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

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


lowerCamelCase_  :	Dict 				=					logging.get_logger(__name__)


lowerCamelCase_  :	Dict 				=					{
    """vocab_file""": """vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
    """merges_file""": """merges.txt""",
}

lowerCamelCase_  :	List[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"""
        ),
    },
}

lowerCamelCase_  :	Dict 				=					"""</w>"""
lowerCamelCase_  :	List[Any] 				=					"""@@ """







def     A__   (  lowerCamelCase  )					->		Optional[int]:
				UpperCamelCase_:							Union[str, Any]		=  set()
				UpperCamelCase_:							Optional[Any]		=  word[0]
				for char in word[1:]:
								pairs.add((prev_char, char)  )
								UpperCamelCase_:							Dict		=  char
				return pairs


# Speech2Text2 has no max input length
lowerCamelCase_  :	Tuple 				=					{"""facebook/s2t-wav2vec2-large-en-de""": 10_24}





class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  Any    =	VOCAB_FILES_NAMES
			__UpperCamelCase :  int    =	PRETRAINED_VOCAB_FILES_MAP
			__UpperCamelCase :  Optional[Any]    =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__UpperCamelCase :  Dict    =	["""input_ids""", """attention_mask"""]

			def __init__(    self	:    Any  ,		snake_case_	:    Optional[int]  ,		snake_case_	:    Any="<s>"  ,		snake_case_	:    Union[str, Any]="<pad>"  ,		snake_case_	:    List[str]="</s>"  ,		snake_case_	:    List[Any]="<unk>"  ,		snake_case_	:    Any=False  ,		snake_case_	:    int=None  ,		**snake_case_	:    Union[str, 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_:							str		=  do_lower_case

							with open(snake_case_  ,		encoding="""utf-8""" ) as vocab_handle:
											UpperCamelCase_:							Dict		=  json.load(snake_case_ )
							UpperCamelCase_:							int		=  {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_:							Dict		=  None
											UpperCamelCase_:							Optional[int]		=  None
							else:
											with open(snake_case_  ,		encoding="""utf-8""" ) as merges_handle:
															UpperCamelCase_:							Tuple		=  merges_handle.read().split("""\n""" )[:-1]

											UpperCamelCase_:							str		=  [tuple(merge.split()[:2] ) for merge in merges]
											UpperCamelCase_:							Any		=  dict(zip(snake_case_  ,		range(len(snake_case_ ) ) ) )
											UpperCamelCase_:							int		=  {}

			@property
			def  lowerCAmelCase__		(    self	:    Any ):
							return len(self.decoder )

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

			def  lowerCAmelCase__		(    self	:    List[str]  ,		snake_case_	:    Any ):
							UpperCamelCase_:							List[str]		=  tuple(token[:-1] ) + (token[-1] + BPE_TOKEN_MERGES,)
							if token in self.cache:
											return self.cache[token]
							UpperCamelCase_:							str		=  get_pairs(snake_case_ )

							if not pairs:
											return token

							while True:
											UpperCamelCase_:							int		=  min(snake_case_  ,		key=lambda snake_case_ : self.bpe_ranks.get(snake_case_  ,		float("""inf""" ) ) )
											if bigram not in self.bpe_ranks:
															break
											UpperCamelCase_,				UpperCamelCase_:							Tuple		=  bigram
											UpperCamelCase_:							Dict		=  []
											UpperCamelCase_:							Any		=  0
											while i < len(snake_case_ ):
															try:
																			UpperCamelCase_:							Tuple		=  word.index(snake_case_  ,		snake_case_ )
															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(snake_case_ ) - 1 and word[i + 1] == second:
																			new_word.append(first + second )
																			i += 2
															else:
																			new_word.append(word[i] )
																			i += 1
											UpperCamelCase_:							Dict		=  tuple(snake_case_ )
											UpperCamelCase_:							int		=  new_word
											if len(snake_case_ ) == 1:
															break
											else:
															UpperCamelCase_:							List[Any]		=  get_pairs(snake_case_ )
							UpperCamelCase_:							Any		=  """ """.join(snake_case_ )
							if word == "\n  " + BPE_TOKEN_MERGES:
											UpperCamelCase_:							Dict		=  """\n""" + BPE_TOKEN_MERGES

							if word.endswith(snake_case_ ):
											UpperCamelCase_:							List[Any]		=  word.replace(snake_case_  ,		"""""" )

