






'''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


__UpperCamelCase   :							List[Any]         =   logging.get_logger(__name__)


__UpperCamelCase   :							List[str]         =   {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

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

__UpperCamelCase   :							int         =   {
    """RUCAIBox/mvp""": 1024,
}
class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):
      __a	       =VOCAB_FILES_NAMES
      __a	       =PRETRAINED_VOCAB_FILES_MAP
      __a	       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __a	       =["input_ids", "attention_mask"]
      __a	       =MvpTokenizer




      def __init__(	self			, lowerCamelCase=None			, lowerCamelCase=None			, lowerCamelCase=None			, lowerCamelCase="replace"			, lowerCamelCase="<s>"			, lowerCamelCase="</s>"			, lowerCamelCase="</s>"			, lowerCamelCase="<s>"			, lowerCamelCase="<unk>"			, lowerCamelCase="<pad>"			, lowerCamelCase="<mask>"			, lowerCamelCase=False			, lowerCamelCase=True			, **lowerCamelCase			, )				->Dict:



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

         __a					  =     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
         if pre_tok_state.get('add_prefix_space'			, lowerCamelCase   ) != add_prefix_space:
            __a					  =     getattr(lowerCamelCase			, pre_tok_state.pop('type'   )   )
            __a					  =     add_prefix_space
            __a					  =     pre_tok_class(**lowerCamelCase   )

         __a					  =     add_prefix_space

         # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
         __a					  =     'post_processor'
         __a					  =     getattr(self.backend_tokenizer			, lowerCamelCase			, lowerCamelCase   )
         if tokenizer_component_instance:
            __a					  =     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:
               __a					  =     tuple(state['sep']   )
            if "cls" in state:
               __a					  =     tuple(state['cls']   )

            __a					  =     False

            if state.get('add_prefix_space'			, lowerCamelCase   ) != add_prefix_space:
               __a					  =     add_prefix_space
               __a					  =     True

            if state.get('trim_offsets'			, lowerCamelCase   ) != trim_offsets:
               __a					  =     trim_offsets
               __a					  =     True

            if changes_to_apply:
               __a					  =     getattr(lowerCamelCase			, state.pop('type'   )   )
               __a					  =     component_class(**lowerCamelCase   )
               setattr(self.backend_tokenizer			, lowerCamelCase			, lowerCamelCase   )




      @property
      def 			__UpperCamelCase				(	self   )				->str:



         '''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 			__UpperCamelCase				(	self			, lowerCamelCase   )				->Dict:



         '''simple docstring'''
         __a					  =     AddedToken(lowerCamelCase			, lstrip=lowerCamelCase			, rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase			, lowerCamelCase   ) else value
         __a					  =     value




      def 			__UpperCamelCase				(	self			, *lowerCamelCase			, **lowerCamelCase   )				->BatchEncoding:



         '''simple docstring'''
         __a					  =     kwargs.get('is_split_into_words'			, lowerCamelCase   )

         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(*lowerCamelCase			, **lowerCamelCase   )




      def 			__UpperCamelCase				(	self			, *lowerCamelCase			, **lowerCamelCase   )				->BatchEncoding:



         '''simple docstring'''
         __a					  =     kwargs.get('is_split_into_words'			, lowerCamelCase   )

         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(*lowerCamelCase			, **lowerCamelCase   )




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase = None   )				->Tuple[str]:



         '''simple docstring'''
         __a					  =     self._tokenizer.model.save(lowerCamelCase			, name=lowerCamelCase   )
         return tuple(lowerCamelCase   )




      def 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase=None   )				->Dict:



         '''simple docstring'''
         __a					  =     [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 			__UpperCamelCase				(	self			, lowerCamelCase			, lowerCamelCase = 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]







'''simple docstring'''



from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
__UpperCamelCase   :							Optional[int]         =   Lock()



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						Tuple,       SCREAMING_SNAKE_CASE__:						Any,       SCREAMING_SNAKE_CASE__:						Tuple,       SCREAMING_SNAKE_CASE__:						str,       SCREAMING_SNAKE_CASE__:						Optional[Any],       SCREAMING_SNAKE_CASE__:						Any,       SCREAMING_SNAKE_CASE__:						List[Any]     )	->      int:

   """simple docstring"""
   global process_lock

   # we perform n swaps since after n swaps we know we are sorted
   # we *could* stop early if we are sorted already, but it takes as long to
   # find out we are sorted as it does to sort the list with this algorithm
   for i in range(0,       10     ):
      if (i + position) % 2 == 0 and r_send is not None:
         # send your value to your right neighbor
         process_lock.acquire()
         r_send[1].send(SCREAMING_SNAKE_CASE__     )
         process_lock.release()

         # receive your right neighbor's value
         process_lock.acquire()
         __a					  =     rr_cv[0].recv()
         process_lock.release()

         # take the lower value since you are on the left
         __a					  =     min(SCREAMING_SNAKE_CASE__,       SCREAMING_SNAKE_CASE__     )
      elif (i + position) % 2 != 0 and l_send is not None:
         # send your value to your left neighbor
         process_lock.acquire()
         l_send[1].send(SCREAMING_SNAKE_CASE__     )
         process_lock.release()

         # receive your left neighbor's value
         process_lock.acquire()
         __a					  =     lr_cv[0].recv()
         process_lock.release()

         # take the higher value since you are on the right
         __a					  =     max(SCREAMING_SNAKE_CASE__,       SCREAMING_SNAKE_CASE__     )
    # after all swaps are performed, send the values back to main
   result_pipe[1].send(SCREAMING_SNAKE_CASE__     )



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						Tuple     )	->      Optional[Any]:

   """simple docstring"""
   __a					  =     []
   __a					  =     []
   # initialize the list of pipes where the values will be retrieved
   for _ in arr:
      result_pipe.append(Pipe()     )
   # creates the processes
   # the first and last process only have one neighbor so they are made outside
   # of the loop
   __a					  =     Pipe()
   __a					  =     Pipe()
   process_array_.append(
       Process(
           target=SCREAMING_SNAKE_CASE__,       args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0]),       )     )
   __a					  =     temp_rs
   __a					  =     temp_rr

   for i in range(1,       len(SCREAMING_SNAKE_CASE__     ) - 1     ):
      __a					  =     Pipe()
      __a					  =     Pipe()
      process_array_.append(
          Process(
              target=SCREAMING_SNAKE_CASE__,       args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i]),       )     )
      __a					  =     temp_rs
      __a					  =     temp_rr

   process_array_.append(
       Process(
           target=SCREAMING_SNAKE_CASE__,       args=(
               len(SCREAMING_SNAKE_CASE__     ) - 1,
               arr[len(SCREAMING_SNAKE_CASE__     ) - 1],
               temp_ls,
               None,
               temp_lr,
               None,
               result_pipe[len(SCREAMING_SNAKE_CASE__     ) - 1],
           ),       )     )

   # start the processes
   for p in process_array_:
      p.start()

   # wait for the processes to end and write their values to the list
   for p in range(0,       len(SCREAMING_SNAKE_CASE__     )     ):
      __a					  =     result_pipe[p][0].recv()
      process_array_[p].join()
   return arr



def  __UpperCAmelCase						(					)	->      Any:

   """simple docstring"""
   __a					  =     list(range(10,       0,       -1     )     )
   print('Initial List'     )
   print(*SCREAMING_SNAKE_CASE__     )
   __a					  =     odd_even_transposition(SCREAMING_SNAKE_CASE__     )
   print('Sorted List\n'     )
   print(*SCREAMING_SNAKE_CASE__     )


if __name__ == "__main__":
 main()