

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_6384,
}

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

def 			lowerCamelCase__			(       _a):
	SCREAMING_SNAKE_CASE :   Tuple					  =							set()
	SCREAMING_SNAKE_CASE :   Optional[int]					  =							word[0]
	for char in word[1:]:
		pairs.add((prev_char, char))
		SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							char
	return pairs






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			lowerCamelCase__							     =VOCAB_FILES_NAMES
			lowerCamelCase__							     =PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase__							     =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase__							     =['input_ids', 'attention_mask']
			def __init__(      self				:			int   ,   a				:			int   ,   a				:			Any   ,   a				:			List[Any]="replace"   ,   a				:			Optional[Any]="<s>"   ,   a				:			str="</s>"   ,   a				:			Optional[Any]="</s>"   ,   a				:			Optional[int]="<s>"   ,   a				:			Optional[int]="<unk>"   ,   a				:			Union[str, Any]="<pad>"   ,   a				:			Tuple="<mask>"   ,   a				:			Any=False   ,   **a				:			Optional[int]   ,   )				->							List[str]:

				"""simple docstring"""

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

				# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
				SCREAMING_SNAKE_CASE :   Dict					  =							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				:			str						)				->							Tuple:

				"""simple docstring"""

				return len(self.encoder						)
			def 				__UpperCamelCase			(      self				:			Dict						)				->							List[str]:

				"""simple docstring"""

				return dict(self.encoder   ,   **self.added_tokens_encoder						)
			def 				__UpperCamelCase			(      self				:			Tuple   ,   a				:			Tuple						)				->							List[Any]:

				"""simple docstring"""

				if token in self.cache:
					return self.cache[token]
				SCREAMING_SNAKE_CASE :   Any					  =							tuple(a						)
				SCREAMING_SNAKE_CASE :   str					  =							get_pairs(a						)

				if not pairs:
					return token

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

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							[]
				for token in re.findall(self.pat   ,   a						):
					SCREAMING_SNAKE_CASE :   Optional[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(a						).split(" "						)						)
				return bpe_tokens
			def 				__UpperCamelCase			(      self				:			List[Any]   ,   a				:			str						)				->							str:

				"""simple docstring"""

				return self.encoder.get(a   ,   self.encoder.get(self.unk_token						)						)
			def 				__UpperCamelCase			(      self				:			Optional[int]   ,   a				:			Any						)				->							Any:

				"""simple docstring"""

				return self.decoder.get(a						)
			def 				__UpperCamelCase			(      self				:			List[str]   ,   a				:			List[str]						)				->							Any:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   List[Any]					  =							"".join(a						)
				SCREAMING_SNAKE_CASE :   Dict					  =							bytearray([self.byte_decoder[c] for c in text]						).decode("utf-8"   ,   errors=self.errors						)
				return text
			def 				__UpperCamelCase			(      self				:			str   ,   a				:			str   ,   a				:			Optional[str] = None						)				->							Tuple[str]:

				"""simple docstring"""

				if not os.path.isdir(a						):
					logger.error(F"Vocabulary path ({save_directory}) should be a directory"						)
					return
				SCREAMING_SNAKE_CASE :   str					  =							os.path.join(
				    a   ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
				SCREAMING_SNAKE_CASE :   int					  =							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"						)

				SCREAMING_SNAKE_CASE :   List[Any]					  =							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!"						)
							SCREAMING_SNAKE_CASE :   int					  =							token_index
						writer.write(" ".join(a						) + "\n"						)
						index += 1

				return vocab_file, merge_file
			def 				__UpperCamelCase			(      self				:			Optional[Any]   ,   a				:			List[int]   ,   a				:			Optional[List[int]] = None						)				->							List[int]:

				"""simple docstring"""

				if token_ids_a is None:
					return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
				SCREAMING_SNAKE_CASE :   Any					  =							[self.cls_token_id]
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							[self.sep_token_id]
				return cls + token_ids_a + sep + sep + token_ids_a + sep
			def 				__UpperCamelCase			(      self				:			Tuple   ,   a				:			List[int]   ,   a				:			Optional[List[int]] = None   ,   a				:			bool = False						)				->							List[int]:

				"""simple docstring"""

				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				:			List[str]   ,   a				:			List[int]   ,   a				:			Optional[List[int]] = None						)				->							List[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   List[str]					  =							[self.sep_token_id]
				SCREAMING_SNAKE_CASE :   Dict					  =							[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				:			List[Any]   ,   a				:			Union[str, Any]   ,   a				:			Any=False   ,   **a				:			Tuple						)				->							Dict:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   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()):
					SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							" " + text
				return (text, kwargs)






			def 				__UpperCamelCase			(      self				:			Union[str, Any]   ,   a				:			Union[Dict[str, EncodedInput], BatchEncoding]   ,   a				:			Optional[int] = None   ,   a				:			PaddingStrategy = PaddingStrategy.DO_NOT_PAD   ,   a				:			Optional[int] = None   ,   a				:			Optional[bool] = None   ,   )				->							dict:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							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:
					SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							"attention_mask" in self.model_input_names

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

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

				return encoded_inputs


from __future__ import annotations

def 			lowerCamelCase__			(       _a):
	SCREAMING_SNAKE_CASE :   Optional[Any]					  =							2
	SCREAMING_SNAKE_CASE :   Optional[int]					  =							[]
	while i * i <= n:
		if n % i:
			i += 1
		else:
			n //= i
			factors.append(_a)
	if n > 1:
		factors.append(_a)
	return factors


if __name__ == "__main__":
			import doctest

			doctest.testmod()