


'''simple docstring'''






import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


lowercase							=logging.get_logger(__name__)


lowercase							={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all MVP models at https://huggingface.co/models?filter=mvp
lowercase							={
    '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',
    },
    'tokenizer_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json',
    },
}

lowercase							={
    'RUCAIBox/mvp': 1024,
}






class  __magic_name__							(		a__    ):
       UpperCAmelCase										=VOCAB_FILES_NAMES
       UpperCAmelCase										=PRETRAINED_VOCAB_FILES_MAP
       UpperCAmelCase										=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCAmelCase										=["input_ids", "attention_mask"]
       UpperCAmelCase										=MvpTokenizer






       def __init__(      self  ,							snake_case=None  ,							snake_case=None  ,							snake_case=None  ,							snake_case="replace"  ,							snake_case="<s>"  ,							snake_case="</s>"  ,							snake_case="</s>"  ,							snake_case="<s>"  ,							snake_case="<unk>"  ,							snake_case="<pad>"  ,							snake_case="<mask>"  ,							snake_case=False  ,							snake_case=True  ,							**snake_case  ,							)						->  Optional[Any]:




          '''simple docstring'''
          super().__init__(
              snake_case  ,							snake_case  ,							tokenizer_file=snake_case  ,							errors=snake_case  ,							bos_token=snake_case  ,							eos_token=snake_case  ,							sep_token=snake_case  ,							cls_token=snake_case  ,							unk_token=snake_case  ,							pad_token=snake_case  ,							mask_token=snake_case  ,							add_prefix_space=snake_case  ,							trim_offsets=snake_case  ,							**snake_case  ,							)

          _UpperCAmelCase       :       str							   =json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
          if pre_tok_state.get('add_prefix_space'  ,							snake_case) != add_prefix_space:
             _UpperCAmelCase       :       List[str]							   =getattr(snake_case  ,							pre_tok_state.pop('type'))
             _UpperCAmelCase       :       Dict							   =add_prefix_space
             _UpperCAmelCase       :       str							   =pre_tok_class(**snake_case)

          _UpperCAmelCase       :       Union[str, Any]							   =add_prefix_space

          # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
          _UpperCAmelCase       :       int							   ="post_processor"
          _UpperCAmelCase       :       List[str]							   =getattr(self.backend_tokenizer  ,							snake_case  ,							snake_case)
          if tokenizer_component_instance:
             _UpperCAmelCase       :       Union[str, Any]							   =json.loads(tokenizer_component_instance.__getstate__())

             # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
             if "sep" in state:
                _UpperCAmelCase       :       List[str]							   =tuple(state['sep'])
             if "cls" in state:
                _UpperCAmelCase       :       Dict							   =tuple(state['cls'])

             _UpperCAmelCase       :       str							   =False

             if state.get('add_prefix_space'  ,							snake_case) != add_prefix_space:
                _UpperCAmelCase       :       List[str]							   =add_prefix_space
                _UpperCAmelCase       :       Optional[Any]							   =True

             if state.get('trim_offsets'  ,							snake_case) != trim_offsets:
                _UpperCAmelCase       :       Dict							   =trim_offsets
                _UpperCAmelCase       :       Tuple							   =True

             if changes_to_apply:
                _UpperCAmelCase       :       List[Any]							   =getattr(snake_case  ,							state.pop('type'))
                _UpperCAmelCase       :       Union[str, Any]							   =component_class(**snake_case)
                setattr(self.backend_tokenizer  ,							snake_case  ,							snake_case)






       @property
       def       lowerCAmelCase		(      self)						->  int:




          '''simple docstring'''
          if self._mask_token is None:
             if self.verbose:
                logger.error('Using mask_token, but it is not set yet.')
             return None
          return str(self._mask_token)






       @mask_token.setter
       def       lowerCAmelCase		(      self  ,							snake_case)						->  Optional[Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       Dict							   =AddedToken(snake_case  ,							lstrip=snake_case  ,							rstrip=snake_case) if isinstance(snake_case  ,							snake_case) else value
          _UpperCAmelCase       :       List[str]							   =value






       def       lowerCAmelCase		(      self  ,							*snake_case  ,							**snake_case)						->  Optional[int]:




          '''simple docstring'''
          _UpperCAmelCase       :       List[str]							   =kwargs.get('is_split_into_words'  ,							snake_case)

          if is_split_into_words and not self.add_prefix_space:
             raise ValueError(
                 f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
                 'to use it with pretokenized inputs.')

          return super()._batch_encode_plus(*snake_case  ,							**snake_case)






       def       lowerCAmelCase		(      self  ,							*snake_case  ,							**snake_case)						->  str:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[Any]							   =kwargs.get('is_split_into_words'  ,							snake_case)

          if is_split_into_words and not self.add_prefix_space:
             raise ValueError(
                 f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
                 'to use it with pretokenized inputs.')

          return super()._encode_plus(*snake_case  ,							**snake_case)






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  Tuple:




          '''simple docstring'''
          _UpperCAmelCase       :       Tuple							   =self._tokenizer.model.save(snake_case  ,							name=snake_case)
          return tuple(snake_case)






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case=None)						->  int:




          '''simple docstring'''
          _UpperCAmelCase       :       Dict							   =[self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
             return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






       def       lowerCAmelCase		(      self  ,							snake_case  ,							snake_case = None)						->  int:




          '''simple docstring'''
          _UpperCAmelCase       :       Union[str, Any]							   =[self.sep_token_id]
          _UpperCAmelCase       :       str							   =[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]






'''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.
import re

from ..utils import cached_file


# docstyle-ignore
lowercase							='\nHuman: <<task>>\n\nAssistant: '


lowercase							='huggingface-tools/default-prompts'
lowercase							={'chat': 'chat_prompt_template.txt', 'run': 'run_prompt_template.txt'}





def lowerCamelCase__      (						__lowerCamelCase	:							Union[str, Any]	,   __lowerCamelCase	:							Union[str, Any]	,   __lowerCamelCase	:							int="run"							):







   '''simple docstring'''




   if prompt_or_repo_id is None:
      _UpperCAmelCase       :       List[str]							   =DEFAULT_PROMPTS_REPO

   # prompt is considered a repo ID when it does not contain any kind of space
   if re.search('\\s'	,   __lowerCamelCase							) is not None:
      return prompt_or_repo_id

   _UpperCAmelCase       :       Dict							   =cached_file(
       __lowerCamelCase	,   PROMPT_FILES[mode]	,   repo_type='dataset'	,   user_agent={'agent': agent_name}							)
   with open(__lowerCamelCase	,   'r'	,   encoding='utf-8'							) as f:
      return f.read()

