





import json
import os
from typing import Dict, List, Optional, Tuple

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


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


UpperCAmelCase	:	List[str]		     =       {
    """vocab_file""": """vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
    """merges_file""": """merges.txt""",
}

UpperCAmelCase	:	Any		     =       {
    """vocab_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"""
        ),
    },
    """tokenizer_config_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"""
        ),
    },
    """merges_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"""
        ),
    },
}

UpperCAmelCase	:	List[Any]		     =       """</w>"""
UpperCAmelCase	:	Tuple		     =       """@@ """
def      _A       (		SCREAMING_SNAKE_CASE     :   Optional[int]						):





  """simple docstring"""



  a__	:					Any										=set()
  a__	:					Union[str, Any]										=word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)						)
    a__	:					Any										=char
  return pairs


# Speech2Text2 has no max input length
UpperCAmelCase	:	Any		     =       {"""facebook/s2t-wav2vec2-large-en-de""": 1024}







class 				__lowerCAmelCase       (    UpperCamelCase__):
      _lowercase				:					str						=			VOCAB_FILES_NAMES
      _lowercase				:					Any						=			PRETRAINED_VOCAB_FILES_MAP
      _lowercase				:					List[Any]						=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowercase				:					Optional[int]						=			["""input_ids""", """attention_mask"""]







      def __init__(    self		,      lowerCAmelCase__		,      lowerCAmelCase__="<s>"		,      lowerCAmelCase__="<pad>"		,      lowerCAmelCase__="</s>"		,      lowerCAmelCase__="<unk>"		,      lowerCAmelCase__=False		,      lowerCAmelCase__=None		,      **lowerCAmelCase__		,      )   ->						Union[str, Any]:



        '''simple docstring'''




        super().__init__(
            unk_token=lowerCAmelCase__		,      bos_token=lowerCAmelCase__		,      eos_token=lowerCAmelCase__		,      pad_token=lowerCAmelCase__		,      do_lower_case=lowerCAmelCase__		,      **lowerCAmelCase__		,      )

        a__	:					Any										=do_lower_case

        with open(lowerCAmelCase__		,      encoding="utf-8"							) as vocab_handle:
          a__	:					Tuple										=json.load(lowerCAmelCase__							)
        a__	:					Any										={v: k for k, v in self.encoder.items()}

        if merges_file is None:
          logger.info(F'''No merges files provided. {self.__class__.__name__} can only be used for decoding.'''							)

          a__	:					List[Any]										=None
          a__	:					Tuple										=None
        else:
          with open(lowerCAmelCase__		,      encoding="utf-8"							) as merges_handle:
            a__	:					int										=merges_handle.read().split("\n"							)[:-1]

          a__	:					int										=[tuple(merge.split()[:2]							) for merge in merges]
          a__	:					Optional[int]										=dict(zip(lowerCAmelCase__		,      range(len(lowerCAmelCase__							)							)							)							)
          a__	:					Dict										={}







      @property
      def    _lowercase  (    self							)   ->						int:



        '''simple docstring'''




        return len(self.decoder							)







      def    _lowercase  (    self							)   ->						Dict:



        '''simple docstring'''




        return dict(self.encoder		,      **self.added_tokens_encoder							)







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						int:



        '''simple docstring'''




        a__	:					Any										=tuple(token[:-1]							) + (token[-1] + BPE_TOKEN_MERGES,)
        if token in self.cache:
          return self.cache[token]
        a__	:					Any										=get_pairs(lowerCAmelCase__							)

        if not pairs:
          return token

        while True:
          a__	:					str										=min(lowerCAmelCase__		,      key=lambda lowerCAmelCase__							: self.bpe_ranks.get(lowerCAmelCase__		,      float("inf"							)							)							)
          if bigram not in self.bpe_ranks:
            break
          a__					,							a__	:					List[str]										=bigram
          a__	:					Union[str, Any]										=[]
          a__	:					Optional[int]										=0
          while i < len(lowerCAmelCase__							):
            try:
              a__	:					Optional[int]										=word.index(lowerCAmelCase__		,      lowerCAmelCase__							)
            except ValueError:
              new_word.extend(word[i:]							)
              break
            else:
              new_word.extend(word[i:j]							)
              a__	:					List[Any]										=j

            if word[i] == first and i < len(lowerCAmelCase__							) - 1 and word[i + 1] == second:
              new_word.append(first + second							)
              i += 2
            else:
              new_word.append(word[i]							)
              i += 1
          a__	:					Dict										=tuple(lowerCAmelCase__							)
          a__	:					Dict										=new_word
          if len(lowerCAmelCase__							) == 1:
            break
          else:
            a__	:					Dict										=get_pairs(lowerCAmelCase__							)
        a__	:					str										=" ".join(lowerCAmelCase__							)
        if word == "\n  " + BPE_TOKEN_MERGES:
          a__	:					Any										="\n" + BPE_TOKEN_MERGES

        if word.endswith(lowerCAmelCase__							):
          a__	:					Dict										=word.replace(lowerCAmelCase__		,      ""							)

        a__	:					List[Any]										=word.replace(" "		,      lowerCAmelCase__							)
        a__	:					List[Any]										=word
        return word







