


"""simple docstring"""

from __future__ import annotations

import math


def lowerCAmelCase_   (					UpperCamelCase__						:			int					, UpperCamelCase__						:			int					, UpperCamelCase__						:			bool					, UpperCamelCase__						:			list[int]					, UpperCamelCase__						:			float			):






 """simple docstring"""







 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_   (					):






 """simple docstring"""







 __lowercase						=						[90, 23, 6, 33, 21, 65, 123, 34423]
 __lowercase						=						math.log(len(UpperCamelCase__			)					, 2			)
 print(f'''Optimal value : {minimax(0					, 0					, UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__			)}'''			)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       main()




"""simple docstring"""

import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

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


UpperCAmelCase__					=logging.get_logger(__name__)

UpperCAmelCase__					="▁"

UpperCAmelCase__					={
    "vocab_file": "vocab.json",
    "spm_file": "sentencepiece.bpe.model",
    "tokenizer_config_file": "tokenizer_config.json",
}

UpperCAmelCase__					={
    "vocab_file": {
        "facebook/m2m100_418M": "https://huggingface.co/facebook/m2m100_418M/resolve/main/vocab.json",
        "facebook/m2m100_1.2B": "https://huggingface.co/facebook/m2m100_1.2B/resolve/main/vocab.json",
    },
    "spm_file": {
        "facebook/m2m100_418M": "https://huggingface.co/facebook/m2m100_418M/resolve/main/sentencepiece.bpe.model",
        "facebook/m2m100_1.2B": "https://huggingface.co/facebook/m2m100_1.2B/resolve/main/sentencepiece.bpe.model",
    },
    "tokenizer_config_file": {
        "facebook/m2m100_418M": "https://huggingface.co/facebook/m2m100_418M/resolve/main/tokenizer_config.json",
        "facebook/m2m100_1.2B": "https://huggingface.co/facebook/m2m100_1.2B/resolve/main/tokenizer_config.json",
    },
}

UpperCAmelCase__					={
    "facebook/m2m100_418M": 1024,
}

# fmt: off
UpperCAmelCase__					={
    "m2m100": ["af", "am", "ar", "ast", "az", "ba", "be", "bg", "bn", "br", "bs", "ca", "ceb", "cs", "cy", "da", "de", "el", "en", "es", "et", "fa", "ff", "fi", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "he", "hi", "hr", "ht", "hu", "hy", "id", "ig", "ilo", "is", "it", "ja", "jv", "ka", "kk", "km", "kn", "ko", "lb", "lg", "ln", "lo", "lt", "lv", "mg", "mk", "ml", "mn", "mr", "ms", "my", "ne", "nl", "no", "ns", "oc", "or", "pa", "pl", "ps", "pt", "ro", "ru", "sd", "si", "sk", "sl", "so", "sq", "sr", "ss", "su", "sv", "sw", "ta", "th", "tl", "tn", "tr", "uk", "ur", "uz", "vi", "wo", "xh", "yi", "yo", "zh", "zu"],
    "wmt21": ["en", "ha", "is", "ja", "cs", "ru", "zh", "de"]
}





class  lowerCamelCase__    (		_a     ):
      a			:  str           =		VOCAB_FILES_NAMES
      a			:  Dict           =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a			:  int           =		PRETRAINED_VOCAB_FILES_MAP
      a			:  Union[str, Any]           =		["""input_ids""", """attention_mask"""]

      a			:  List[int]           =		[]
      a			:  List[int]           =		[]
      def __init__(		self						:						Optional[Any]   ,							A_						:						str   ,							A_						:						Dict   ,							A_						:						str=None   ,							A_						:						Dict=None   ,							A_						:						str="<s>"   ,							A_						:						Any="</s>"   ,							A_						:						List[Any]="</s>"   ,							A_						:						List[str]="<pad>"   ,							A_						:						Optional[int]="<unk>"   ,							A_						:						str="m2m100"   ,							A_						:						Optional[Dict[str, Any]] = None   ,							A_						:						Tuple=8   ,							**A_						:						Dict   ,							):






       '''simple docstring'''


