


"""simple docstring"""






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

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


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


UpperCamelCase__				:Union[str, Any]			   =	{
    """vocab_file""": """vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
    """merges_file""": """merges.txt""",
}

UpperCamelCase__				:str			   =	{
    """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__				:Dict			   =	"""@@ """





def 				A_       ( snake_case__		)					->  List[str]:
			_UpperCamelCase					:Union[str, Any]					     =	set()
			_UpperCamelCase					:int					     =	word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)		)
						_UpperCamelCase					:Tuple					     =	char
			return pairs


# Speech2Text2 has no max input length
UpperCamelCase__				:Optional[Any]			   =	{"""facebook/s2t-wav2vec2-large-en-de""": 1_024}






class      A(  snake_case_		):

		"""simple docstring"""





		A    =							VOCAB_FILES_NAMES
		A    =							PRETRAINED_VOCAB_FILES_MAP
		A    =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		A    =							['''input_ids''', '''attention_mask''']
		def __init__( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__="<s>"					,				SCREAMING_SNAKE_CASE__="<pad>"					,				SCREAMING_SNAKE_CASE__="</s>"					,				SCREAMING_SNAKE_CASE__="<unk>"					,				SCREAMING_SNAKE_CASE__=False					,				SCREAMING_SNAKE_CASE__=None					,				**SCREAMING_SNAKE_CASE__					,				)      ->	List[Any]:

					"""simple docstring"""



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

					_UpperCamelCase					:int					     =	do_lower_case

					with open(UpperCamelCase__					,				encoding='''utf-8'''   ) as vocab_handle:
								_UpperCamelCase					:int					     =	json.load(UpperCamelCase__   )
					_UpperCamelCase					:List[str]					     =	{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					:Any					     =	None
								_UpperCamelCase					:Tuple					     =	None
					else:
								with open(UpperCamelCase__					,				encoding='''utf-8'''   ) as merges_handle:
											_UpperCamelCase					:Union[str, Any]					     =	merges_handle.read().split('''\n'''   )[:-1]

								_UpperCamelCase					:List[str]					     =	[tuple(merge.split()[:2]   ) for merge in merges]
								_UpperCamelCase					:List[str]					     =	dict(zip(UpperCamelCase__					,				range(len(UpperCamelCase__   )   )   )   )
								_UpperCamelCase					:Dict					     =	{}
		@property
		def   _UpperCamelCase( self   )      ->	int:

					"""simple docstring"""



					return len(self.decoder   )
		def   _UpperCamelCase( self   )      ->	Dict:

					"""simple docstring"""



					return dict(self.encoder					,				**self.added_tokens_encoder   )
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	List[Any]:

					"""simple docstring"""



					_UpperCamelCase					:List[Any]					     =	tuple(token[:-1]   ) + (token[-1] + BPE_TOKEN_MERGES,)
					if token in self.cache:
								return self.cache[token]
					_UpperCamelCase					:List[str]					     =	get_pairs(UpperCamelCase__   )

					if not pairs:
								return token

					while True:
								_UpperCamelCase					:Dict					     =	min(UpperCamelCase__					,				key=lambda SCREAMING_SNAKE_CASE__   : self.bpe_ranks.get(UpperCamelCase__					,				float('''inf'''   )   )   )
								if bigram not in self.bpe_ranks:
											break
								_UpperCamelCase					:str					     =	bigram
								_UpperCamelCase					:Tuple					     =	[]
								_UpperCamelCase					:Optional[int]					     =	0
								while i < len(UpperCamelCase__   ):
											try:
														_UpperCamelCase					:Tuple					     =	word.index(UpperCamelCase__					,				UpperCamelCase__   )
											except ValueError:
														new_word.extend(word[i:]   )
														break
											else:
														new_word.extend(word[i:j]   )
														_UpperCamelCase					:str					     =	j

											if word[i] == first and i < len(UpperCamelCase__   ) - 1 and word[i + 1] == second:
														new_word.append(first + second   )
														i += 2
											else:
														new_word.append(word[i]   )
														i += 1
								_UpperCamelCase					:Any					     =	tuple(UpperCamelCase__   )
								_UpperCamelCase					:List[Any]					     =	new_word
								if len(UpperCamelCase__   ) == 1:
											break
								else:
											_UpperCamelCase					:Optional[int]					     =	get_pairs(UpperCamelCase__   )
					_UpperCamelCase					:Optional[int]					     =	" ".join(UpperCamelCase__   )
					if word == "\n  " + BPE_TOKEN_MERGES:
								_UpperCamelCase					:List[Any]					     =	"\n" + BPE_TOKEN_MERGES

					if word.endswith(UpperCamelCase__   ):
								_UpperCamelCase					:str					     =	word.replace(UpperCamelCase__					,				''''''   )

					_UpperCamelCase					:Dict					     =	word.replace(''' '''					,				UpperCamelCase__   )
					_UpperCamelCase					:List[str]					     =	word
					return word
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	int:

					"""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:
								_UpperCamelCase					:int					     =	text.lower()

					_UpperCamelCase					:Union[str, Any]					     =	text.split()

					_UpperCamelCase					:List[Any]					     =	[]
					for token in text:
								if token:
											split_tokens.extend(list(self.bpe(UpperCamelCase__   ).split(''' '''   )   )   )

					return split_tokens
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	int:

					"""simple docstring"""



					return self.encoder.get(UpperCamelCase__					,				self.encoder.get(self.unk_token   )   )
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	str:

					"""simple docstring"""



					_UpperCamelCase					:Union[str, Any]					     =	self.decoder.get(UpperCamelCase__					,				self.unk_token   )
					return result
		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__   )      ->	str:

					"""simple docstring"""



					_UpperCamelCase					:Tuple					     =	" ".join(UpperCamelCase__   )

					# make sure @@ tokens are concatenated
					_UpperCamelCase					:Optional[Any]					     =	"".join(string.split(UpperCamelCase__   )   )

					return string





		def   _UpperCamelCase( self					,				SCREAMING_SNAKE_CASE__					,				SCREAMING_SNAKE_CASE__ = None   )      ->	Tuple[str]:

					"""simple docstring"""



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

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

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

					with open(UpperCamelCase__					,				'''w'''					,				encoding='''utf-8'''   ) as writer:
								for bpe_tokens, token_index in sorted(self.bpe_ranks.items()					,				key=lambda SCREAMING_SNAKE_CASE__   : 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					:Optional[int]					     =	token_index
											writer.write(''' '''.join(UpperCamelCase__   ) + '''\n'''   )
											index += 1

					return (vocab_file, merges_file)





"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case       =       {
    """configuration_bigbird_pegasus""": [
        """BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BigBirdPegasusConfig""",
        """BigBirdPegasusOnnxConfig""",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case       =       [
      """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

  __snake_case       =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





