

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

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


__A			:					Any						=			logging.get_logger(__name__)


__A			:					Optional[Any]						=			{
    'vocab_file': 'vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
    'merges_file': 'merges.txt',
}

__A			:					Optional[int]						=			{
    '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'
        ),
    },
}

__A			:					Optional[int]						=			'</w>'
__A			:					List[Any]						=			'@@ '





def 	__a     (      A__			:  Optional[int]       ):
    SCREAMING_SNAKE_CASE										=   set()
    SCREAMING_SNAKE_CASE										=   word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)       )
        SCREAMING_SNAKE_CASE										=   char
    return pairs


# Speech2Text2 has no max input length
__A			:					Any						=			{'facebook/s2t-wav2vec2-large-en-de': 1_0_2_4}





class 			_SCREAMING_SNAKE_CASE (   __snake_case		):







   '''simple docstring'''




   lowerCamelCase__				=      VOCAB_FILES_NAMES
   lowerCamelCase__				=      PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase__				=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCamelCase__				=      ["input_ids", "attention_mask"]





   def __init__(       self					:			Optional[int]     , __lowerCamelCase					:			Dict     , __lowerCamelCase					:			Optional[int]="<s>"     , __lowerCamelCase					:			List[Any]="<pad>"     , __lowerCamelCase					:			Optional[int]="</s>"     , __lowerCamelCase					:			Tuple="<unk>"     , __lowerCamelCase					:			Optional[Any]=False     , __lowerCamelCase					:			List[str]=None     , **__lowerCamelCase					:			Optional[Any]     , ):
       super().__init__(
           unk_token=__lowerCamelCase     , bos_token=__lowerCamelCase     , eos_token=__lowerCamelCase     , pad_token=__lowerCamelCase     , do_lower_case=__lowerCamelCase     , **__lowerCamelCase     , )

       SCREAMING_SNAKE_CASE										=   do_lower_case

       with open(__lowerCamelCase     , encoding="utf-8"			) as vocab_handle:
           SCREAMING_SNAKE_CASE										=   json.load(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   {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."			)

           SCREAMING_SNAKE_CASE										=   None
           SCREAMING_SNAKE_CASE										=   None
       else:
           with open(__lowerCamelCase     , encoding="utf-8"			) as merges_handle:
               SCREAMING_SNAKE_CASE										=   merges_handle.read().split("\n"			)[:-1]

           SCREAMING_SNAKE_CASE										=   [tuple(merge.split()[:2]			) for merge in merges]
           SCREAMING_SNAKE_CASE										=   dict(zip(__lowerCamelCase     , range(len(__lowerCamelCase			)			)			)			)
           SCREAMING_SNAKE_CASE										=   {}





   @property
   def      _snake_case		(       self					:			str			):
       return len(self.decoder			)





   def      _snake_case		(       self					:			Optional[Any]			):
       return dict(self.encoder     , **self.added_tokens_encoder			)





   def      _snake_case		(       self					:			List[Any]     , __lowerCamelCase					:			Optional[int]			):
       SCREAMING_SNAKE_CASE										=   tuple(token[:-1]			) + (token[-1] + BPE_TOKEN_MERGES,)
       if token in self.cache:
           return self.cache[token]
       SCREAMING_SNAKE_CASE										=   get_pairs(__lowerCamelCase			)