       __lowercase						=						{} if sp_model_kwargs is None else sp_model_kwargs

       __lowercase						=						language_codes
       __lowercase						=						FAIRSEQ_LANGUAGE_CODES[language_codes]
       __lowercase						=						{lang_code: F'''__{lang_code}__''' for lang_code in fairseq_language_code}

       __lowercase						=						kwargs.get("""additional_special_tokens"""   ,							[]				)
       kwargs["additional_special_tokens"] += [
           self.get_lang_token(A_				)
           for lang_code in fairseq_language_code
           if self.get_lang_token(A_				) not in kwargs["additional_special_tokens"]
       ]

       super().__init__(
           src_lang=A_   ,							tgt_lang=A_   ,							bos_token=A_   ,							eos_token=A_   ,							sep_token=A_   ,							unk_token=A_   ,							pad_token=A_   ,							language_codes=A_   ,							sp_model_kwargs=self.sp_model_kwargs   ,							num_madeup_words=A_   ,							**A_   ,							)

       __lowercase						=						vocab_file
       __lowercase						=						load_json(A_				)
       __lowercase						=						{v: k for k, v in self.encoder.items()}
       __lowercase						=						spm_file
       __lowercase						=						load_spm(A_   ,							self.sp_model_kwargs				)

       __lowercase						=						len(self.encoder				)

       __lowercase						=						{
           self.get_lang_token(A_				): self.encoder_size + i for i, lang_code in enumerate(A_				)
       }
       __lowercase						=						{lang_code: self.encoder_size + i for i, lang_code in enumerate(A_				)}
       __lowercase						=						{v: k for k, v in self.lang_token_to_id.items()}

       __lowercase						=						src_lang if src_lang is not None else """en"""
       __lowercase						=						tgt_lang
       __lowercase						=						self.get_lang_id(self._src_lang				)
       self.set_src_lang_special_tokens(self._src_lang				)

       __lowercase						=						num_madeup_words
      @property
      def SCREAMING_SNAKE_CASE_						(		self						:						Union[str, Any]				):






       '''simple docstring'''


       return len(self.encoder				) + len(self.lang_token_to_id				)
      @property
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict				):






       '''simple docstring'''


       return self._src_lang
      @src_lang.setter
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict   ,							A_						:						str				):






       '''simple docstring'''


       __lowercase						=						new_src_lang
       self.set_src_lang_special_tokens(self._src_lang				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict   ,							A_						:						str				):






       '''simple docstring'''


       return self.sp_model.encode(A_   ,							out_type=A_				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[Any]   ,							A_						:						str				):






       '''simple docstring'''


       if token in self.lang_token_to_id:
        return self.lang_token_to_id[token]
       return self.encoder.get(A_   ,							self.encoder[self.unk_token]				)
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]   ,							A_						:						int				):






       '''simple docstring'''


       if index in self.id_to_lang_token:
        return self.id_to_lang_token[index]
       return self.decoder.get(A_   ,							self.unk_token				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Tuple   ,							A_						:						Union[str, Any]				):






       '''simple docstring'''


       __lowercase						=						[]
       __lowercase						=						""""""
       for token in tokens:
        # make sure that special tokens are not decoded using sentencepiece model
        if token in self.all_special_tokens:
         out_string += self.sp_model.decode(A_				) + token
         __lowercase						=						[]
        else:
         current_sub_tokens.append(A_				)
       out_string += self.sp_model.decode(A_				)
       return out_string.strip()
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None   ,							A_						:						bool = 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_				)

       __lowercase						=						[1] * len(self.prefix_tokens				)
       __lowercase						=						[1] * len(self.suffix_tokens				)
       if token_ids_a is None:
        return prefix_ones + ([0] * len(A_				)) + suffix_ones
       return prefix_ones + ([0] * len(A_				)) + ([0] * len(A_				)) + suffix_ones
      def SCREAMING_SNAKE_CASE_						(		self						:						Any   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None				):






       '''simple docstring'''


       if token_ids_a is None:
        return self.prefix_tokens + token_ids_a + self.suffix_tokens
       # We don't expect to process pairs, but leave the pair logic for API consistency
       return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]				):