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						List[Any]:



        '''simple docstring'''




        if self.bpe_ranks is None:
          raise ValueError(
              "This tokenizer was instantiated without a `merges.txt` file, so"
              " that it can only be used for decoding, not for encoding."
              "Make sure to provide `merges.txt` file at instantiation to enable "
              "encoding."							)

        if self.do_lower_case:
          a__	:					Optional[int]										=text.lower()

        a__	:					str										=text.split()

        a__	:					Union[str, Any]										=[]
        for token in text:
          if token:
            split_tokens.extend(list(self.bpe(lowerCAmelCase__							).split(" "							)							)							)

        return split_tokens







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						int:



        '''simple docstring'''




        return self.encoder.get(lowerCAmelCase__		,      self.encoder.get(self.unk_token							)							)







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						str:



        '''simple docstring'''




        a__	:					List[Any]										=self.decoder.get(lowerCAmelCase__		,      self.unk_token							)
        return result







      def    _lowercase  (    self		,      lowerCAmelCase__							)   ->						str:



        '''simple docstring'''




        a__	:					Dict										=" ".join(lowerCAmelCase__							)

        # make sure @@ tokens are concatenated
        a__	:					Dict										="".join(string.split(lowerCAmelCase__							)							)

        return string







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None							)   ->						Tuple[str]:



        '''simple docstring'''




        if not os.path.isdir(lowerCAmelCase__							):
          logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
          return
        a__	:					Any										=os.path.join(
            lowerCAmelCase__		,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)
        a__	:					Optional[Any]										=os.path.join(
            lowerCAmelCase__		,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]							)

        with open(lowerCAmelCase__		,      "w"		,      encoding="utf-8"							) as f:
          f.write(json.dumps(self.encoder		,      indent=2		,      sort_keys=lowerCAmelCase__		,      ensure_ascii=lowerCAmelCase__							) + "\n"							)

        a__	:					Optional[Any]										=0
        if self.bpe_ranks is None:
          return (vocab_file,)

        with open(lowerCAmelCase__		,      "w"		,      encoding="utf-8"							) as writer:
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,      key=lambda lowerCAmelCase__							: kv[1]							):
            if index != token_index:
              logger.warning(
                  F'''Saving vocabulary to {merges_file}: BPE merge indices are not consecutive.'''
                  " Please check that the tokenizer is not corrupted!"							)
              a__	:					Tuple										=token_index
            writer.write(" ".join(lowerCAmelCase__							) + "\n"							)
            index += 1

        return (vocab_file, merges_file)










from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


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

A      :    Optional[Any]		=					{
    "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/config.json",
    "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/config.json",
    "xlm-roberta-large-finetuned-conll02-dutch": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll02-spanish": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-english": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-german": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"
    ),
}







class 			_lowercase (							lowercase__):


       """simple docstring"""




       A__											=			"xlm-roberta"





       def __init__(   self							:			Union[str, Any]					,      __lowerCamelCase							:			Optional[Any]=30522					,      __lowerCamelCase							:			List[Any]=768					,      __lowerCamelCase							:			Union[str, Any]=12					,      __lowerCamelCase							:			int=12					,      __lowerCamelCase							:			Dict=3072					,      __lowerCamelCase							:			Optional[int]="gelu"					,      __lowerCamelCase							:			Optional[Any]=0.1					,      __lowerCamelCase							:			Tuple=0.1					,      __lowerCamelCase							:			str=512					,      __lowerCamelCase							:			Optional[Any]=2					,      __lowerCamelCase							:			Dict=0.0_2					,      __lowerCamelCase							:			List[str]=1E-1_2					,      __lowerCamelCase							:			Optional[int]=1					,      __lowerCamelCase							:			Union[str, Any]=0					,      __lowerCamelCase							:			Optional[int]=2					,      __lowerCamelCase							:			Dict="absolute"					,      __lowerCamelCase							:			Optional[Any]=True					,      __lowerCamelCase							:			Tuple=None					,      **__lowerCamelCase							:			int					,      ):


             '''simple docstring'''



             super().__init__(pad_token_id=__lowerCamelCase					,      bos_token_id=__lowerCamelCase					,      eos_token_id=__lowerCamelCase					,      **__lowerCamelCase       )

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







class 			_lowercase (							lowercase__):


       """simple docstring"""




       @property
       def 						lowerCAmelCase     (   self							:			Union[str, Any]       ):


             '''simple docstring'''



             if self.task == "multiple-choice":
                   lowerCamelCase__		:				List[str]    =  {0: "batch", 1: "choice", 2: "sequence"}
             else:
                   lowerCamelCase__		:				Any    =  {0: "batch", 1: "sequence"}
             return OrderedDict(
                 [
                     ("input_ids", dynamic_axis),
                     ("attention_mask", dynamic_axis),
                 ]       )


