




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


__A        =    logging.get_logger(__name__)


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

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

__A        =    {
    "allenai/led-base-16384": 1_63_84,
}







@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 			lowerCamelCase_		(       )     ->       Dict:





				"""simple docstring"""


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







def 			lowerCamelCase_		(       UpperCamelCase__				:      int      )     ->       Optional[Any]:





				"""simple docstring"""


				__lowerCamelCase		       =    set()
				__lowerCamelCase		       =    word[0]
				for char in word[1:]:
								pairs.add((prev_char, char)      )
								__lowerCamelCase		       =    char
				return pairs







class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







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


			def __init__(      self			,						lowerCamelCase__			,						lowerCamelCase__			,						lowerCamelCase__="replace"			,						lowerCamelCase__="<s>"			,						lowerCamelCase__="</s>"			,						lowerCamelCase__="</s>"			,						lowerCamelCase__="<s>"			,						lowerCamelCase__="<unk>"			,						lowerCamelCase__="<pad>"			,						lowerCamelCase__="<mask>"			,						lowerCamelCase__=False			,						**lowerCamelCase__			,						)    ->      str:



							'''simple docstring'''
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else bos_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else eos_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else sep_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else cls_token
							__lowerCamelCase		       =    AddedToken(lowerCamelCase__			,						lstrip=lowerCamelCase__			,						rstrip=lowerCamelCase__							) if isinstance(lowerCamelCase__			,						lowerCamelCase__							) else unk_token
							__lowerCamelCase		       =    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		       =    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		       =    json.load(lowerCamelCase__							)
							__lowerCamelCase		       =    {v: k for k, v in self.encoder.items()}
							__lowerCamelCase		       =    errors  # how to handle errors in decoding
							__lowerCamelCase		       =    bytes_to_unicode()
							__lowerCamelCase		       =    {v: k for k, v in self.byte_encoder.items()}
							with open(lowerCamelCase__			,						encoding='utf-8'							) as merges_handle:
											__lowerCamelCase		       =    merges_handle.read().split('\n'							)[1:-1]
							__lowerCamelCase		       =    [tuple(merge.split()							) for merge in bpe_merges]
							__lowerCamelCase		       =    dict(zip(lowerCamelCase__			,						range(len(lowerCamelCase__							)							)							)							)
							__lowerCamelCase		       =    {}
							__lowerCamelCase		       =    add_prefix_space

							# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
							__lowerCamelCase		       =    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       lowercase_    (      self							)    ->      Dict:



							'''simple docstring'''
							return len(self.encoder							)


			def       lowercase_    (      self							)    ->      Tuple:



							'''simple docstring'''
							return dict(self.encoder			,						**self.added_tokens_encoder							)


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[str]:



							'''simple docstring'''
							if token in self.cache:
											return self.cache[token]
							__lowerCamelCase		       =    tuple(lowerCamelCase__							)
							__lowerCamelCase		       =    get_pairs(lowerCamelCase__							)

							if not pairs:
											return token

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


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      Union[str, Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    []
							for token in re.findall(self.pat			,						lowerCamelCase__							):
											__lowerCamelCase		       =    ''.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       lowercase_    (      self			,						lowerCamelCase__							)    ->      Tuple:



							'''simple docstring'''
							return self.encoder.get(lowerCamelCase__			,						self.encoder.get(self.unk_token							)							)


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[Any]:



							'''simple docstring'''
							return self.decoder.get(lowerCamelCase__							)


			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[str]:



							'''simple docstring'''
							__lowerCamelCase		       =    ''.join(lowerCamelCase__							)
							__lowerCamelCase		       =    bytearray([self.byte_decoder[c] for c in text]							).decode('utf-8'			,						errors=self.errors							)
							return text


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      Tuple[str]:



							'''simple docstring'''
							if not os.path.isdir(lowerCamelCase__							):
											logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
											return
							__lowerCamelCase		       =    os.path.join(
							    lowerCamelCase__			,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']							)
							__lowerCamelCase		       =    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		       =    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		       =    token_index
															writer.write(' '.join(lowerCamelCase__							) + '\n'							)
															index += 1

							return vocab_file, merge_file


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      List[int]:



