





"""simple docstring"""







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

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


a__      :	str       				=      logging.get_logger(__name__)


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

a__      :	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'
        ),
    },
}

a__      :	List[str]       				=      '</w>'
a__      :	Any       				=      '@@ '







def     A__			(       __lowerCamelCase					):





  """simple docstring"""
  _lowerCAmelCase	      =					set()
  _lowerCAmelCase	      =					word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)					)
    _lowerCAmelCase	      =					char
  return pairs


# Speech2Text2 has no max input length
a__      :	List[Any]       				=      {'facebook/s2t-wav2vec2-large-en-de': 1024}




class __magic_name__   (       A__		):
       UpperCamelCase    :						Optional[int]      =	VOCAB_FILES_NAMES
       UpperCamelCase    :						List[str]      =	PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase    :						Any      =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       UpperCamelCase    :						Any      =	["input_ids", "attention_mask"]
       def __init__(     self   ,  __magic_name__   ,  __magic_name__="<s>"   ,  __magic_name__="<pad>"   ,  __magic_name__="</s>"   ,  __magic_name__="<unk>"   ,  __magic_name__=False   ,  __magic_name__=None   ,  **__magic_name__   ,  ):





         """simple docstring"""


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

         _lowerCAmelCase	      =					do_lower_case

         with open(__magic_name__   ,  encoding='utf-8'	) as vocab_handle:
           _lowerCAmelCase	      =					json.load(__magic_name__	)
         _lowerCAmelCase	      =					{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.'''	)

           _lowerCAmelCase	      =					None
           _lowerCAmelCase	      =					None
         else:
           with open(__magic_name__   ,  encoding='utf-8'	) as merges_handle:
             _lowerCAmelCase	      =					merges_handle.read().split('\n'	)[:-1]

           _lowerCAmelCase	      =					[tuple(merge.split()[:2]	) for merge in merges]
           _lowerCAmelCase	      =					dict(zip(__magic_name__   ,  range(len(__magic_name__	)	)	)	)
           _lowerCAmelCase	      =					{}
       @property
       def 		_lowerCamelCase   (     self	):





         """simple docstring"""


         return len(self.decoder	)
       def 		_lowerCamelCase   (     self	):





         """simple docstring"""


         return dict(self.encoder   ,  **self.added_tokens_encoder	)
       def 		_lowerCamelCase   (     self   ,  __magic_name__	):





         """simple docstring"""


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

         if not pairs:
           return token

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

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

         if word.endswith(__magic_name__	):
           _lowerCAmelCase	      =					word.replace(__magic_name__   ,  ''	)

         _lowerCAmelCase	      =					word.replace(' '   ,  __magic_name__	)
         _lowerCAmelCase	      =					word
         return word
       def 		_lowerCamelCase   (     self   ,  __magic_name__	):





         """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:
           _lowerCAmelCase	      =					text.lower()

         _lowerCAmelCase	      =					text.split()

         _lowerCAmelCase	      =					[]
         for token in text:
           if token:
             split_tokens.extend(list(self.bpe(__magic_name__	).split(' '	)	)	)

         return split_tokens
       def 		_lowerCamelCase   (     self   ,  __magic_name__	):





         """simple docstring"""


         return self.encoder.get(__magic_name__   ,  self.encoder.get(self.unk_token	)	)
       def 		_lowerCamelCase   (     self   ,  __magic_name__	):





         """simple docstring"""


         _lowerCAmelCase	      =					self.decoder.get(__magic_name__   ,  self.unk_token	)
         return result
       def 		_lowerCamelCase   (     self   ,  __magic_name__	):





         """simple docstring"""


         _lowerCAmelCase	      =					' '.join(__magic_name__	)

         # make sure @@ tokens are concatenated
         _lowerCAmelCase	      =					''.join(string.split(__magic_name__	)	)

         return string
       def 		_lowerCamelCase   (     self   ,  __magic_name__   ,  __magic_name__ = None	):





         """simple docstring"""


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

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

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

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

         return (vocab_file, merges_file)











import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING


A__      :     Tuple       =					logging.get_logger(__name__)
class  _UpperCAmelCase   (			A__      ):

				"""simple docstring"""




				lowercase__											=			"""upernet"""




				def __init__(	self		:       Dict,    lowerCamelCase		:       Union[str, Any]=None,    lowerCamelCase		:       str=512,    lowerCamelCase		:       Optional[Any]=0.02,    lowerCamelCase		:       Optional[Any]=[1, 2, 3, 6],    lowerCamelCase		:       Optional[int]=True,    lowerCamelCase		:       Tuple=0.4,    lowerCamelCase		:       Optional[int]=384,    lowerCamelCase		:       Optional[int]=256,    lowerCamelCase		:       Dict=1,    lowerCamelCase		:       str=False,    lowerCamelCase		:       List[str]=255,    **lowerCamelCase		:       List[Any],    ):

								'''simple docstring'''
								super().__init__(**lowerCamelCase    )

								if backbone_config is None:
												logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''    )
												lowercase__  					=     CONFIG_MAPPING['''resnet'''](out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']    )
								elif isinstance(lowerCamelCase,    lowerCamelCase    ):
												lowercase__  					=     backbone_config.get('''model_type'''    )
												lowercase__  					=     CONFIG_MAPPING[backbone_model_type]
												lowercase__  					=     config_class.from_dict(lowerCamelCase    )

								lowercase__  					=     backbone_config
								lowercase__  					=     hidden_size
								lowercase__  					=     initializer_range
								lowercase__  					=     pool_scales
								lowercase__  					=     use_auxiliary_head
								lowercase__  					=     auxiliary_loss_weight
								lowercase__  					=     auxiliary_in_channels
								lowercase__  					=     auxiliary_channels
								lowercase__  					=     auxiliary_num_convs
								lowercase__  					=     auxiliary_concat_input
								lowercase__  					=     loss_ignore_index




				def 							lowercase__  (	self		:       str    ):

								'''simple docstring'''
								lowercase__  					=     copy.deepcopy(self.__dict__    )
								lowercase__  					=     self.backbone_config.to_dict()
								lowercase__  					=     self.__class__.model_type
								return output




