






"""simple docstring"""
import json
import os
from typing import List, Optional, Tuple

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


A_     :					Tuple							=     logging.get_logger(__name__)

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

A_     :					Optional[Any]							=     {
    "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"},
}

A_     :					Any							=     {
    "microsoft/biogpt": 10_24,
}






def 			lowerCamelCase_    (		_lowerCamelCase							):
 lowerCamelCase__	:     Dict								=		set()
 lowerCamelCase__	:     Any								=		word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)							)
  lowerCamelCase__	:     Any								=		char
 return pairs





class 						a_ (      snake_case_					):







      '''simple docstring'''

      lowerCamelCase__			:							str					=      VOCAB_FILES_NAMES
      lowerCamelCase__			:							Optional[int]					=      PRETRAINED_VOCAB_FILES_MAP
      lowerCamelCase__			:							Union[str, Any]					=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCamelCase__			:							Union[str, Any]					=      ["""input_ids""", """attention_mask"""]




      def __init__(self,	lowerCamelCase_,	lowerCamelCase_,	lowerCamelCase_="<unk>",	lowerCamelCase_="<s>",	lowerCamelCase_="</s>",	lowerCamelCase_="</s>",	lowerCamelCase_="<pad>",	**lowerCamelCase_,	):

       '''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.'   )

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




      @property
      def      a__				(self   ):

       '''simple docstring'''



       return len(self.encoder   )




      def      a__				(self   ):

       '''simple docstring'''



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




      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_   ):

       '''simple docstring'''



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




      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_   ):

       '''simple docstring'''



       if lang not in self.cache_moses_detokenizer:
        lowerCamelCase__	:     Union[str, Any]								=		self.sm.MosesDetokenizer(lang=_A   )
        lowerCamelCase__	:     int								=		moses_detokenizer
       return self.cache_moses_detokenizer[lang].detokenize(_A   )




      def      a__				(self,	lowerCamelCase_   ):

       '''simple docstring'''



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

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

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




      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_=False   ):

       '''simple docstring'''



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

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

       return split_tokens




      def      a__				(self,	lowerCamelCase_   ):

       '''simple docstring'''



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




      def      a__				(self,	lowerCamelCase_   ):

       '''simple docstring'''



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




      def      a__				(self,	lowerCamelCase_   ):

       '''simple docstring'''



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




      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_ = None   ):

       '''simple docstring'''



       if token_ids_a is None:
        return [self.sep_token_id] + token_ids_a
       lowerCamelCase__	:     List[Any]								=		[self.sep_token_id]
       return sep + token_ids_a + sep + token_ids_a




      def      a__				(self,	lowerCamelCase_,	lowerCamelCase_ = None,	lowerCamelCase_ = 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      a__				(self,	lowerCamelCase_,	lowerCamelCase_ = None   ):

       '''simple docstring'''



       lowerCamelCase__	:     List[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      a__				(self,	lowerCamelCase_,	lowerCamelCase_ = None   ):

       '''simple docstring'''



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

       lowerCamelCase__	:     Optional[int]								=		0
       with open(_A,	'w',	encoding='utf-8'   ) as writer:
        for bpe_tokens, token_index in sorted(self.bpe_ranks.items(),	key=lambda lowerCamelCase_   : 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__	:     Tuple								=		token_index
         writer.write(' '.join(_A   ) + '\n'   )
         index += 1

       return vocab_file, merge_file




      def __getstate__(self   ):

       '''simple docstring'''



       lowerCamelCase__	:     List[str]								=		self.__dict__.copy()
       lowerCamelCase__	:     Optional[int]								=		None
       return state





      def __setstate__(self,	lowerCamelCase_   ):

       '''simple docstring'''



       lowerCamelCase__	:     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.'   )

       lowerCamelCase__	:     Optional[int]								=		sacremoses


"""simple docstring"""







# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


_a	:	Union[str, Any]=					"Here is a text containing a lot of information: '''{text}'''.\n\nCan you answer this question about the text: '{question}'"

class 						UpperCamelCase     (       lowercase		):
				UpperCAmelCase							: str       =						"""google/flan-t5-base"""
				UpperCAmelCase							: int       =						(
				    """This is a tool that answers questions related to a text. It takes two arguments named `text`, which is the """
				    """text where to find the answer, and `question`, which is the question, and returns the answer to the question."""
				)
				UpperCAmelCase							: Dict       =						"""text_qa"""
				UpperCAmelCase							: Dict       =						AutoTokenizer
				UpperCAmelCase							: Optional[Any]       =						AutoModelForSeqaSeqLM

				UpperCAmelCase							: List[str]       =						["""text""", """text"""]
				UpperCAmelCase							: Any       =						["""text"""]



				def    _lowercase	(self							: Tuple      ,    _A							: str      ,    _A							: str)       ->      Tuple:
					__snake_case     :				List[Any] 						=					QA_PROMPT.format(text=_A      ,    question=_A)
					return self.pre_processor(_A      ,    return_tensors='pt')



				def    _lowercase	(self							: Tuple      ,    _A							: Optional[Any])       ->      List[Any]:
					__snake_case     :				List[Any] 						=					self.model.generate(**_A)

					__snake_case						,							__snake_case     :				Any 						=					inputs['input_ids'].shape
					__snake_case     :				Any 						=					output_ids.shape[0]

					return output_ids.reshape(_A      ,    out_b // in_b      ,    *output_ids.shape[1:])[0][0]






				def    _lowercase	(self							: Optional[int]      ,    _A							: int)       ->      str:
					return self.pre_processor.decode(_A      ,    skip_special_tokens=_A      ,    clean_up_tokenization_spaces=_A)