							'''simple docstring'''
							if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							__lowerCamelCase		       =    [self.cls_token_id]
							__lowerCamelCase		       =    [self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None			,						lowerCamelCase__ = False							)    ->      List[int]:



							'''simple docstring'''
							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       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      List[int]:



							'''simple docstring'''
							__lowerCamelCase		       =    [self.sep_token_id]
							__lowerCamelCase		       =    [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       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__=False			,						**lowerCamelCase__							)    ->      str:



							'''simple docstring'''
							__lowerCamelCase		       =    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		       =    ' ' + text
							return (text, kwargs)






			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None			,						lowerCamelCase__ = PaddingStrategy.DO_NOT_PAD			,						lowerCamelCase__ = None			,						lowerCamelCase__ = None			,						)    ->      dict:



							'''simple docstring'''
							__lowerCamelCase		       =    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		       =    'attention_mask' in self.model_input_names

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

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

							return encoded_inputs








import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
__A        =    {
    "E": 1_2.7_0,
    "T": 9.0_6,
    "A": 8.1_7,
    "O": 7.5_1,
    "I": 6.9_7,
    "N": 6.7_5,
    "S": 6.3_3,
    "H": 6.0_9,
    "R": 5.9_9,
    "D": 4.2_5,
    "L": 4.0_3,
    "C": 2.7_8,
    "U": 2.7_6,
    "M": 2.4_1,
    "W": 2.3_6,
    "F": 2.2_3,
    "G": 2.0_2,
    "Y": 1.9_7,
    "P": 1.9_3,
    "B": 1.2_9,
    "V": 0.9_8,
    "K": 0.7_7,
    "J": 0.1_5,
    "X": 0.1_5,
    "Q": 0.1_0,
    "Z": 0.0_7,
}
__A        =    "ETAOINSHRDLCUMWFGYPBVKJXQZ"
__A        =    "ABCDEFGHIJKLMNOPQRSTUVWXYZ"







def 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       dict[str, int]:





				"""simple docstring"""


				__lowerCamelCase		       =    {letter: 0 for letter in string.ascii_uppercase}
				for letter in message.upper():
								if letter in LETTERS:
												letter_count[letter] += 1

				return letter_count







def 			lowerCamelCase_		(       UpperCamelCase__				:      tuple      )     ->       str:





				"""simple docstring"""


				return x[0]







def 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       str:





				"""simple docstring"""


				__lowerCamelCase		       =    get_letter_count(UpperCamelCase__      )
				__lowerCamelCase		       =    {
				    freq: [] for letter, freq in letter_to_freq.items()
				}
				for letter in LETTERS:
								freq_to_letter[letter_to_freq[letter]].append(UpperCamelCase__      )

				__lowerCamelCase		       =    {}

				for freq in freq_to_letter:
								freq_to_letter[freq].sort(key=ETAOIN.find ,     reverse=UpperCamelCase__      )
								__lowerCamelCase		       =    ''.join(freq_to_letter[freq]      )

				__lowerCamelCase		       =    list(freq_to_letter_str.items()      )
				freq_pairs.sort(key=UpperCamelCase__ ,     reverse=UpperCamelCase__      )

				__lowerCamelCase		       =    [freq_pair[1] for freq_pair in freq_pairs]

				return "".join(UpperCamelCase__      )







def 			lowerCamelCase_		(       UpperCamelCase__				:      str      )     ->       int:





				"""simple docstring"""


				__lowerCamelCase		       =    get_frequency_order(UpperCamelCase__      )
				__lowerCamelCase		       =    0
				for common_letter in ETAOIN[:6]:
								if common_letter in freq_order[:6]:
												match_score += 1

				for uncommon_letter in ETAOIN[-6:]:
								if uncommon_letter in freq_order[-6:]:
												match_score += 1

				return match_score


if __name__ == "__main__":
					import doctest

					doctest.testmod()


