





"""simple docstring"""
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


lowerCAmelCase:	Optional[Any]							      =logging.get_logger(__name__)

lowerCAmelCase:	Union[str, Any]							      ={
    """source_spm""": """source.spm""",
    """target_spm""": """target.spm""",
    """vocab""": """vocab.json""",
    """target_vocab_file""": """target_vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

lowerCAmelCase:	Optional[int]							      ={
    """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"""
        )
    },
}

lowerCAmelCase:	int							      ={"""Helsinki-NLP/opus-mt-en-de""": 512}
lowerCAmelCase:	Dict							      ={}
class lowerCamelCase__  (    UpperCAmelCase__				):
   __UpperCAmelCase        =					VOCAB_FILES_NAMES
   __UpperCAmelCase        =					PRETRAINED_VOCAB_FILES_MAP
   __UpperCAmelCase        =					PRETRAINED_INIT_CONFIGURATION
   __UpperCAmelCase        =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __UpperCAmelCase        =					['input_ids', 'attention_mask']
   __UpperCAmelCase        =					re.compile(""">>.+<<"""				)  # type: re.Pattern



   def __init__(       self      ,   snake_case      ,   snake_case      ,   snake_case      ,   snake_case=None      ,   snake_case=None      ,   snake_case=None      ,   snake_case="<unk>"      ,   snake_case="</s>"      ,   snake_case="<pad>"      ,   snake_case=5_1_2      ,   snake_case = None      ,   snake_case=False      ,   **snake_case      ,   ) ->    Any:







      """simple docstring"""
      lowercase    :			Union[str, Any]  =       {} 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=lowerCamelCase__      ,   target_lang=lowerCamelCase__      ,   unk_token=lowerCamelCase__      ,   eos_token=lowerCamelCase__      ,   pad_token=lowerCamelCase__      ,   model_max_length=lowerCamelCase__      ,   sp_model_kwargs=self.sp_model_kwargs      ,   target_vocab_file=lowerCamelCase__      ,   separate_vocabs=lowerCamelCase__      ,   **lowerCamelCase__      ,   )
      assert Path(lowerCamelCase__	).exists(), f'''cannot find spm source {source_spm}'''

      lowercase    :			Optional[int]  =       separate_vocabs
      lowercase    :			Dict  =       load_json(lowerCamelCase__	)
      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    :			Any  =       load_json(lowerCamelCase__	)
         lowercase    :			Tuple  =       {v: k for k, v in self.target_encoder.items()}
         lowercase    :			List[Any]  =       []
      else:
         lowercase    :			int  =       {v: k for k, v in self.encoder.items()}
         lowercase    :			list  =       [k for k in self.encoder if k.startswith(""">>"""	) and k.endswith("""<<"""	)]

      lowercase    :			List[Any]  =       source_lang
      lowercase    :			int  =       target_lang
      lowercase    :			List[str]  =       [source_spm, target_spm]

      # load SentencePiece model for pre-processing
      lowercase    :			int  =       load_spm(lowerCamelCase__      ,   self.sp_model_kwargs	)
      lowercase    :			str  =       load_spm(lowerCamelCase__      ,   self.sp_model_kwargs	)
      lowercase    :			Optional[Any]  =       self.spm_source
      lowercase    :			Tuple  =       self.encoder

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

      self._setup_normalizer()



   def    _UpperCAmelCase	(       self	) ->    str:







      """simple docstring"""
      try:
         from sacremoses import MosesPunctNormalizer

         lowercase    :			str  =       MosesPunctNormalizer(self.source_lang	).normalize
      except (ImportError, FileNotFoundError):
         warnings.warn("""Recommended: pip install sacremoses."""	)
         lowercase    :			Any  =       lambda snake_case	: x



   def    _UpperCAmelCase	(       self      ,   snake_case	) ->    str:







      """simple docstring"""
      return self.punc_normalizer(lowerCamelCase__	) if x else ""



   def    _UpperCAmelCase	(       self      ,   snake_case	) ->    int:







