


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


_snake_case					:		str      =    logging.get_logger(__name__)


_snake_case					:		Optional[Any]      =    {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all LED models at https://huggingface.co/models?filter=LED
_snake_case					:		int      =    {
    "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",
    },
}

_snake_case					:		int      =    {
    "allenai/led-base-16384": 16_384,
}







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







def     lowerCAmelCase_					( __lowerCamelCase     ):
							__snake_case		:      str										=       set()
							__snake_case		:      Any										=       word[0]
							for char in word[1:]:
														pairs.add((prev_char, char)     )
														__snake_case		:      List[str]										=       char
							return pairs

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							str					  =  VOCAB_FILES_NAMES
							__UpperCAmelCase   :							List[Any]					  =  PRETRAINED_VOCAB_FILES_MAP
							__UpperCAmelCase   :							int					  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__UpperCAmelCase   :							List[str]					  =  ["input_ids", "attention_mask"]

							def __init__(							self	:  Optional[Any]   ,     lowerCamelCase	:  List[Any]   ,     lowerCamelCase	:  Dict   ,     lowerCamelCase	:  Dict="replace"   ,     lowerCamelCase	:  List[str]="<s>"   ,     lowerCamelCase	:  Any="</s>"   ,     lowerCamelCase	:  Union[str, Any]="</s>"   ,     lowerCamelCase	:  Union[str, Any]="<s>"   ,     lowerCamelCase	:  str="<unk>"   ,     lowerCamelCase	:  Any="<pad>"   ,     lowerCamelCase	:  Optional[int]="<mask>"   ,     lowerCamelCase	:  List[Any]=False   ,     **lowerCamelCase	:  str   ,     )     ->   Tuple:
														__snake_case		:      Tuple										=       AddedToken(lowerCamelCase   ,     lstrip=lowerCamelCase   ,     rstrip=lowerCamelCase    ) if isinstance(lowerCamelCase   ,     lowerCamelCase    ) else bos_token
														__snake_case		:      Dict										=       AddedToken(lowerCamelCase   ,     lstrip=lowerCamelCase   ,     rstrip=lowerCamelCase    ) if isinstance(lowerCamelCase   ,     lowerCamelCase    ) else eos_token
														__snake_case		:      int										=       AddedToken(lowerCamelCase   ,     lstrip=lowerCamelCase   ,     rstrip=lowerCamelCase    ) if isinstance(lowerCamelCase   ,     lowerCamelCase    ) else sep_token
														__snake_case		:      str										=       AddedToken(lowerCamelCase   ,     lstrip=lowerCamelCase   ,     rstrip=lowerCamelCase    ) if isinstance(lowerCamelCase   ,     lowerCamelCase    ) else cls_token
														__snake_case		:      Any										=       AddedToken(lowerCamelCase   ,     lstrip=lowerCamelCase   ,     rstrip=lowerCamelCase    ) if isinstance(lowerCamelCase   ,     lowerCamelCase    ) else unk_token
														__snake_case		:      int										=       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
														__snake_case		:      Union[str, 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:
																					__snake_case		:      Tuple										=       json.load(lowerCamelCase    )
														__snake_case		:      Union[str, Any]										=       {v: k for k, v in self.encoder.items()}
														__snake_case		:      str										=       errors  # how to handle errors in decoding
														__snake_case		:      Any										=       bytes_to_unicode()
														__snake_case		:      Any										=       {v: k for k, v in self.byte_encoder.items()}
														with open(lowerCamelCase   ,     encoding="utf-8"    ) as merges_handle:
																					__snake_case		:      Optional[Any]										=       merges_handle.read().split("\n"    )[1:-1]
														__snake_case		:      Tuple										=       [tuple(merge.split()    ) for merge in bpe_merges]
														__snake_case		:      Optional[int]										=       dict(zip(lowerCamelCase   ,     range(len(lowerCamelCase    )    )    )    )
														__snake_case		:      Optional[Any]										=       {}
														__snake_case		:      Tuple										=       add_prefix_space

														# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
														__snake_case		:      Optional[int]										=       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	:  List[Any]    )     ->   Union[str, Any]:
														return len(self.encoder    )

							def    __snake_case (							self	:  Union[str, Any]    )     ->   Union[str, Any]:
														return dict(self.encoder   ,     **self.added_tokens_encoder    )

							def    __snake_case (							self	:  List[Any]   ,     lowerCamelCase	:  Tuple    )     ->   Tuple:
														if token in self.cache:
																					return self.cache[token]
														__snake_case		:      List[Any]										=       tuple(lowerCamelCase    )
														__snake_case		:      int										=       get_pairs(lowerCamelCase    )

														if not pairs:
																					return token

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

							def    __snake_case (							self	:  List[Any]   ,     lowerCamelCase	:  str    )     ->   Union[str, Any]:
														__snake_case		:      Any										=       []
														for token in re.findall(self.pat   ,     lowerCamelCase    ):
																					__snake_case		:      Any										=       "".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	:  Optional[int]   ,     lowerCamelCase	:  List[str]    )     ->   Optional[int]:
														return self.encoder.get(lowerCamelCase   ,     self.encoder.get(self.unk_token    )    )

							def    __snake_case (							self	:  str   ,     lowerCamelCase	:  Tuple    )     ->   int:
														return self.decoder.get(lowerCamelCase    )

