"""simple docstring"""





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

import sentencepiece as spm

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


_UpperCamelCase  :		Optional[int]           =       logging.get_logger(__name__)

_UpperCamelCase  :		List[Any]           =       '''▁'''

_UpperCamelCase  :		Optional[Any]           =       {'''vocab_file''': '''sentencepiece.bpe.model'''}

_UpperCamelCase  :		int           =       {
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    }
}

_UpperCamelCase  :		Dict           =       {
    '''facebook/xglm-564M''': 20_48,
}


class 	UpperCAmelCase_      (       _a):
      lowerCamelCase__						:       Optional[Any]					    =    VOCAB_FILES_NAMES
      lowerCamelCase__						:       Optional[int]					    =    PRETRAINED_VOCAB_FILES_MAP
      lowerCamelCase__						:       Dict					    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCamelCase__						:       Optional[int]					    =    ["input_ids", "attention_mask"]


      def __init__(  self						,     a						,     a="<s>"						,     a="</s>"						,     a="</s>"						,     a="<s>"						,     a="<unk>"						,     a="<pad>"						,     a = None						,     **a						,     )			->   None:
             lowercase__     :						Tuple         =      {} if sp_model_kwargs is None else sp_model_kwargs

             # Compatibility with the original tokenizer
             lowercase__     :						int         =      7
             lowercase__     :						Tuple         =      [f"""<madeupword{i}>""" for i in range(self.num_madeup_words				)]

             lowercase__     :						List[str]         =      kwargs.get('additional_special_tokens'						,     []				)
             kwargs["additional_special_tokens"] += [
                 word for word in madeup_words if word not in kwargs["additional_special_tokens"]
             ]

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

             lowercase__     :						Dict         =      spm.SentencePieceProcessor(**self.sp_model_kwargs				)
             self.sp_model.Load(str(UpperCamelCase_				)				)
             lowercase__     :						Any         =      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'

             # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
             lowercase__     :						List[str]         =      1

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

             lowercase__     :						Any         =      len(self.sp_model				)
             lowercase__     :						Dict         =      {f"""<madeupword{i}>""": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words				)}
             self.fairseq_tokens_to_ids.update(UpperCamelCase_				)

             lowercase__     :						List[Any]         =      {v: k for k, v in self.fairseq_tokens_to_ids.items()}


      def __getstate__(  self				)			->   List[Any]:
             lowercase__     :						Any         =      self.__dict__.copy()
             lowercase__     :						Any         =      None
             lowercase__     :						Any         =      self.sp_model.serialized_model_proto()
             return state


      def __setstate__(  self						,     a				)			->   Optional[int]:
             lowercase__     :						int         =      d

             # for backward compatibility
             if not hasattr(self						,     'sp_model_kwargs'				):
                    lowercase__     :						Optional[int]         =      {}

             lowercase__     :						Union[str, Any]         =      spm.SentencePieceProcessor(**self.sp_model_kwargs				)
             self.sp_model.LoadFromSerializedProto(self.sp_model_proto				)


      def 						_UpperCAmelCase			(  self						,     a						,     a = None				)			->   List[int]:

             if token_ids_a is None:
                    return [self.sep_token_id] + token_ids_a
             lowercase__     :						Union[str, Any]         =      [self.sep_token_id]
             return sep + token_ids_a + sep + sep + token_ids_a


      def 						_UpperCAmelCase			(  self						,     a						,     a = None						,     a = False				)			->   List[int]:

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

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


      def 						_UpperCAmelCase			(  self						,     a						,     a = None				)			->   List[int]:
             lowercase__     :						Union[str, Any]         =      [self.sep_token_id]

             if token_ids_a is None:
                    return len(sep + token_ids_a				) * [0]
             return len(sep + token_ids_a + sep + sep + token_ids_a				) * [0]


      @property
      def 						_UpperCAmelCase			(  self				)			->   Union[str, Any]:
             return len(self.sp_model				) + self.fairseq_offset + self.num_madeup_words


      def 						_UpperCAmelCase			(  self				)			->   List[str]:
             lowercase__     :						List[str]         =      {self.convert_ids_to_tokens(UpperCamelCase_				): i for i in range(self.vocab_size				)}
             vocab.update(self.added_tokens_encoder				)
             return vocab


      def 						_UpperCAmelCase			(  self						,     a				)			->   List[str]:
             return self.sp_model.encode(UpperCamelCase_						,     out_type=UpperCamelCase_				)


      def 						_UpperCAmelCase			(  self						,     a				)			->   str:
             if token in self.fairseq_tokens_to_ids:
                    return self.fairseq_tokens_to_ids[token]
             lowercase__     :						List[Any]         =      self.sp_model.PieceToId(UpperCamelCase_				)

             # 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 						_UpperCAmelCase			(  self						,     a				)			->   Tuple:
             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 						_UpperCAmelCase			(  self						,     a				)			->   Optional[Any]:
             lowercase__     :						Optional[int]         =      ''.join(UpperCamelCase_				).replace(UpperCamelCase_						,     ' '				).strip()
             return out_string


      def 						_UpperCAmelCase			(  self						,     a						,     a = None				)			->   Tuple[str]:
             if not os.path.isdir(UpperCamelCase_				):
                    logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
                    return
             lowercase__     :						List[Any]         =      os.path.join(
                 UpperCamelCase_						,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

             if os.path.abspath(self.vocab_file				) != os.path.abspath(UpperCamelCase_				) and os.path.isfile(self.vocab_file				):
                    copyfile(self.vocab_file						,     UpperCamelCase_				)
             elif not os.path.isfile(self.vocab_file				):
                    with open(UpperCamelCase_						,     'wb'				) as fi:
                           lowercase__     :						List[str]         =      self.sp_model.serialized_model_proto()
                           fi.write(UpperCamelCase_				)

             return (out_vocab_file,)








'''simple docstring'''




from __future__ import annotations

import math




def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)   ->int:

	if depth < 0:
		raise ValueError('Depth cannot be less than 0'							)

	if not scores:
		raise ValueError('Scores cannot be empty'							)

	if depth == height:
		return scores[node_index]

	return (
	    max(
	        minimax(depth + 1					,				node_index * 2					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)					,				minimax(depth + 1					,				node_index * 2 + 1					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)					,				)
	    if is_max
	    else min(
	        minimax(depth + 1					,				node_index * 2					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)					,				minimax(depth + 1					,				node_index * 2 + 1					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)					,				)
	)




def 						__lowerCamelCase			(	)   ->None:
	snake_case__	       =   [90, 23, 6, 33, 21, 65, 1_23, 3_44_23]
	snake_case__	       =   math.log(len(UpperCAmelCase_							)					,				2							)
	print(f'''Optimal value : {minimax(0					,				0					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)}'''							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			main()



