



"""simple docstring"""






import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


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


_lowercase				:				int   		=		{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all LED models at https://huggingface.co/models?filter=LED
_lowercase				:				str   		=		{
    "vocab_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json",
    },
    "merges_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json",
    },
}

_lowercase				:				str   		=		{
    "allenai/led-base-16384": 1_6_3_8_4,
}






@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def   snake_case__     (	):
			"""simple docstring"""
			lowerCamelCase__	:	Optional[Any]				=(
			    list(range(ord('''!'''			)							,	ord('''~'''			) + 1			)			) + list(range(ord('''¡'''			)							,	ord('''¬'''			) + 1			)			) + list(range(ord('''®'''			)							,	ord('''ÿ'''			) + 1			)			)
			)
			lowerCamelCase__	:	Optional[int]				=bs[:]
			lowerCamelCase__	:	Dict				=0
			for b in range(2**8			):
						if b not in bs:
									bs.append(__lowerCamelCase			)
									cs.append(2**8 + n			)
									n += 1
			lowerCamelCase__	:	str				=[chr(__lowerCamelCase			) for n in cs]
			return dict(zip(__lowerCamelCase							,	__lowerCamelCase			)			)






def   snake_case__     (	__lowerCamelCase       :					int			):
			"""simple docstring"""
			lowerCamelCase__	:	Dict				=set()
			lowerCamelCase__	:	Optional[Any]				=word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)			)
						lowerCamelCase__	:	str				=char
			return pairs

class  __SCREAMING_SNAKE_CASE			(   lowerCAmelCase_     ):


					'''simple docstring'''





					_a         =							VOCAB_FILES_NAMES
					_a         =							PRETRAINED_VOCAB_FILES_MAP
					_a         =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					_a         =							['input_ids', 'attention_mask']



					def __init__( self							:						str,						lowerCamelCase							:						List[Any],						lowerCamelCase							:						int,						lowerCamelCase							:						Optional[Any]="replace",						lowerCamelCase							:						List[str]="<s>",						lowerCamelCase							:						Union[str, Any]="</s>",						lowerCamelCase							:						List[Any]="</s>",						lowerCamelCase							:						Tuple="<s>",						lowerCamelCase							:						int="<unk>",						lowerCamelCase							:						Optional[int]="<pad>",						lowerCamelCase							:						Tuple="<mask>",						lowerCamelCase							:						Tuple=False,						**lowerCamelCase							:						Optional[int],						)->      Optional[Any]:
								lowerCamelCase__	:	Optional[Any]				=AddedToken(lowerCamelCase,						lstrip=lowerCamelCase,						rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,						lowerCamelCase  ) else bos_token
								lowerCamelCase__	:	str				=AddedToken(lowerCamelCase,						lstrip=lowerCamelCase,						rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,						lowerCamelCase  ) else eos_token
								lowerCamelCase__	:	Optional[Any]				=AddedToken(lowerCamelCase,						lstrip=lowerCamelCase,						rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,						lowerCamelCase  ) else sep_token
								lowerCamelCase__	:	Dict				=AddedToken(lowerCamelCase,						lstrip=lowerCamelCase,						rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,						lowerCamelCase  ) else cls_token
								lowerCamelCase__	:	int				=AddedToken(lowerCamelCase,						lstrip=lowerCamelCase,						rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,						lowerCamelCase  ) else unk_token
								lowerCamelCase__	:	List[str]				=AddedToken(lowerCamelCase,						lstrip=lowerCamelCase,						rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,						lowerCamelCase  ) else pad_token

								# Mask token behave like a normal word, i.e. include the space before it
								lowerCamelCase__	:	Any				=AddedToken(lowerCamelCase,						lstrip=lowerCamelCase,						rstrip=lowerCamelCase  ) if isinstance(lowerCamelCase,						lowerCamelCase  ) else mask_token

								super().__init__(
								    errors=lowerCamelCase,						bos_token=lowerCamelCase,						eos_token=lowerCamelCase,						unk_token=lowerCamelCase,						sep_token=lowerCamelCase,						cls_token=lowerCamelCase,						pad_token=lowerCamelCase,						mask_token=lowerCamelCase,						add_prefix_space=lowerCamelCase,						**lowerCamelCase,						)

								with open(lowerCamelCase,						encoding='''utf-8'''  ) as vocab_handle:
											lowerCamelCase__	:	Tuple				=json.load(lowerCamelCase  )
								lowerCamelCase__	:	Optional[int]				={v: k for k, v in self.encoder.items()}
								lowerCamelCase__	:	Tuple				=errors  # how to handle errors in decoding
								lowerCamelCase__	:	Optional[Any]				=bytes_to_unicode()
								lowerCamelCase__	:	Optional[Any]				={v: k for k, v in self.byte_encoder.items()}
								with open(lowerCamelCase,						encoding='''utf-8'''  ) as merges_handle:
											lowerCamelCase__	:	Any				=merges_handle.read().split('''\n'''  )[1:-1]
								lowerCamelCase__	:	Optional[Any]				=[tuple(merge.split()  ) for merge in bpe_merges]
								lowerCamelCase__	:	List[str]				=dict(zip(lowerCamelCase,						range(len(lowerCamelCase  )  )  )  )
								lowerCamelCase__	:	Optional[Any]				={}
								lowerCamelCase__	:	Optional[int]				=add_prefix_space

								# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
								lowerCamelCase__	:	Optional[Any]				=re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''  )



					@property
					# Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
					def 	snake_case ( self							:						str  )->      List[Any]:
								return len(self.encoder  )



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



					def 	snake_case ( self							:						Optional[int],						lowerCamelCase							:						Union[str, Any]  )->      Tuple:
								if token in self.cache:
											return self.cache[token]
								lowerCamelCase__	:	Tuple				=tuple(lowerCamelCase  )
								lowerCamelCase__	:	Optional[Any]				=get_pairs(lowerCamelCase  )

								if not pairs:
											return token

								while True:
											lowerCamelCase__	:	List[Any]				=min(lowerCamelCase,						key=lambda lowerCamelCase  : self.bpe_ranks.get(lowerCamelCase,						float('''inf'''  )  )  )
											if bigram not in self.bpe_ranks:
														break
											lowerCamelCase__	:	List[Any]				=bigram
											lowerCamelCase__	:	Tuple				=[]
											lowerCamelCase__	:	List[str]				=0
											while i < len(lowerCamelCase  ):
														try:
																	lowerCamelCase__	:	str				=word.index(lowerCamelCase,						lowerCamelCase  )
														except ValueError:
																	new_word.extend(word[i:]  )
																	break
														else:
																	new_word.extend(word[i:j]  )
																	lowerCamelCase__	:	str				=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
											lowerCamelCase__	:	Optional[int]				=tuple(lowerCamelCase  )
											lowerCamelCase__	:	int				=new_word
											if len(lowerCamelCase  ) == 1:
														break
											else:
														lowerCamelCase__	:	Dict				=get_pairs(lowerCamelCase  )
								lowerCamelCase__	:	Tuple				=''' '''.join(lowerCamelCase  )
								lowerCamelCase__	:	List[Any]				=word
								return word



					def 	snake_case ( self							:						List[Any],						lowerCamelCase							:						List[str]  )->      List[Any]:
								lowerCamelCase__	:	Tuple				=[]
								for token in re.findall(self.pat,						lowerCamelCase  ):
											lowerCamelCase__	:	str				=''''''.join(
											    self.byte_encoder[b] for b in token.encode('''utf-8'''  )  )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
											bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase  ).split(''' '''  )  )
								return bpe_tokens



					def 	snake_case ( self							:						List[Any],						lowerCamelCase							:						str  )->      str:
								return self.encoder.get(lowerCamelCase,						self.encoder.get(self.unk_token  )  )



					def 	snake_case ( self							:						Optional[Any],						lowerCamelCase							:						Any  )->      Union[str, Any]:
								return self.decoder.get(lowerCamelCase  )



					def 	snake_case ( self							:						Optional[Any],						lowerCamelCase							:						int  )->      List[Any]:
								lowerCamelCase__	:	Dict				=''''''.join(lowerCamelCase  )
								lowerCamelCase__	:	List[str]				=bytearray([self.byte_decoder[c] for c in text]  ).decode('''utf-8''',						errors=self.errors  )
								return text



					def 	snake_case ( self							:						List[Any],						lowerCamelCase							:						str,						lowerCamelCase							:						Optional[str] = None  )->      Tuple[str]:
								if not os.path.isdir(lowerCamelCase  ):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
											return
								lowerCamelCase__	:	Dict				=os.path.join(
								    lowerCamelCase,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )
								lowerCamelCase__	:	List[str]				=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'''  )

								lowerCamelCase__	:	Union[str, Any]				=0
								with open(lowerCamelCase,						'''w''',						encoding='''utf-8'''  ) as writer:
											writer.write('''#version: 0.2\n'''  )
											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 {merge_file}: BPE merge indices are not consecutive.'''
																	    ''' Please check that the tokenizer is not corrupted!'''  )
																	lowerCamelCase__	:	List[Any]				=token_index
														writer.write(''' '''.join(lowerCamelCase  ) + '''\n'''  )
														index += 1

