




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


__UpperCamelCase					:       Tuple    					=      logging.get_logger(__name__)


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

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

__UpperCamelCase					:       List[Any]    					=      {
    "allenai/led-base-16384": 16_384,
}





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





def 		__A		(	__lowerCamelCase    )      ->       Dict:
	a										=							set()
	a										=							word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)    )
		a										=							char
	return pairs



class 		__lowerCAmelCase	(	__magic_name__ ):
							UpperCamelCase__					     =  VOCAB_FILES_NAMES
							UpperCamelCase__					     =  PRETRAINED_VOCAB_FILES_MAP
							UpperCamelCase__					     =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							UpperCamelCase__					     =  ['''input_ids''', '''attention_mask''']
							def __init__(						self						:Optional[Any]		,      __magic_name__						:Optional[int]		,      __magic_name__						:Any		,      __magic_name__						:int="replace"		,      __magic_name__						:Optional[Any]="<s>"		,      __magic_name__						:str="</s>"		,      __magic_name__						:Any="</s>"		,      __magic_name__						:Dict="<s>"		,      __magic_name__						:List[str]="<unk>"		,      __magic_name__						:Union[str, Any]="<pad>"		,      __magic_name__						:Dict="<mask>"		,      __magic_name__						:Dict=False		,      **__magic_name__						:int		,      ):







								'''simple docstring'''







								a										=							AddedToken(__magic_name__		,      lstrip=__magic_name__		,      rstrip=__magic_name__				) if isinstance(__magic_name__		,      __magic_name__				) else bos_token
								a										=							AddedToken(__magic_name__		,      lstrip=__magic_name__		,      rstrip=__magic_name__				) if isinstance(__magic_name__		,      __magic_name__				) else eos_token
								a										=							AddedToken(__magic_name__		,      lstrip=__magic_name__		,      rstrip=__magic_name__				) if isinstance(__magic_name__		,      __magic_name__				) else sep_token
								a										=							AddedToken(__magic_name__		,      lstrip=__magic_name__		,      rstrip=__magic_name__				) if isinstance(__magic_name__		,      __magic_name__				) else cls_token
								a										=							AddedToken(__magic_name__		,      lstrip=__magic_name__		,      rstrip=__magic_name__				) if isinstance(__magic_name__		,      __magic_name__				) else unk_token
								a										=							AddedToken(__magic_name__		,      lstrip=__magic_name__		,      rstrip=__magic_name__				) if isinstance(__magic_name__		,      __magic_name__				) else pad_token

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

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

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

								# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
								a										=							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       lowerCamelCase__							(						self						:int				):







								'''simple docstring'''







								return len(self.encoder				)
							def       lowerCamelCase__							(						self						:str				):







								'''simple docstring'''







								return dict(self.encoder		,      **self.added_tokens_encoder				)
							def       lowerCamelCase__							(						self						:Any		,      __magic_name__						:Dict				):







								'''simple docstring'''







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

								if not pairs:
									return token

								while True:
									a										=							min(__magic_name__		,      key=lambda __magic_name__				: self.bpe_ranks.get(__magic_name__		,      float("""inf"""				)				)				)
									if bigram not in self.bpe_ranks:
										break
									a				, a										=							bigram
									a										=							[]
									a										=							0
									while i < len(__magic_name__				):
										try:
											a										=							word.index(__magic_name__		,      __magic_name__				)
										except ValueError:
											new_word.extend(word[i:]				)
											break
										else:
											new_word.extend(word[i:j]				)
											a										=							j

										if word[i] == first and i < len(__magic_name__				) - 1 and word[i + 1] == second:
											new_word.append(first + second				)
											i += 2
										else:
											new_word.append(word[i]				)
											i += 1
									a										=							tuple(__magic_name__				)
									a										=							new_word
									if len(__magic_name__				) == 1:
										break
									else:
										a										=							get_pairs(__magic_name__				)
								a										=							""" """.join(__magic_name__				)
								a										=							word
								return word
							def       lowerCamelCase__							(						self						:Optional[int]		,      __magic_name__						:str				):







								'''simple docstring'''







								a										=							[]
								for token in re.findall(self.pat		,      __magic_name__				):
									a										=							"""""".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(__magic_name__				).split(""" """				)				)
								return bpe_tokens
							def       lowerCamelCase__							(						self						:Optional[Any]		,      __magic_name__						:Any				):







								'''simple docstring'''







								return self.encoder.get(__magic_name__		,      self.encoder.get(self.unk_token				)				)
							def       lowerCamelCase__							(						self						:Any		,      __magic_name__						:Tuple				):







								'''simple docstring'''







								return self.decoder.get(__magic_name__				)
							def       lowerCamelCase__							(						self						:Optional[Any]		,      __magic_name__						:Optional[Any]				):







