

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

import sentencepiece

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


_a				   =							logging.get_logger(__name__)

_a				   =							{
    'source_spm': 'source.spm',
    'target_spm': 'target.spm',
    'vocab': 'vocab.json',
    'target_vocab_file': 'target_vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
}

_a				   =							{
    'source_spm': {
        'Helsinki-NLP/opus-mt-en-de': 'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/source.spm'
    },
    'target_spm': {
        'Helsinki-NLP/opus-mt-en-de': 'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/target.spm'
    },
    'vocab': {
        'Helsinki-NLP/opus-mt-en-de': 'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/vocab.json'
    },
    'tokenizer_config_file': {
        'Helsinki-NLP/opus-mt-en-de': (
            'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/tokenizer_config.json'
        )
    },
}

_a				   =							{'Helsinki-NLP/opus-mt-en-de': 5_12}
_a				   =							{}




class       _lowerCAmelCase						(			lowercase     ):







 """simple docstring"""







 __UpperCAmelCase			:      Optional[int]     	=			VOCAB_FILES_NAMES
 __UpperCAmelCase			:      Any     	=			PRETRAINED_VOCAB_FILES_MAP
 __UpperCAmelCase			:      Dict     	=			PRETRAINED_INIT_CONFIGURATION
 __UpperCAmelCase			:      Tuple     	=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __UpperCAmelCase			:      Tuple     	=			["input_ids", "attention_mask"]
 __UpperCAmelCase			:      List[Any]     	=			re.compile(">>.+<<"     )  # type: re.Pattern


 def __init__(    self							:    str,      UpperCAmelCase__							:    int,      UpperCAmelCase__							:    Union[str, Any],      UpperCAmelCase__							:    List[Any],      UpperCAmelCase__							:    str=None,      UpperCAmelCase__							:    int=None,      UpperCAmelCase__							:    List[str]=None,      UpperCAmelCase__							:    List[Any]="<unk>",      UpperCAmelCase__							:    str="</s>",      UpperCAmelCase__							:    Any="<pad>",      UpperCAmelCase__							:    List[Any]=5_1_2,      UpperCAmelCase__							:    Optional[Dict[str, Any]] = None,      UpperCAmelCase__							:    Tuple=False,      **UpperCAmelCase__							:    Union[str, Any],      ):
    __lowercase			=		{} if sp_model_kwargs is None else sp_model_kwargs

    super().__init__(
        # bos_token=bos_token,  unused. Start decoding with config.decoder_start_token_id
        source_lang=UpperCAmelCase__,      target_lang=UpperCAmelCase__,      unk_token=UpperCAmelCase__,      eos_token=UpperCAmelCase__,      pad_token=UpperCAmelCase__,      model_max_length=UpperCAmelCase__,      sp_model_kwargs=self.sp_model_kwargs,      target_vocab_file=UpperCAmelCase__,      separate_vocabs=UpperCAmelCase__,      **UpperCAmelCase__,      )
    assert Path(UpperCAmelCase__			).exists(), F"""cannot find spm source {source_spm}"""

    __lowercase			=		separate_vocabs
    __lowercase			=		load_json(UpperCAmelCase__			)
    if self.unk_token not in self.encoder:
       raise KeyError("<unk> token must be in vocab"			)
    assert self.pad_token in self.encoder

    if separate_vocabs:
       __lowercase			=		load_json(UpperCAmelCase__			)
       __lowercase			=		{v: k for k, v in self.target_encoder.items()}
       __lowercase			=		[]
    else:
       __lowercase			=		{v: k for k, v in self.encoder.items()}
       __lowercase			=		[k for k in self.encoder if k.startswith(">>"			) and k.endswith("<<"			)]

    __lowercase			=		source_lang
    __lowercase			=		target_lang
    __lowercase			=		[source_spm, target_spm]

    # load SentencePiece model for pre-processing
    __lowercase			=		load_spm(UpperCAmelCase__,      self.sp_model_kwargs			)
    __lowercase			=		load_spm(UpperCAmelCase__,      self.sp_model_kwargs			)
    __lowercase			=		self.spm_source
    __lowercase			=		self.encoder

    # Multilingual target side: default to using first supported language code.

    self._setup_normalizer()


 def       _lowercase				(    self							:    str			):
    try:
       from sacremoses import MosesPunctNormalizer