       if not pairs:
           return token

       while True:
           SCREAMING_SNAKE_CASE										=   min(__lowerCamelCase     , key=lambda __lowerCamelCase			: self.bpe_ranks.get(__lowerCamelCase     , float("inf"			)			)			)
           if bigram not in self.bpe_ranks:
               break
           SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   bigram
           SCREAMING_SNAKE_CASE										=   []
           SCREAMING_SNAKE_CASE										=   0
           while i < len(__lowerCamelCase			):
               try:
                   SCREAMING_SNAKE_CASE										=   word.index(__lowerCamelCase     , __lowerCamelCase			)
               except ValueError:
                   new_word.extend(word[i:]			)
                   break
               else:
                   new_word.extend(word[i:j]			)
                   SCREAMING_SNAKE_CASE										=   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
           SCREAMING_SNAKE_CASE										=   tuple(__lowerCamelCase			)
           SCREAMING_SNAKE_CASE										=   new_word
           if len(__lowerCamelCase			) == 1:
               break
           else:
               SCREAMING_SNAKE_CASE										=   get_pairs(__lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   " ".join(__lowerCamelCase			)
       if word == "\n  " + BPE_TOKEN_MERGES:
           SCREAMING_SNAKE_CASE										=   "\n" + BPE_TOKEN_MERGES

       if word.endswith(__lowerCamelCase			):
           SCREAMING_SNAKE_CASE										=   word.replace(__lowerCamelCase     , ""			)

       SCREAMING_SNAKE_CASE										=   word.replace(" "     , __lowerCamelCase			)
       SCREAMING_SNAKE_CASE										=   word
       return word





   def      _snake_case		(       self					:			Union[str, Any]     , __lowerCamelCase					:			Any			):

       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:
           SCREAMING_SNAKE_CASE										=   text.lower()

       SCREAMING_SNAKE_CASE										=   text.split()

       SCREAMING_SNAKE_CASE										=   []
       for token in text:
           if token:
               split_tokens.extend(list(self.bpe(__lowerCamelCase			).split(" "			)			)			)

       return split_tokens





   def      _snake_case		(       self					:			Union[str, Any]     , __lowerCamelCase					:			str			):
       return self.encoder.get(__lowerCamelCase     , self.encoder.get(self.unk_token			)			)





   def      _snake_case		(       self					:			List[Any]     , __lowerCamelCase					:			int			):
       SCREAMING_SNAKE_CASE										=   self.decoder.get(__lowerCamelCase     , self.unk_token			)
       return result





   def      _snake_case		(       self					:			List[str]     , __lowerCamelCase					:			List[str]			):
       SCREAMING_SNAKE_CASE										=   " ".join(__lowerCamelCase			)

       # make sure @@ tokens are concatenated
       SCREAMING_SNAKE_CASE										=   "".join(string.split(__lowerCamelCase			)			)

       return string





   def      _snake_case		(       self					:			Optional[int]     , __lowerCamelCase					:			str     , __lowerCamelCase					:			Optional[str] = None			):
       if not os.path.isdir(__lowerCamelCase			):
           logger.error(f"Vocabulary path ({save_directory}) should be a directory"			)
           return
       SCREAMING_SNAKE_CASE										=   os.path.join(
           __lowerCamelCase     , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]			)
       SCREAMING_SNAKE_CASE										=   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"			)

       SCREAMING_SNAKE_CASE										=   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!"			)
                   SCREAMING_SNAKE_CASE										=   token_index
               writer.write(" ".join(__lowerCamelCase			) + "\n"			)
               index += 1

       return (vocab_file, merges_file)


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A			:					Dict						=			{
    'configuration_bigbird_pegasus': [
        'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BigBirdPegasusConfig',
        'BigBirdPegasusOnnxConfig',
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __A			:					int						=			[
        'BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST',
        'BigBirdPegasusForCausalLM',
        'BigBirdPegasusForConditionalGeneration',
        'BigBirdPegasusForQuestionAnswering',
        'BigBirdPegasusForSequenceClassification',
        'BigBirdPegasusModel',
        'BigBirdPegasusPreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
        BigBirdPegasusConfig,
        BigBirdPegasusOnnxConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_bigbird_pegasus import (
            BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
            BigBirdPegasusForCausalLM,
            BigBirdPegasusForConditionalGeneration,
            BigBirdPegasusForQuestionAnswering,
            BigBirdPegasusForSequenceClassification,
            BigBirdPegasusModel,
            BigBirdPegasusPreTrainedModel,
        )


else:
    import sys

    __A			:					List[Any]						=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)