								'''simple docstring'''







								a										=							"""""".join(__magic_name__				)
								a										=							bytearray([self.byte_decoder[c] for c in text]				).decode("""utf-8"""		,      errors=self.errors				)
								return text
							def       lowerCamelCase__							(						self						:Union[str, Any]		,      __magic_name__						:str		,      __magic_name__						:Optional[str] = None				):







								'''simple docstring'''







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

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

								a										=							0
								with open(__magic_name__		,      """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 __magic_name__				: 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!"""				)
											a										=							token_index
										writer.write(""" """.join(__magic_name__				) + """\n"""				)
										index += 1

								return vocab_file, merge_file
							def       lowerCamelCase__							(						self						:Optional[Any]		,      __magic_name__						:List[int]		,      __magic_name__						:Optional[List[int]] = None				):







								'''simple docstring'''







								if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								a										=							[self.cls_token_id]
								a										=							[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep
							def       lowerCamelCase__							(						self						:List[str]		,      __magic_name__						:List[int]		,      __magic_name__						:Optional[List[int]] = None		,      __magic_name__						:bool = False				):







								'''simple docstring'''







								if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=__magic_name__		,      token_ids_a=__magic_name__		,      already_has_special_tokens=__magic_name__				)

								if token_ids_a is None:
									return [1] + ([0] * len(__magic_name__				)) + [1]
								return [1] + ([0] * len(__magic_name__				)) + [1, 1] + ([0] * len(__magic_name__				)) + [1]
							def       lowerCamelCase__							(						self						:Optional[int]		,      __magic_name__						:List[int]		,      __magic_name__						:Optional[List[int]] = None				):







								'''simple docstring'''







								a										=							[self.sep_token_id]
								a										=							[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       lowerCamelCase__							(						self						:List[str]		,      __magic_name__						:Optional[Any]		,      __magic_name__						:Union[str, Any]=False		,      **__magic_name__						:Optional[int]				):







								'''simple docstring'''







								a										=							kwargs.pop("""add_prefix_space"""		,      self.add_prefix_space				)
								if (is_split_into_words or add_prefix_space) and (len(__magic_name__				) > 0 and not text[0].isspace()):
									a										=							""" """ + text
								return (text, kwargs)





							def       lowerCamelCase__							(						self						:Optional[Any]		,      __magic_name__						:Union[Dict[str, EncodedInput], BatchEncoding]		,      __magic_name__						:Optional[int] = None		,      __magic_name__						:PaddingStrategy = PaddingStrategy.DO_NOT_PAD		,      __magic_name__						:Optional[int] = None		,      __magic_name__						:Optional[bool] = None		,      ):







								'''simple docstring'''







								a										=							super()._pad(
								    encoded_inputs=__magic_name__		,      max_length=__magic_name__		,      padding_strategy=__magic_name__		,      pad_to_multiple_of=__magic_name__		,      return_attention_mask=__magic_name__		,      )

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

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

									if needs_to_be_padded:
										a										=							len(__magic_name__				) - 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`
											a										=							(
											    encoded_inputs["""global_attention_mask"""] + [-1] * difference
											)
										elif self.padding_side == "left":
											a										=							[-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 		__A		(	__lowerCamelCase							,			__lowerCamelCase = None    )      ->       list[list[str]]:
	a										=							word_bank or []
	# create a table
	a										=							len(__lowerCamelCase    ) + 1

	a										=							[]
	for _ in range(__lowerCamelCase    ):
		table.append([]    )
	# seed value
	a										=							[[]]  # because empty string has empty combination

	# iterate through the indices
	for i in range(__lowerCamelCase    ):
		# condition
		if table[i] != []:
			for word in word_bank:
				# slice condition
				if target[i : i + len(__lowerCamelCase    )] == word:
					a										=							[
					    [word, *way] for way in table[i]
					]
					# adds the word to every combination the current position holds
					# now,push that combination to the table[i+len(word)]
					table[i + len(__lowerCamelCase    )] += new_combinations

    # combinations are in reverse order so reverse for better output
	for combination in table[len(__lowerCamelCase    )]:
		combination.reverse()

	return table[len(__lowerCamelCase    )]


if __name__ == "__main__":
		print(all_construct("jwajalapa", ["jwa", "j", "w", "a", "la", "lapa"]))
		print(all_construct("rajamati", ["s", "raj", "amat", "raja", "ma", "i", "t"]))
		print(
		    all_construct(
		        "hexagonosaurus",
		        ["h", "ex", "hex", "ag", "ago", "ru", "auru", "rus", "go", "no", "o", "s"],
		    )
		)