       __lowercase			=		MosesPunctNormalizer(self.source_lang			).normalize
    except (ImportError, FileNotFoundError):
       warnings.warn("Recommended: pip install sacremoses."			)
       __lowercase			=		lambda UpperCAmelCase__			: x


 def       _lowercase				(    self							:    Tuple,      UpperCAmelCase__							:    str			):
    return self.punc_normalizer(UpperCAmelCase__			) if x else ""


 def       _lowercase				(    self							:    int,      UpperCAmelCase__							:    str			):
    return self.current_encoder.get(UpperCAmelCase__,      self.current_encoder[self.unk_token]			)


 def       _lowercase				(    self							:    List[Any],      UpperCAmelCase__							:    str			):
    __lowercase			=		self.language_code_re.match(UpperCAmelCase__			)
    __lowercase			=		[match.group(0			)] if match else []
    return code, self.language_code_re.sub("",      UpperCAmelCase__			)


 def       _lowercase				(    self							:    List[str],      UpperCAmelCase__							:    str			):
    __lowercase	,__lowercase			=		self.remove_language_code(UpperCAmelCase__			)
    __lowercase			=		self.current_spm.encode(UpperCAmelCase__,      out_type=UpperCAmelCase__			)
    return code + pieces


 def       _lowercase				(    self							:    Dict,      UpperCAmelCase__							:    int			):
    return self.decoder.get(UpperCAmelCase__,      self.unk_token			)


 def       _lowercase				(    self							:    int,      UpperCAmelCase__							:    str,      **UpperCAmelCase__							:    int			):
    return super().batch_decode(UpperCAmelCase__,      **UpperCAmelCase__			)


 def       _lowercase				(    self							:    int,      UpperCAmelCase__							:    Tuple,      **UpperCAmelCase__							:    Dict			):
    return super().decode(UpperCAmelCase__,      **UpperCAmelCase__			)


 def       _lowercase				(    self							:    Optional[int],      UpperCAmelCase__							:    List[str]			):
    __lowercase			=		self.spm_source if self._decode_use_source_tokenizer else self.spm_target
    __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 += sp_model.decode_pieces(UpperCAmelCase__			) + token + " "
          __lowercase			=		[]
       else:
          current_sub_tokens.append(UpperCAmelCase__			)
    out_string += sp_model.decode_pieces(UpperCAmelCase__			)
    return out_string.strip()


 def       _lowercase				(    self							:    Optional[int],      UpperCAmelCase__							:    Any,      UpperCAmelCase__							:    str=None			):
    if token_ids_a is None:
       return token_ids_a + [self.eos_token_id]
    # We don't expect to process pairs, but leave the pair logic for API consistency
    return token_ids_a + token_ids_a + [self.eos_token_id]


 def       _lowercase				(    self							:    Optional[Any]			):
    __lowercase			=		self.spm_source
    __lowercase			=		self.encoder


 def       _lowercase				(    self							:    Optional[int]			):
    __lowercase			=		self.spm_target
    if self.separate_vocabs:
       __lowercase			=		self.target_encoder


 @property
 def       _lowercase				(    self							:    Optional[int]			):
    return len(self.encoder			)


 def       _lowercase				(    self							:    Optional[int],      UpperCAmelCase__							:    str,      UpperCAmelCase__							:    Optional[str] = None			):
    if not os.path.isdir(UpperCAmelCase__			):
       logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""			)
       return
    __lowercase			=		[]

    if self.separate_vocabs:
       __lowercase			=		os.path.join(
           UpperCAmelCase__,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab"],      )
       __lowercase			=		os.path.join(
           UpperCAmelCase__,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["target_vocab_file"],      )
       save_json(self.encoder,      UpperCAmelCase__			)
       save_json(self.target_encoder,      UpperCAmelCase__			)
       saved_files.append(UpperCAmelCase__			)
       saved_files.append(UpperCAmelCase__			)
    else:
       __lowercase			=		os.path.join(
           UpperCAmelCase__,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab"]			)
       save_json(self.encoder,      UpperCAmelCase__			)
       saved_files.append(UpperCAmelCase__			)