							UpperCamelCase_:							Any		=  word.replace(""" """  ,		snake_case_ )
							UpperCamelCase_:							List[Any]		=  word
							return word

			def  lowerCAmelCase__		(    self	:    Tuple  ,		snake_case_	:    Optional[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:
											UpperCamelCase_:							Tuple		=  text.lower()

							UpperCamelCase_:							Any		=  text.split()

							UpperCamelCase_:							Any		=  []
							for token in text:
											if token:
															split_tokens.extend(list(self.bpe(snake_case_ ).split(""" """ ) ) )

							return split_tokens

			def  lowerCAmelCase__		(    self	:    str  ,		snake_case_	:    str ):
							return self.encoder.get(snake_case_  ,		self.encoder.get(self.unk_token ) )

			def  lowerCAmelCase__		(    self	:    Any  ,		snake_case_	:    int ):
							UpperCamelCase_:							Optional[int]		=  self.decoder.get(snake_case_  ,		self.unk_token )
							return result

			def  lowerCAmelCase__		(    self	:    int  ,		snake_case_	:    List[str] ):
							UpperCamelCase_:							str		=  """ """.join(snake_case_ )

							# make sure @@ tokens are concatenated
							UpperCamelCase_:							List[str]		=  """""".join(string.split(snake_case_ ) )

							return string




			def  lowerCAmelCase__		(    self	:    int  ,		snake_case_	:    str  ,		snake_case_	:    Optional[str] = None ):
							if not os.path.isdir(snake_case_ ):
											logger.error(f'''Vocabulary path ({save_directory}) should be a directory''' )
											return
							UpperCamelCase_:							int		=  os.path.join(
							    snake_case_  ,		(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )
							UpperCamelCase_:							Optional[int]		=  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_:							Optional[Any]		=  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 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[Any]		=  token_index
															writer.write(""" """.join(snake_case_ ) + """\n""" )
															index += 1

							return (vocab_file, merges_file)








from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_  :	Optional[int] 				=					logging.get_logger(__name__)

lowerCamelCase_  :	Dict 				=					{
    """studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json""",
    """studio-ousia/luke-large""": """https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json""",
}

class     _UpperCamelCase			(   _A					):






			'''simple docstring'''

			__UpperCamelCase :  Optional[int]    =	"""luke"""

			def __init__(    self	:    Tuple  ,		snake_case_	:    List[Any]=5_0267  ,		snake_case_	:    Any=50_0000  ,		snake_case_	:    str=768  ,		snake_case_	:    int=256  ,		snake_case_	:    str=12  ,		snake_case_	:    int=12  ,		snake_case_	:    Dict=3072  ,		snake_case_	:    Optional[Any]="gelu"  ,		snake_case_	:    Dict=0.1  ,		snake_case_	:    List[str]=0.1  ,		snake_case_	:    int=512  ,		snake_case_	:    Dict=2  ,		snake_case_	:    List[Any]=0.02  ,		snake_case_	:    int=1e-12  ,		snake_case_	:    Union[str, Any]=True  ,		snake_case_	:    Union[str, Any]=None  ,		snake_case_	:    Dict=1  ,		snake_case_	:    Optional[int]=0  ,		snake_case_	:    List[str]=2  ,		**snake_case_	:    Union[str, Any]  ,		):
							super().__init__(pad_token_id=snake_case_  ,		bos_token_id=snake_case_  ,		eos_token_id=snake_case_  ,		**snake_case_ )

							UpperCamelCase_:							Dict		=  vocab_size
							UpperCamelCase_:							Tuple		=  entity_vocab_size
							UpperCamelCase_:							Optional[int]		=  hidden_size
							UpperCamelCase_:							Any		=  entity_emb_size
							UpperCamelCase_:							str		=  num_hidden_layers
							UpperCamelCase_:							Union[str, Any]		=  num_attention_heads
							UpperCamelCase_:							Dict		=  hidden_act
							UpperCamelCase_:							Dict		=  intermediate_size
							UpperCamelCase_:							str		=  hidden_dropout_prob
							UpperCamelCase_:							List[str]		=  attention_probs_dropout_prob
							UpperCamelCase_:							int		=  max_position_embeddings
							UpperCamelCase_:							int		=  type_vocab_size
							UpperCamelCase_:							List[Any]		=  initializer_range
							UpperCamelCase_:							Union[str, Any]		=  layer_norm_eps
							UpperCamelCase_:							Tuple		=  use_entity_aware_attention
							UpperCamelCase_:							int		=  classifier_dropout