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

							def    __snake_case (							self	:  Optional[int]   ,     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
														__snake_case		:      Tuple										=       os.path.join(
														    lowerCamelCase   ,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]    )
														__snake_case		:      Tuple										=       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"    )

														__snake_case		:      List[str]										=       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!"    )
																																			__snake_case		:      Any										=       token_index
																												writer.write(" ".join(lowerCamelCase    ) + "\n"    )
																												index += 1

														return vocab_file, merge_file

							def    __snake_case (							self	:  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]
														__snake_case		:      Dict										=       [self.cls_token_id]
														__snake_case		:      List[Any]										=       [self.sep_token_id]
														return cls + token_ids_a + sep + sep + token_ids_a + sep

							def    __snake_case (							self	:  str   ,     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	:  Union[str, Any]   ,     lowerCamelCase	:  List[int]   ,     lowerCamelCase	:  Optional[List[int]] = None    )     ->   List[int]:
														__snake_case		:      Dict										=       [self.sep_token_id]
														__snake_case		:      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	:  List[Any]   ,     lowerCamelCase	:  Optional[int]   ,     lowerCamelCase	:  Dict=False   ,     **lowerCamelCase	:  Optional[Any]    )     ->   Tuple:
														__snake_case		:      Optional[int]										=       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()):
																					__snake_case		:      int										=       " " + text
														return (text, kwargs)






							def    __snake_case (							self	:  Union[str, Any]   ,     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:
														__snake_case		:      Optional[Any]										=       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:
																					__snake_case		:      Optional[int]										=       "attention_mask" in self.model_input_names

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

																					if needs_to_be_padded:
																												__snake_case		:      List[Any]										=       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`
																																			__snake_case		:      Any										=       (
																																			    encoded_inputs["global_attention_mask"] + [-1] * difference
																																			)
																												elif self.padding_side == "left":
																																			__snake_case		:      List[str]										=       [-1] * difference + encoded_inputs[
																																			    "global_attention_mask"
																																			]
																												else:
																																			raise ValueError("Invalid padding strategy:" + str(self.padding_side    )    )

														return encoded_inputs





import logging

from transformers.configuration_utils import PretrainedConfig


_snake_case					:		Optional[Any]      =    logging.getLogger(__name__)

class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Tuple					  =  "masked_bert"

							def __init__(							self	:  Optional[int]   ,     lowerCamelCase	:  Any=30522   ,     lowerCamelCase	:  Tuple=768   ,     lowerCamelCase	:  str=12   ,     lowerCamelCase	:  Dict=12   ,     lowerCamelCase	:  List[str]=3072   ,     lowerCamelCase	:  List[str]="gelu"   ,     lowerCamelCase	:  Any=0.1   ,     lowerCamelCase	:  Any=0.1   ,     lowerCamelCase	:  List[Any]=512   ,     lowerCamelCase	:  int=2   ,     lowerCamelCase	:  str=0.02   ,     lowerCamelCase	:  List[str]=1E-12   ,     lowerCamelCase	:  Any=0   ,     lowerCamelCase	:  Dict="topK"   ,     lowerCamelCase	:  List[Any]="constant"   ,     lowerCamelCase	:  Dict=0.0   ,     **lowerCamelCase	:  List[Any]   ,     )     ->   Dict:
														super().__init__(pad_token_id=lowerCamelCase   ,     **lowerCamelCase    )

														__snake_case		:      Optional[Any]										=       vocab_size
														__snake_case		:      Optional[int]										=       hidden_size
														__snake_case		:      Tuple										=       num_hidden_layers
														__snake_case		:      Union[str, Any]										=       num_attention_heads
														__snake_case		:      Optional[Any]										=       hidden_act
														__snake_case		:      str										=       intermediate_size
														__snake_case		:      Tuple										=       hidden_dropout_prob
														__snake_case		:      Dict										=       attention_probs_dropout_prob
														__snake_case		:      List[str]										=       max_position_embeddings
														__snake_case		:      Union[str, Any]										=       type_vocab_size
														__snake_case		:      Any										=       initializer_range
														__snake_case		:      str										=       layer_norm_eps
														__snake_case		:      str										=       pruning_method
														__snake_case		:      int										=       mask_init
														__snake_case		:      Any										=       mask_scale