    for spm_save_filename, spm_orig_path, spm_model in zip(
        [VOCAB_FILES_NAMES["source_spm"], VOCAB_FILES_NAMES["target_spm"]],      self.spm_files,      [self.spm_source, self.spm_target],      ):
       __lowercase			=		os.path.join(
           UpperCAmelCase__,      (filename_prefix + "-" if filename_prefix else "") + spm_save_filename			)
       if os.path.abspath(UpperCAmelCase__			) != os.path.abspath(UpperCAmelCase__			) and os.path.isfile(UpperCAmelCase__			):
          copyfile(UpperCAmelCase__,      UpperCAmelCase__			)
          saved_files.append(UpperCAmelCase__			)
       elif not os.path.isfile(UpperCAmelCase__			):
          with open(UpperCAmelCase__,      "wb"			) as fi:
             __lowercase			=		spm_model.serialized_model_proto()
             fi.write(UpperCAmelCase__			)
          saved_files.append(UpperCAmelCase__			)

    return tuple(UpperCAmelCase__			)


 def       _lowercase				(    self							:    int			):
    return self.get_src_vocab()


 def       _lowercase				(    self							:    List[str]			):
    return dict(self.encoder,      **self.added_tokens_encoder			)


 def       _lowercase				(    self							:    Tuple			):
    return dict(self.target_encoder,      **self.added_tokens_decoder			)


 def __getstate__(    self							:    int			):
    __lowercase			=		self.__dict__.copy()
    state.update(
        {k: None for k in ["spm_source", "spm_target", "current_spm", "punc_normalizer", "target_vocab_file"]}			)
    return state


 def __setstate__(    self							:    str,      UpperCAmelCase__							:    Dict			):
    __lowercase			=		d

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

    __lowercase	,__lowercase			=		(load_spm(UpperCAmelCase__,      self.sp_model_kwargs			) for f in self.spm_files)
    __lowercase			=		self.spm_source
    self._setup_normalizer()


 def       _lowercase				(    self							:    str,      *UpperCAmelCase__							:    int,      **UpperCAmelCase__							:    List[Any]			):
    return 1


 def       _lowercase				(    self							:    Dict,      UpperCAmelCase__							:    Optional[Any]			):
    __lowercase			=		set(self.all_special_ids			)  # call it once instead of inside list comp
    all_special_ids.remove(self.unk_token_id			)  # <unk> is only sometimes special
    return [1 if x in all_special_ids else 0 for x in seq]



 def       _lowercase				(    self							:    List[Any],      UpperCAmelCase__							:    List,      UpperCAmelCase__							:    Optional[List] = None,      UpperCAmelCase__							:    bool = False			):
    if already_has_special_tokens:
       return self._special_token_mask(UpperCAmelCase__			)
    elif token_ids_a is None:
       return self._special_token_mask(UpperCAmelCase__			) + [1]
    else:
       return self._special_token_mask(token_ids_a + token_ids_a			) + [1]







def 						_A						(						UpperCamelCase_  : str,    UpperCamelCase_  : Dict[str, Any])			->		sentencepiece.SentencePieceProcessor:
   '''simple docstring'''


   __lowercase			=		sentencepiece.SentencePieceProcessor(**UpperCamelCase_)
   spm.Load(UpperCamelCase_)
   return spm




def 						_A						(						UpperCamelCase_  : Any,    UpperCamelCase_  : str)			->		None:
   '''simple docstring'''


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




def 						_A						(						UpperCamelCase_  : str)			->		Union[Dict, List]:
   '''simple docstring'''


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







"""simple docstring"""





def 						_A						(						UpperCamelCase_  : list,    UpperCamelCase_  : list,    UpperCamelCase_  : list,    UpperCamelCase_  : int,    UpperCamelCase_  : int)			->		None:
   '''simple docstring'''


   if target == 0:
      answer.append(path.copy())
   else:
      for index in range(UpperCamelCase_,    len(UpperCamelCase_)):
         if target >= candidates[index]:
            path.append(candidates[index])
            backtrack(UpperCamelCase_,    UpperCamelCase_,    UpperCamelCase_,    target - candidates[index],    UpperCamelCase_)
            path.pop(len(UpperCamelCase_) - 1)




def 						_A						(						UpperCamelCase_  : list,    UpperCamelCase_  : int)			->		list:
   '''simple docstring'''


   __lowercase			=		[]  # type: list[int]
   __lowercase			=		[]  # type: list[int]
   backtrack(UpperCamelCase_,    UpperCamelCase_,    UpperCamelCase_,    UpperCamelCase_,    0)
   return answer




def 						_A						(						)			->		None:
   '''simple docstring'''


   print(combination_sum([-8, 2.3, 0],    1))


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   main()




