
'''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							:   List[str]					=    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							:   List[Any]					=    {
    '''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							:   List[str]					=    {
    '''allenai/led-base-16384''': 16384,
}




@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def lowercase_	(   )     ->							Union[str, Any]:
					'''simple docstring'''

					lowerCamelCase_					:      Union[str, Any]     =		(
					    list(range(ord('''!'''				)			,       ord('''~'''				) + 1				)				) + list(range(ord('''¡'''				)			,       ord('''¬'''				) + 1				)				) + list(range(ord('''®'''				)			,       ord('''ÿ'''				) + 1				)				)
					)
					lowerCamelCase_					:      List[str]     =		bs[:]
					lowerCamelCase_					:      str     =		0
					for b in range(2**8				):
										if b not in bs:
															bs.append(lowercase_				)
															cs.append(2**8 + n				)
															n += 1
					lowerCamelCase_					:      str     =		[chr(lowercase_				) for n in cs]
					return dict(zip(lowercase_			,       lowercase_				)				)




def lowercase_	(   _lowercase				)     ->							str:
					'''simple docstring'''

					lowerCamelCase_					:      Dict     =		set()
					lowerCamelCase_					:      Optional[Any]     =		word[0]
					for char in word[1:]:
										pairs.add((prev_char, char)				)
										lowerCamelCase_					:      Dict     =		char
					return pairs






class 	__lowercase				(  _UpperCamelCase    ):
			lowerCamelCase			:		Optional[int]	      =			VOCAB_FILES_NAMES
			lowerCamelCase			:		Union[str, Any]	      =			PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase			:		Tuple	      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase			:		Optional[int]	      =			["input_ids", "attention_mask"]

			def __init__(self			,   A			,   A			,   A="replace"			,   A="<s>"			,   A="</s>"			,   A="</s>"			,   A="<s>"			,   A="<unk>"			,   A="<pad>"			,   A="<mask>"			,   A=False			,   **A			,   ):
								lowerCamelCase_					:      Tuple     =		AddedToken(__a			,   lstrip=__a			,   rstrip=__a      ) if isinstance(__a			,   __a      ) else bos_token
								lowerCamelCase_					:      List[str]     =		AddedToken(__a			,   lstrip=__a			,   rstrip=__a      ) if isinstance(__a			,   __a      ) else eos_token
								lowerCamelCase_					:      Tuple     =		AddedToken(__a			,   lstrip=__a			,   rstrip=__a      ) if isinstance(__a			,   __a      ) else sep_token
								lowerCamelCase_					:      str     =		AddedToken(__a			,   lstrip=__a			,   rstrip=__a      ) if isinstance(__a			,   __a      ) else cls_token
								lowerCamelCase_					:      Any     =		AddedToken(__a			,   lstrip=__a			,   rstrip=__a      ) if isinstance(__a			,   __a      ) else unk_token
								lowerCamelCase_					:      List[Any]     =		AddedToken(__a			,   lstrip=__a			,   rstrip=__a      ) if isinstance(__a			,   __a      ) else pad_token

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

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

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

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

			def        UpperCAmelCase__ (self			,   A      ):
								if token in self.cache:
													return self.cache[token]
								lowerCamelCase_					:      Optional[int]     =		tuple(__a      )
								lowerCamelCase_					:      List[Any]     =		get_pairs(__a      )

