase_     =	VOCAB_FILES_NAMES
     lowerCAmelCase_     =	PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase_     =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase_     =	['''input_ids''', '''attention_mask''']



     def __init__(							self    :    List[str]      ,		_A    :    Tuple      ,		_A    :    int      ,		_A    :    List[Any]="<unk>"      ,		_A    :    List[Any]="<s>"      ,		_A    :    Optional[Any]="</s>"      ,		_A    :    Dict="</s>"      ,		_A    :    Optional[int]="<pad>"      ,		**_A    :    Optional[Any]      ,		):







       """simple docstring"""




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

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

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



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







       """simple docstring"""




       return len(self.encoder				)



     def 				UpperCAmelCase__    (							self    :    int				):







       """simple docstring"""




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



     def 				UpperCAmelCase__    (							self    :    Any      ,		_A    :    str      ,		_A    :    Dict				):







       """simple docstring"""




       if lang not in self.cache_moses_tokenizer:
         __SCREAMING_SNAKE_CASE     :					Dict			=						self.sm.MosesTokenizer(lang=_A				)
         __SCREAMING_SNAKE_CASE     :					Optional[int]			=						moses_tokenizer
       return self.cache_moses_tokenizer[lang].tokenize(
           _A      ,		aggressive_dash_splits=_A      ,		return_str=_A      ,		escape=_A				)



     def 				UpperCAmelCase__    (							self    :    List[str]      ,		_A    :    Optional[Any]      ,		_A    :    Tuple				):







       """simple docstring"""




       if lang not in self.cache_moses_detokenizer:
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						self.sm.MosesDetokenizer(lang=_A				)
         __SCREAMING_SNAKE_CASE     :					List[Any]			=						moses_detokenizer
       return self.cache_moses_detokenizer[lang].detokenize(_A				)



     def 				UpperCAmelCase__    (							self    :    int      ,		_A    :    List[Any]				):







       """simple docstring"""




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

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

       while True:
         __SCREAMING_SNAKE_CASE     :					str			=						min(_A      ,		key=lambda _A				: self.bpe_ranks.get(_A      ,		float('''inf'''				)				)				)
         if bigram not in self.bpe_ranks:
           break
         __SCREAMING_SNAKE_CASE     :					List[Any]			=						bigram
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						[]
         __SCREAMING_SNAKE_CASE     :					str			=						0
         while i < len(_A				):
           try:
             __SCREAMING_SNAKE_CASE     :					List[str]			=						word.index(_A      ,		_A				)
           except ValueError:
             new_word.extend(word[i:]				)
             break
           else:
             new_word.extend(word[i:j]				)
             __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						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
         __SCREAMING_SNAKE_CASE     :					Any			=						tuple(_A				)
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						new_word
         if len(_A				) == 1:
           break
         else:
           __SCREAMING_SNAKE_CASE     :					Dict			=						get_pairs(_A				)
       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						''' '''.join(_A				)
       if word == "\n  </w>":
         __SCREAMING_SNAKE_CASE     :					Any			=						'''\n</w>'''
       __SCREAMING_SNAKE_CASE     :					str			=						word
       return word



     def 				UpperCAmelCase__    (							self    :    int      ,		_A    :    Union[str, Any]      ,		_A    :    Dict=False				):







       """simple docstring"""




       if bypass_tokenizer:
         __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						text.split()
       else:
         __SCREAMING_SNAKE_CASE     :					Any			=						self.moses_tokenize(_A      ,		self.lang				)

       __SCREAMING_SNAKE_CASE     :					str			=						[]
       for token in text:
         if token:
           split_tokens.extend(list(self.bpe(_A				).split(''' '''				)				)				)

       return split_tokens



     def 				UpperCAmelCase__    (							self    :    List[Any]      ,		_A    :    Optional[Any]				):







       """simple docstring"""




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



     def 				UpperCAmelCase__    (							self    :    Dict      ,		_A    :    str				):







       """simple docstring"""




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



     def 				UpperCAmelCase__    (							self    :    Optional[Any]      ,		_A    :    Any				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					str			=						[t.replace(''' '''      ,		''''''				).replace('''</w>'''      ,		''' '''				) for t in tokens]
       __SCREAMING_SNAKE_CASE     :					str			=						''''''.join(_A				).split()
       # detokenize
       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						self.moses_detokenize(_A      ,		self.lang				)
       return text



     def 				UpperCAmelCase__    (							self    :    int      ,		_A    :    List[int]      ,		_A    :    Optional[List[int]] = None				):







       """simple docstring"""




       if token_ids_a is None:
         return [self.sep_token_id] + token_ids_a
       __SCREAMING_SNAKE_CASE     :					Tuple			=						[self.sep_token_id]
       return sep + token_ids_a + sep + token_ids_a



     def 				UpperCAmelCase__    (							self    :    List[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				)
       # no bos used in fairseq
       if token_ids_a is not None:
         return [1] + ([0] * len(_A				)) + [1] + ([0] * len(_A				))
       return [1] + ([0] * len(_A				))



     def 				UpperCAmelCase__    (							self    :    Tuple      ,		_A    :    List[int]      ,		_A    :    Optional[List[int]] = None				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						[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    :    Union[str, 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
       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						os.path.join(
           _A      ,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)
       __SCREAMING_SNAKE_CASE     :					List[str]			=						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'''				)

       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						0
       with open(_A      ,		'''w'''      ,		encoding='''utf-8'''				) as writer:
         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!'''				)
             __SCREAMING_SNAKE_CASE     :					str			=						token_index
           writer.write(''' '''.join(_A				) + '''\n'''				)
           index += 1

       return vocab_file, merge_file



     def __getstate__(							self    :    str				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						self.__dict__.copy()
       __SCREAMING_SNAKE_CASE     :					Dict			=						None
       return state




     def __setstate__(							self    :    Tuple      ,		_A    :    int				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					str			=						d

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

       __SCREAMING_SNAKE_CASE     :					Optional[int]			=						sacremoses


import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


lowercase_											=	"""
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
"""





class   __UpperCamelCase				(    unittest.TestCase				,		lowerCAmelCase__   ):






     """simple docstring"""







     def 				UpperCAmelCase__    (							self    :    Optional[Any]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					int			=						load_tool('''summarization'''				)
       self.tool.setup()
       __SCREAMING_SNAKE_CASE     :					Any			=						load_tool('''summarization'''      ,		remote=_A				)



     def 				UpperCAmelCase__    (							self    :    Tuple				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Dict			=						self.tool(_A				)
       self.assertEqual(
           _A      ,		'''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''      ,		)



     def 				UpperCAmelCase__    (							self    :    List[str]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						self.remote_tool(_A				)
       self.assertEqual(
           _A      ,		'''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''      ,		)



     def 				UpperCAmelCase__    (							self    :    List[str]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					Dict			=						self.tool(text=_A				)
       self.assertEqual(
           _A      ,		'''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''      ,		)




     def 				UpperCAmelCase__    (							self    :    Optional[int]				):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE     :					str			=						self.remote_tool(text=_A				)
       self.assertEqual(
           _A      ,		'''Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf. In March 2021, Hugging Face raised $40 million in a Series B funding round. On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model. In 2022, the workshop concluded with the announcement of BLOOM.'''      ,		)