       '''simple docstring'''


       __lowercase						=						{self.convert_ids_to_tokens(A_				): i for i in range(self.vocab_size				)}
       vocab.update(self.added_tokens_encoder				)
       return vocab
      def __getstate__(		self						:						List[str]				):






       '''simple docstring'''


       __lowercase						=						self.__dict__.copy()
       __lowercase						=						None
       return state
      def __setstate__(		self						:						Optional[Any]   ,							A_						:						Dict				):






       '''simple docstring'''


       __lowercase						=						d

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

       __lowercase						=						load_spm(self.spm_file   ,							self.sp_model_kwargs				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Tuple   ,							A_						:						str   ,							A_						:						Optional[str] = None				):






       '''simple docstring'''


       __lowercase						=						Path(A_				)
       if not save_dir.is_dir():
        raise OSError(F'''{save_directory} should be a directory'''				)
       __lowercase						=						save_dir / (
           (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
       )
       __lowercase						=						save_dir / (
           (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
       )

       save_json(self.encoder   ,							A_				)

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

       return (str(A_				), str(A_				))
      def SCREAMING_SNAKE_CASE_						(		self						:						List[Any]   ,							A_						:						List[str]   ,							A_						:						str = "en"   ,							A_						:						Optional[List[str]] = None   ,							A_						:						str = "ro"   ,							**A_						:						List[Any]   ,							):






       '''simple docstring'''


       __lowercase						=						src_lang
       __lowercase						=						tgt_lang
       self.set_src_lang_special_tokens(self.src_lang				)
       return super().prepare_seqaseq_batch(A_   ,							A_   ,							**A_				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						List[Any]   ,							A_						:						Optional[str]   ,							A_						:						Optional[str]   ,							**A_						:						Optional[Any]				):






       '''simple docstring'''


       if src_lang is None or tgt_lang is None:
        raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""				)
       __lowercase						=						src_lang
       __lowercase						=						self(A_   ,							add_special_tokens=A_   ,							**A_				)
       __lowercase						=						self.get_lang_id(A_				)
       __lowercase						=						tgt_lang_id
       return inputs
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]				):






       '''simple docstring'''


       self.set_src_lang_special_tokens(self.src_lang				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]				):






       '''simple docstring'''


       self.set_tgt_lang_special_tokens(self.tgt_lang				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[Any]   ,							A_						:						str				):






       '''simple docstring'''


       __lowercase						=						self.get_lang_token(A_				)
       __lowercase						=						self.lang_token_to_id[lang_token]
       __lowercase						=						[self.cur_lang_id]
       __lowercase						=						[self.eos_token_id]
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						str				):






       '''simple docstring'''


       __lowercase						=						self.get_lang_token(A_				)
       __lowercase						=						self.lang_token_to_id[lang_token]
       __lowercase						=						[self.cur_lang_id]
       __lowercase						=						[self.eos_token_id]
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict   ,							A_						:						str				):






       '''simple docstring'''


       return self.lang_code_to_token[lang]






      def SCREAMING_SNAKE_CASE_						(		self						:						Dict   ,							A_						:						str				):






       '''simple docstring'''


       __lowercase						=						self.get_lang_token(A_				)
       return self.lang_token_to_id[lang_token]






def lowerCAmelCase_   (					UpperCamelCase__						:			str					, UpperCamelCase__						:			Dict[str, Any]			):






 """simple docstring"""







 __lowercase						=						sentencepiece.SentencePieceProcessor(**UpperCamelCase__			)
 spm.Load(str(UpperCamelCase__			)			)
 return spm


def lowerCAmelCase_   (					UpperCamelCase__						:			str			):






 """simple docstring"""







 with open(UpperCamelCase__					, """r"""			) as f:
  return json.load(UpperCamelCase__			)


def lowerCAmelCase_   (					UpperCamelCase__						:			List[str]					, UpperCamelCase__						:			str			):






 """simple docstring"""







 with open(UpperCamelCase__					, """w"""			) as f:
  json.dump(UpperCamelCase__					, UpperCamelCase__					, indent=2			)