								if not pairs:
													return token

								while True:
													lowerCamelCase_					:      List[str]     =		min(__a			,   key=lambda A      : self.bpe_ranks.get(__a			,   float('''inf'''      )      )      )
													if bigram not in self.bpe_ranks:
																		break
													lowerCamelCase_					:      Union[str, Any]     =		bigram
													lowerCamelCase_					:      Dict     =		[]
													lowerCamelCase_					:      Optional[Any]     =		0
													while i < len(__a      ):
																		try:
																							lowerCamelCase_					:      Dict     =		word.index(__a			,   __a      )
																		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(__a      ) - 1 and word[i + 1] == second:
																							new_word.append(first + second      )
																							i += 2
																		else:
																							new_word.append(word[i]      )
																							i += 1
													lowerCamelCase_					:      str     =		tuple(__a      )
													lowerCamelCase_					:      Optional[int]     =		new_word
													if len(__a      ) == 1:
																		break
													else:
																		lowerCamelCase_					:      Any     =		get_pairs(__a      )
								lowerCamelCase_					:      str     =		" ".join(__a      )
								lowerCamelCase_					:      Dict     =		word
								return word

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      str     =		[]
								for token in re.findall(self.pat			,   __a      ):
													lowerCamelCase_					:      List[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(__a      ).split(''' '''      )      )
								return bpe_tokens

			def        UpperCAmelCase__ (self			,   A      ):
								return self.encoder.get(__a			,   self.encoder.get(self.unk_token      )      )

			def        UpperCAmelCase__ (self			,   A      ):
								return self.decoder.get(__a      )

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      Tuple     =		"".join(__a      )
								lowerCamelCase_					:      List[Any]     =		bytearray([self.byte_decoder[c] for c in text]      ).decode('''utf-8'''			,   errors=self.errors      )
								return text

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								if not os.path.isdir(__a      ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
													return
								lowerCamelCase_					:      Tuple     =		os.path.join(
								    __a			,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
								lowerCamelCase_					:      Dict     =		os.path.join(
								    __a			,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']      )

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

								lowerCamelCase_					:      str     =		0
								with open(__a			,   '''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 A      : 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_					:      Union[str, Any]     =		token_index
																		writer.write(''' '''.join(__a      ) + '''\n'''      )
																		index += 1

								return vocab_file, merge_file

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								lowerCamelCase_					:      Tuple     =		[self.cls_token_id]
								lowerCamelCase_					:      List[Any]     =		[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep

			def        UpperCAmelCase__ (self			,   A			,   A = None			,   A = False      ):
								if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=__a			,   token_ids_a=__a			,   already_has_special_tokens=__a      )

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

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								lowerCamelCase_					:      Optional[int]     =		[self.sep_token_id]
								lowerCamelCase_					:      List[Any]     =		[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        UpperCAmelCase__ (self			,   A			,   A=False			,   **A      ):
								lowerCamelCase_					:      Optional[Any]     =		kwargs.pop('''add_prefix_space'''			,   self.add_prefix_space      )
								if (is_split_into_words or add_prefix_space) and (len(__a      ) > 0 and not text[0].isspace()):
													lowerCamelCase_					:      List[Any]     =		" " + text
								return (text, kwargs)






			def        UpperCAmelCase__ (self			,   A			,   A = None			,   A = PaddingStrategy.DO_NOT_PAD			,   A = None			,   A = None			,   ):
								lowerCamelCase_					:      Any     =		super()._pad(
								    encoded_inputs=__a			,   max_length=__a			,   padding_strategy=__a			,   pad_to_multiple_of=__a			,   return_attention_mask=__a			,   )

								# Load from model defaults
								if return_attention_mask is None:
													lowerCamelCase_					:      str     =		"attention_mask" in self.model_input_names

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

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

								return encoded_inputs




'''simple docstring'''


from __future__ import annotations




def lowercase_	(   _lowercase			,       _lowercase			,       _lowercase				)     ->							dict[str, float]:
					'''simple docstring'''

					if (voltage, current, resistance).count(0				) != 1:
										raise ValueError('''One and only one argument must be 0'''				)
					if resistance < 0:
										raise ValueError('''Resistance cannot be negative'''				)
					if voltage == 0:
										return {"voltage": float(current * resistance				)}
					elif current == 0:
										return {"current": voltage / resistance}
					elif resistance == 0:
										return {"resistance": voltage / current}
					else:
										raise ValueError('''Exactly one argument must be 0'''				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()