      """simple docstring"""
      return self.current_encoder.get(lowerCamelCase__      ,   self.current_encoder[self.unk_token]	)



   def    _UpperCAmelCase	(       self      ,   snake_case	) ->    Tuple:







      """simple docstring"""
      lowercase    :			Dict  =       self.language_code_re.match(lowerCamelCase__	)
      lowercase    :			list  =       [match.group(0	)] if match else []
      return code, self.language_code_re.sub(""""""      ,   lowerCamelCase__	)



   def    _UpperCAmelCase	(       self      ,   snake_case	) ->    Tuple:







      """simple docstring"""
      lowercase    :			List[Any]  =       self.remove_language_code(lowerCamelCase__	)
      lowercase    :			Any  =       self.current_spm.encode(lowerCamelCase__      ,   out_type=lowerCamelCase__	)
      return code + pieces



   def    _UpperCAmelCase	(       self      ,   snake_case	) ->    List[Any]:







      """simple docstring"""
      return self.decoder.get(lowerCamelCase__      ,   self.unk_token	)



   def    _UpperCAmelCase	(       self      ,   snake_case      ,   **snake_case	) ->    List[Any]:







      """simple docstring"""
      return super().batch_decode(lowerCamelCase__      ,   **lowerCamelCase__	)



   def    _UpperCAmelCase	(       self      ,   snake_case      ,   **snake_case	) ->    Tuple:







      """simple docstring"""
      return super().decode(lowerCamelCase__      ,   **lowerCamelCase__	)



   def    _UpperCAmelCase	(       self      ,   snake_case	) ->    Union[str, Any]:







      """simple docstring"""
      lowercase    :			List[str]  =       self.spm_source if self._decode_use_source_tokenizer else self.spm_target
      lowercase    :			List[str]  =       []
      lowercase    :			List[Any]  =       ""
      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(lowerCamelCase__	) + token + " "
            lowercase    :			Union[str, Any]  =       []
         else:
            current_sub_tokens.append(lowerCamelCase__	)
      out_string += sp_model.decode_pieces(lowerCamelCase__	)
      return out_string.strip()



   def    _UpperCAmelCase	(       self      ,   snake_case      ,   snake_case=None	) ->    List[Any]:







      """simple docstring"""
      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    _UpperCAmelCase	(       self	) ->    Dict:







      """simple docstring"""
      lowercase    :			Union[str, Any]  =       self.spm_source
      lowercase    :			Tuple  =       self.encoder



   def    _UpperCAmelCase	(       self	) ->    Optional[Any]:







      """simple docstring"""
      lowercase    :			List[Any]  =       self.spm_target
      if self.separate_vocabs:
         lowercase    :			Tuple  =       self.target_encoder



   @property
   def    _UpperCAmelCase	(       self	) ->    Tuple:







      """simple docstring"""
      return len(self.encoder	)



   def    _UpperCAmelCase	(       self      ,   snake_case      ,   snake_case = None	) ->    List[Any]:







      """simple docstring"""
      if not os.path.isdir(lowerCamelCase__	):
         logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
         return
      lowercase    :			Tuple  =       []

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

      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    :			List[str]  =       os.path.join(
             lowerCamelCase__      ,   (filename_prefix + """-""" if filename_prefix else """""") + spm_save_filename	)
         if os.path.abspath(lowerCamelCase__	) != os.path.abspath(lowerCamelCase__	) and os.path.isfile(lowerCamelCase__	):
            copyfile(lowerCamelCase__      ,   lowerCamelCase__	)
            saved_files.append(lowerCamelCase__	)
         elif not os.path.isfile(lowerCamelCase__	):
            with open(lowerCamelCase__      ,   """wb"""	) as fi:
               lowercase    :			str  =       spm_model.serialized_model_proto()
               fi.write(lowerCamelCase__	)
            saved_files.append(lowerCamelCase__	)

      return tuple(lowerCamelCase__	)



   def    _UpperCAmelCase	(       self	) ->    str:







      """simple docstring"""
      return self.get_src_vocab()



   def    _UpperCAmelCase	(       self	) ->    Any:







