'''simple docstring'''





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

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


SCREAMING_SNAKE_CASE_:					str  =logging.get_logger(__name__)


SCREAMING_SNAKE_CASE_:					int  ={
    'vocab_file': 'vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
    'merges_file': 'merges.txt',
}

SCREAMING_SNAKE_CASE_:					Tuple  ={
    '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'
        ),
    },
}

SCREAMING_SNAKE_CASE_:					Union[str, Any]  ='</w>'
SCREAMING_SNAKE_CASE_:					Any  ='@@ '





def      lowerCAmelCase_    ( snake_case_	:			List[Any]      )   ->				List[Any]:


     '''simple docstring'''




     UpperCAmelCase_	   =       set()
     UpperCAmelCase_	   =       word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)      )
          UpperCAmelCase_	   =       char
     return pairs


# Speech2Text2 has no max input length
SCREAMING_SNAKE_CASE_:					Optional[int]  ={'facebook/s2t-wav2vec2-large-en-de': 10_24}






class 	__A				(			__SCREAMING_SNAKE_CASE     ):
    a__	:						Optional[Any]	       =  VOCAB_FILES_NAMES
    a__	:						List[Any]	       =  PRETRAINED_VOCAB_FILES_MAP
    a__	:						Any	       =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a__	:						int	       =  ["input_ids", "attention_mask"]



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

         UpperCAmelCase_	   =       do_lower_case

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

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

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



    @property
    def  _lowercase						(self   :   List[str]			):
         return len(self.decoder			)



    def  _lowercase						(self   :   Any			):
         return dict(self.encoder       ,      **self.added_tokens_encoder			)



    def  _lowercase						(self   :   Any       ,      __a   :   Dict			):
         UpperCAmelCase_	   =       tuple(token[:-1]			) + (token[-1] + BPE_TOKEN_MERGES,)
         if token in self.cache:
              return self.cache[token]
         UpperCAmelCase_	   =       get_pairs(_snake_case			)

         if not pairs:
              return token

         while True:
              UpperCAmelCase_	   =       min(_snake_case       ,      key=lambda __a			: self.bpe_ranks.get(_snake_case       ,      float("inf"			)			)			)
              if bigram not in self.bpe_ranks:
                   break
              UpperCAmelCase_	   =       bigram
              UpperCAmelCase_	   =       []
              UpperCAmelCase_	   =       0
              while i < len(_snake_case			):
                   try:
                        UpperCAmelCase_	   =       word.index(_snake_case       ,      _snake_case			)
                   except ValueError:
                        new_word.extend(word[i:]			)
                        break
                   else:
                        new_word.extend(word[i:j]			)
                        UpperCAmelCase_	   =       j

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

         if word.endswith(_snake_case			):
              UpperCAmelCase_	   =       word.replace(_snake_case       ,      ""			)

         UpperCAmelCase_	   =       word.replace(" "       ,      _snake_case			)
         UpperCAmelCase_	   =       word
         return word



    def  _lowercase						(self   :   Optional[Any]       ,      __a   :   Tuple			):

         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:
              UpperCAmelCase_	   =       text.lower()

         UpperCAmelCase_	   =       text.split()

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

         return split_tokens



    def  _lowercase						(self   :   Optional[int]       ,      __a   :   Tuple			):
         return self.encoder.get(_snake_case       ,      self.encoder.get(self.unk_token			)			)



    def  _lowercase						(self   :   Tuple       ,      __a   :   Any			):
         UpperCAmelCase_	   =       self.decoder.get(_snake_case       ,      self.unk_token			)
         return result



    def  _lowercase						(self   :   List[Any]       ,      __a   :   str			):
         UpperCAmelCase_	   =       " ".join(_snake_case			)

         # make sure @@ tokens are concatenated
         UpperCAmelCase_	   =       "".join(string.split(_snake_case			)			)

         return string






    def  _lowercase						(self   :   str       ,      __a   :   Dict       ,      __a   :   Tuple = None			):
         if not os.path.isdir(_snake_case			):
              logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""			)
              return
         UpperCAmelCase_	   =       os.path.join(
             _snake_case       ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]			)
         UpperCAmelCase_	   =       os.path.join(
             _snake_case       ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]			)

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

         UpperCAmelCase_	   =       0
         if self.bpe_ranks is None:
              return (vocab_file,)

         with open(_snake_case       ,      "w"       ,      encoding="utf-8"			) as writer:
              for bpe_tokens, token_index in sorted(self.bpe_ranks.items()       ,      key=lambda __a			: 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!"			)
                        UpperCAmelCase_	   =       token_index
                   writer.write(" ".join(_snake_case			) + "\n"			)
                   index += 1

         return (vocab_file, merges_file)





'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


SCREAMING_SNAKE_CASE_:					int  ={
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					List[str]  =['MaskFormerFeatureExtractor']
    SCREAMING_SNAKE_CASE_:					Union[str, Any]  =['MaskFormerImageProcessor']


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_:					Dict  =[
        'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
        'MaskFormerForInstanceSegmentation',
        'MaskFormerModel',
        'MaskFormerPreTrainedModel',
    ]
    SCREAMING_SNAKE_CASE_:					List[str]  =[
        'MaskFormerSwinBackbone',
        'MaskFormerSwinModel',
        'MaskFormerSwinPreTrainedModel',
    ]

if TYPE_CHECKING:
    from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
    from .configuration_maskformer_swin import MaskFormerSwinConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_maskformer import MaskFormerFeatureExtractor
        from .image_processing_maskformer import MaskFormerImageProcessor
    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_maskformer import (
            MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            MaskFormerForInstanceSegmentation,
            MaskFormerModel,
            MaskFormerPreTrainedModel,
        )
        from .modeling_maskformer_swin import (
            MaskFormerSwinBackbone,
            MaskFormerSwinModel,
            MaskFormerSwinPreTrainedModel,
        )


else:
    import sys

    SCREAMING_SNAKE_CASE_:					Dict  =_LazyModule(__name__, globals()['__file__'], _import_structure)




