"""simple docstring"""






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__lowerCAmelCase					: Union[str, Any]        =logging.get_logger(__name__)

__lowerCAmelCase					: Any        ="""▁"""

__lowerCAmelCase					: Union[str, Any]        ={"""vocab_file""": """sentencepiece.bpe.model"""}

__lowerCAmelCase					: Tuple        ={
    """vocab_file""": {
        """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large-finetuned-conll02-dutch""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll02-spanish""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-english""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-german""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

__lowerCAmelCase					: Any        ={
    """xlm-roberta-base""": 5_1_2,
    """xlm-roberta-large""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-dutch""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-spanish""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-english""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-german""": 5_1_2,
}





class 				_A		( lowerCAmelCase			):
      snake_case__    :     int													=			VOCAB_FILES_NAMES
      snake_case__    :     List[Any]													=			PRETRAINED_VOCAB_FILES_MAP
      snake_case__    :     str													=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      snake_case__    :     Union[str, Any]													=			['input_ids', 'attention_mask']

      def __init__(		self	, __lowerCAmelCase	, __lowerCAmelCase="<s>"	, __lowerCAmelCase="</s>"	, __lowerCAmelCase="</s>"	, __lowerCAmelCase="<s>"	, __lowerCAmelCase="<unk>"	, __lowerCAmelCase="<pad>"	, __lowerCAmelCase="<mask>"	, __lowerCAmelCase = None	, **__lowerCAmelCase	, ):







            """simple docstring"""



            lowercase														=			AddedToken(__lowerCAmelCase	, lstrip=__lowerCAmelCase	, rstrip=__lowerCAmelCase		) if isinstance(__lowerCAmelCase	, __lowerCAmelCase		) else mask_token

            lowercase														=			{} if sp_model_kwargs is None else sp_model_kwargs

            super().__init__(
                bos_token=__lowerCAmelCase	, eos_token=__lowerCAmelCase	, unk_token=__lowerCAmelCase	, sep_token=__lowerCAmelCase	, cls_token=__lowerCAmelCase	, pad_token=__lowerCAmelCase	, mask_token=__lowerCAmelCase	, sp_model_kwargs=self.sp_model_kwargs	, **__lowerCAmelCase	, )

            lowercase														=			spm.SentencePieceProcessor(**self.sp_model_kwargs		)
            self.sp_model.Load(str(__lowerCAmelCase		)		)
            lowercase														=			vocab_file

            # Original fairseq vocab and spm vocab must be "aligned":
            # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
            # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
            # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
            # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

            # Mimic fairseq token-to-id alignment for the first 4 token
            lowercase														=			{"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

            # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
            lowercase														=			1

            lowercase														=			len(self.sp_model		) + self.fairseq_offset
            lowercase														=			{v: k for k, v in self.fairseq_tokens_to_ids.items()}

      def __getstate__(		self		):







            """simple docstring"""



            lowercase														=			self.__dict__.copy()
            lowercase														=			None
            lowercase														=			self.sp_model.serialized_model_proto()
            return state

      def __setstate__(		self	, __lowerCAmelCase		):







            """simple docstring"""



            lowercase														=			d

            # for backward compatibility
            if not hasattr(self	, """sp_model_kwargs"""		):
                  lowercase														=			{}

            lowercase														=			spm.SentencePieceProcessor(**self.sp_model_kwargs		)
            self.sp_model.LoadFromSerializedProto(self.sp_model_proto		)

      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = None		):







            """simple docstring"""



            if token_ids_a is None:
                  return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
            lowercase														=			[self.cls_token_id]
            lowercase														=			[self.sep_token_id]
            return cls + token_ids_a + sep + sep + token_ids_a + sep

      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = None	, __lowerCAmelCase = False		):







            """simple docstring"""



            if already_has_special_tokens:
                  return super().get_special_tokens_mask(
                      token_ids_a=__lowerCAmelCase	, token_ids_a=__lowerCAmelCase	, already_has_special_tokens=__lowerCAmelCase		)

            if token_ids_a is None:
                  return [1] + ([0] * len(__lowerCAmelCase		)) + [1]
            return [1] + ([0] * len(__lowerCAmelCase		)) + [1, 1] + ([0] * len(__lowerCAmelCase		)) + [1]

      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = None		):







            """simple docstring"""



            lowercase														=			[self.sep_token_id]
            lowercase														=			[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]

      @property
      def        A__ (		self		):







            """simple docstring"""



            return len(self.sp_model		) + self.fairseq_offset + 1  # Add the <mask> token

      def        A__ (		self		):







            """simple docstring"""



            lowercase														=			{self.convert_ids_to_tokens(__lowerCAmelCase		): i for i in range(self.vocab_size		)}
            vocab.update(self.added_tokens_encoder		)
            return vocab

      def        A__ (		self	, __lowerCAmelCase		):







            """simple docstring"""



            return self.sp_model.encode(__lowerCAmelCase	, out_type=__lowerCAmelCase		)

      def        A__ (		self	, __lowerCAmelCase		):







            """simple docstring"""



            if token in self.fairseq_tokens_to_ids:
                  return self.fairseq_tokens_to_ids[token]
            lowercase														=			self.sp_model.PieceToId(__lowerCAmelCase		)

            # Need to return unknown token if the SP model returned 0
            return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

      def        A__ (		self	, __lowerCAmelCase		):







            """simple docstring"""



            if index in self.fairseq_ids_to_tokens:
                  return self.fairseq_ids_to_tokens[index]
            return self.sp_model.IdToPiece(index - self.fairseq_offset		)

      def        A__ (		self	, __lowerCAmelCase		):







            """simple docstring"""



            lowercase														=			"""""".join(__lowerCAmelCase		).replace(__lowerCAmelCase	, """ """		).strip()
            return out_string







      def        A__ (		self	, __lowerCAmelCase	, __lowerCAmelCase = None		):







            """simple docstring"""



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

            if os.path.abspath(self.vocab_file		) != os.path.abspath(__lowerCAmelCase		) and os.path.isfile(self.vocab_file		):
                  copyfile(self.vocab_file	, __lowerCAmelCase		)
            elif not os.path.isfile(self.vocab_file		):
                  with open(__lowerCAmelCase	, """wb"""		) as fi:
                        lowercase														=			self.sp_model.serialized_model_proto()
                        fi.write(__lowerCAmelCase		)

            return (out_vocab_file,)




"""simple docstring"""






from __future__ import annotations


def     UpperCAmelCase__ (       lowerCAmelCase__  :list[float]      ,	lowerCAmelCase__  :list[float]	)				->					float:
      '''simple docstring'''


      lowercase														=			sorted(numsa + numsa	)
      lowercase							,							lowercase														=			divmod(len(lowerCAmelCase__	)      ,	2	)
      if mod == 1:
            return all_numbers[div]
      else:
            return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       __lowerCAmelCase					: List[Any]        =[float(x) for x in input("""Enter the elements of first array: """).split()]
       __lowerCAmelCase					: List[Any]        =[float(x) for x in input("""Enter the elements of second array: """).split()]
       print(F"""The median of two arrays is: {median_of_two_arrays(array_a, array_a)}""")