								return vocab_file, merge_file



					def 	snake_case ( self							:						Optional[int],						lowerCamelCase							:						List[int],						lowerCamelCase							:						Optional[List[int]] = None  )->      List[int]:
								if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								lowerCamelCase__	:	Dict				=[self.cls_token_id]
								lowerCamelCase__	:	Any				=[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep



					def 	snake_case ( self							:						Tuple,						lowerCamelCase							:						List[int],						lowerCamelCase							:						Optional[List[int]] = None,						lowerCamelCase							:						bool = False  )->      List[int]:
								if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=lowerCamelCase,						token_ids_a=lowerCamelCase,						already_has_special_tokens=lowerCamelCase  )

								if token_ids_a is None:
											return [1] + ([0] * len(lowerCamelCase  )) + [1]
								return [1] + ([0] * len(lowerCamelCase  )) + [1, 1] + ([0] * len(lowerCamelCase  )) + [1]



					def 	snake_case ( self							:						Dict,						lowerCamelCase							:						List[int],						lowerCamelCase							:						Optional[List[int]] = None  )->      List[int]:
								lowerCamelCase__	:	int				=[self.sep_token_id]
								lowerCamelCase__	:	Optional[int]				=[self.cls_token_id]

								if token_ids_a is None:
											return len(cls + token_ids_a + sep  ) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep  ) * [0]



					def 	snake_case ( self							:						int,						lowerCamelCase							:						Union[str, Any],						lowerCamelCase							:						Optional[Any]=False,						**lowerCamelCase							:						Tuple  )->      List[Any]:
								lowerCamelCase__	:	Union[str, Any]				=kwargs.pop('''add_prefix_space''',						self.add_prefix_space  )
								if (is_split_into_words or add_prefix_space) and (len(lowerCamelCase  ) > 0 and not text[0].isspace()):
											lowerCamelCase__	:	List[Any]				=''' ''' + text
								return (text, kwargs)




					def 	snake_case ( self							:						List[str],						lowerCamelCase							:						Union[Dict[str, EncodedInput], BatchEncoding],						lowerCamelCase							:						Optional[int] = None,						lowerCamelCase							:						PaddingStrategy = PaddingStrategy.DO_NOT_PAD,						lowerCamelCase							:						Optional[int] = None,						lowerCamelCase							:						Optional[bool] = None,						)->      dict:
								lowerCamelCase__	:	str				=super()._pad(
								    encoded_inputs=lowerCamelCase,						max_length=lowerCamelCase,						padding_strategy=lowerCamelCase,						pad_to_multiple_of=lowerCamelCase,						return_attention_mask=lowerCamelCase,						)

								# Load from model defaults
								if return_attention_mask is None:
											lowerCamelCase__	:	Dict				='''attention_mask''' in self.model_input_names

								if return_attention_mask and "global_attention_mask" in encoded_inputs:
											lowerCamelCase__	:	Tuple				=encoded_inputs[self.model_input_names[0]]
											# `global_attention_mask` need to have the same length as other (sequential) inputs.
											lowerCamelCase__	:	Optional[Any]				=len(encoded_inputs['''global_attention_mask''']  ) != len(lowerCamelCase  )

											if needs_to_be_padded:
														lowerCamelCase__	:	Tuple				=len(lowerCamelCase  ) - len(encoded_inputs['''global_attention_mask''']  )

														if self.padding_side == "right":
																	# Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
																	lowerCamelCase__	:	Any				=(
																	    encoded_inputs['''global_attention_mask'''] + [-1] * difference
																	)
														elif self.padding_side == "left":
																	lowerCamelCase__	:	Dict				=[-1] * difference + encoded_inputs[
																	    '''global_attention_mask'''
																	]
														else:
																	raise ValueError('''Invalid padding strategy:''' + str(self.padding_side  )  )

								return encoded_inputs









"""simple docstring"""






from ..utils import DummyObject, requires_backends

class  __SCREAMING_SNAKE_CASE			(   metaclass=lowerCAmelCase_     ):


					'''simple docstring'''





					_a         =							['onnx']



					def __init__( self							:						List[str],						*lowerCamelCase							:						Union[str, Any],						**lowerCamelCase							:						str  )->      Optional[int]:
								requires_backends(self,						['''onnx''']  )



					@classmethod
					def 	snake_case ( cls							:						List[str],						*lowerCamelCase							:						Any,						**lowerCamelCase							:						Union[str, Any]  )->      Optional[int]:
								requires_backends(cls,						['''onnx''']  )




					@classmethod
					def 	snake_case ( cls							:						Union[str, Any],						*lowerCamelCase							:						Tuple,						**lowerCamelCase							:						Tuple  )->      Optional[int]:
								requires_backends(cls,						['''onnx''']  )