      """simple docstring"""
      return dict(self.encoder      ,   **self.added_tokens_encoder	)



   def    _UpperCAmelCase	(       self	) ->    Optional[int]:







      """simple docstring"""
      return dict(self.target_encoder      ,   **self.added_tokens_decoder	)



   def __getstate__(       self	) ->    Optional[int]:







      """simple docstring"""
      lowercase    :			List[Any]  =       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      ,   snake_case	) ->    List[str]:







      """simple docstring"""
      lowercase    :			Union[str, Any]  =       d

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

      lowercase    :			Tuple  =       (load_spm(lowerCamelCase__      ,   self.sp_model_kwargs	) for f in self.spm_files)
      lowercase    :			Any  =       self.spm_source
      self._setup_normalizer()



   def    _UpperCAmelCase	(       self      ,   *snake_case      ,   **snake_case	) ->    Any:







      """simple docstring"""
      return 1



   def    _UpperCAmelCase	(       self      ,   snake_case	) ->    Dict:







      """simple docstring"""
      lowercase    :			Union[str, Any]  =       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    _UpperCAmelCase	(       self      ,   snake_case      ,   snake_case = None      ,   snake_case = False	) ->    List[str]:







      """simple docstring"""
      if already_has_special_tokens:
         return self._special_token_mask(lowerCamelCase__	)
      elif token_ids_a is None:
         return self._special_token_mask(lowerCamelCase__	) + [1]
      else:
         return self._special_token_mask(token_ids_a + token_ids_a	) + [1]




def 			__snake_case						(      __A ,__A    )		->				Tuple:
   lowercase    :			Dict  =       sentencepiece.SentencePieceProcessor(**__A    )
   spm.Load(__A    )
   return spm




def 			__snake_case						(      __A ,__A    )		->				int:
   with open(__A ,"""w"""    ) as f:
      json.dump(__A ,__A ,indent=2    )







def 			__snake_case						(      __A    )		->				str:
   with open(__A ,"""r"""    ) as f:
      return json.load(__A    )









"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase:	int							      =logging.get_logger(__name__)

lowerCAmelCase:	int							      ={
    "bert-base-uncased": "https://huggingface.co/bert-base-uncased/resolve/main/config.json",
    # QDQBERT models can be loaded from any BERT checkpoint, available at https://huggingface.co/models?filter=bert
}
class lowerCamelCase__  (    __UpperCamelCase				):
   __UpperCAmelCase        =					"""qdqbert"""



   def __init__(       self      ,   snake_case=3_0_5_2_2      ,   snake_case=7_6_8      ,   snake_case=1_2      ,   snake_case=1_2      ,   snake_case=3_0_7_2      ,   snake_case="gelu"      ,   snake_case=0.1      ,   snake_case=0.1      ,   snake_case=5_1_2      ,   snake_case=2      ,   snake_case=0.02      ,   snake_case=1E-12      ,   snake_case=True      ,   snake_case=1      ,   snake_case=0      ,   snake_case=2      ,   **snake_case      ,   ) ->    List[str]:







      """simple docstring"""
      super().__init__(pad_token_id=snake_case      ,   bos_token_id=snake_case      ,   eos_token_id=snake_case      ,   **snake_case	)

      lowercase    :			Optional[Any]  =       vocab_size
      lowercase    :			int  =       max_position_embeddings
      lowercase    :			Dict  =       hidden_size
      lowercase    :			Union[str, Any]  =       num_hidden_layers
      lowercase    :			str  =       num_attention_heads
      lowercase    :			List[str]  =       intermediate_size
      lowercase    :			List[str]  =       hidden_act
      lowercase    :			List[str]  =       hidden_dropout_prob
      lowercase    :			Optional[Any]  =       attention_probs_dropout_prob
      lowercase    :			Optional[Any]  =       initializer_range
      lowercase    :			str  =       type_vocab_size
      lowercase    :			Optional[int]  =       layer_norm_eps
      lowercase    :			Optional[int]  =       use_cache


