





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             =							logging.get_logger(__name__)


_UpperCAmelCase             =							{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all LED models at https://huggingface.co/models?filter=LED
_UpperCAmelCase             =							{
    '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             =							{
    'allenai/led-base-16384': 1_6384,
}






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






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:str   )      ->   Union[str, Any]:
 __lowerCAmelCase					:	List[Any]      =       set()
 __lowerCAmelCase					:	Optional[Any]      =       word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)   )
  __lowerCAmelCase					:	str      =       char
 return pairs







class        snake_case_    (		__lowercase						):
  A_      							=   VOCAB_FILES_NAMES
  A_      							=   PRETRAINED_VOCAB_FILES_MAP
  A_      							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  A_      							=   ['input_ids', 'attention_mask']






  def __init__(							self			:					Dict       ,  _snake_case			:					List[str]       ,  _snake_case			:					Dict       ,  _snake_case			:					Tuple="replace"       ,  _snake_case			:					List[Any]="<s>"       ,  _snake_case			:					Optional[int]="</s>"       ,  _snake_case			:					Tuple="</s>"       ,  _snake_case			:					Any="<s>"       ,  _snake_case			:					str="<unk>"       ,  _snake_case			:					Dict="<pad>"       ,  _snake_case			:					Dict="<mask>"       ,  _snake_case			:					str=False       ,  **_snake_case			:					str       ,  )->Dict:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[int]      =       AddedToken(_snake_case       ,  lstrip=_snake_case       ,  rstrip=_snake_case      ) if isinstance(_snake_case       ,  _snake_case      ) else bos_token
   __lowerCAmelCase					:	List[str]      =       AddedToken(_snake_case       ,  lstrip=_snake_case       ,  rstrip=_snake_case      ) if isinstance(_snake_case       ,  _snake_case      ) else eos_token
   __lowerCAmelCase					:	List[str]      =       AddedToken(_snake_case       ,  lstrip=_snake_case       ,  rstrip=_snake_case      ) if isinstance(_snake_case       ,  _snake_case      ) else sep_token
   __lowerCAmelCase					:	int      =       AddedToken(_snake_case       ,  lstrip=_snake_case       ,  rstrip=_snake_case      ) if isinstance(_snake_case       ,  _snake_case      ) else cls_token
   __lowerCAmelCase					:	Union[str, Any]      =       AddedToken(_snake_case       ,  lstrip=_snake_case       ,  rstrip=_snake_case      ) if isinstance(_snake_case       ,  _snake_case      ) else unk_token
   __lowerCAmelCase					:	Union[str, Any]      =       AddedToken(_snake_case       ,  lstrip=_snake_case       ,  rstrip=_snake_case      ) if isinstance(_snake_case       ,  _snake_case      ) else pad_token

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

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

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

   # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
   __lowerCAmelCase					:	Union[str, 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			:					str      )->List[str]:






   '''simple docstring'''

   return len(self.encoder      )






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






   '''simple docstring'''

   return dict(self.encoder       ,  **self.added_tokens_encoder      )






  def 				UpperCAmelCase__						(							self			:					Optional[Any]       ,  _snake_case			:					Tuple      )->List[str]:






   '''simple docstring'''

   if token in self.cache:
    return self.cache[token]
   __lowerCAmelCase					:	List[Any]      =       tuple(_snake_case      )
   __lowerCAmelCase					:	Union[str, Any]      =       get_pairs(_snake_case      )

   if not pairs:
    return token

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

     if word[i] == first and i < len(_snake_case      ) - 1 and word[i + 1] == second:
      new_word.append(first + second      )
      i += 2
     else:
      new_word.append(word[i]      )
      i += 1
    __lowerCAmelCase					:	Optional[int]      =       tuple(_snake_case      )
    __lowerCAmelCase					:	Optional[int]      =       new_word
    if len(_snake_case      ) == 1:
     break
    else:
     __lowerCAmelCase					:	Optional[int]      =       get_pairs(_snake_case      )
   __lowerCAmelCase					:	Dict      =       """ """.join(_snake_case      )
   __lowerCAmelCase					:	Union[str, Any]      =       word
   return word






  def 				UpperCAmelCase__						(							self			:					List[Any]       ,  _snake_case			:					Optional[int]      )->List[str]:






   '''simple docstring'''

   __lowerCAmelCase					:	List[Any]      =       []
   for token in re.findall(self.pat       ,  _snake_case      ):
    __lowerCAmelCase					:	Dict      =       """""".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(_snake_case      ).split(""" """      )      )
   return bpe_tokens






  def 				UpperCAmelCase__						(							self			:					Tuple       ,  _snake_case			:					List[str]      )->Tuple:






   '''simple docstring'''

   return self.encoder.get(_snake_case       ,  self.encoder.get(self.unk_token      )      )






  def 				UpperCAmelCase__						(							self			:					List[str]       ,  _snake_case			:					List[str]      )->Union[str, Any]:






   '''simple docstring'''

   return self.decoder.get(_snake_case      )






  def 				UpperCAmelCase__						(							self			:					List[str]       ,  _snake_case			:					List[Any]      )->Optional[int]:






   '''simple docstring'''

   __lowerCAmelCase					:	Dict      =       """""".join(_snake_case      )
   __lowerCAmelCase					:	int      =       bytearray([self.byte_decoder[c] for c in text]      ).decode("""utf-8"""       ,  errors=self.errors      )
   return text






  def 				UpperCAmelCase__						(							self			:					List[Any]       ,  _snake_case			:					str       ,  _snake_case			:					Optional[str] = None      )->Tuple[str]:






   '''simple docstring'''

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

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

   __lowerCAmelCase					:	List[str]      =       0
   with open(_snake_case       ,  """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 _snake_case      : 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					:	Dict      =       token_index
     writer.write(""" """.join(_snake_case      ) + """\n"""      )
     index += 1

   return vocab_file, merge_file






  def 				UpperCAmelCase__						(							self			:					Tuple       ,  _snake_case			:					List[int]       ,  _snake_case			:					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]
   __lowerCAmelCase					:	List[str]      =       [self.cls_token_id]
   __lowerCAmelCase					:	Tuple      =       [self.sep_token_id]
   return cls + token_ids_a + sep + sep + token_ids_a + sep






  def 				UpperCAmelCase__						(							self			:					Optional[int]       ,  _snake_case			:					List[int]       ,  _snake_case			:					Optional[List[int]] = None       ,  _snake_case			:					bool = False      )->List[int]:






   '''simple docstring'''

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

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






  def 				UpperCAmelCase__						(							self			:					Dict       ,  _snake_case			:					List[int]       ,  _snake_case			:					Optional[List[int]] = None      )->List[int]:






   '''simple docstring'''

   __lowerCAmelCase					:	Any      =       [self.sep_token_id]
   __lowerCAmelCase					:	Union[str, 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			:					Dict       ,  _snake_case			:					List[str]       ,  _snake_case			:					Optional[Any]=False       ,  **_snake_case			:					int      )->Optional[int]:






   '''simple docstring'''

   __lowerCAmelCase					:	Union[str, Any]      =       kwargs.pop("""add_prefix_space"""       ,  self.add_prefix_space      )
   if (is_split_into_words or add_prefix_space) and (len(_snake_case      ) > 0 and not text[0].isspace()):
    __lowerCAmelCase					:	Union[str, Any]      =       """ """ + text
   return (text, kwargs)






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






   '''simple docstring'''

   __lowerCAmelCase					:	Tuple      =       super()._pad(
       encoded_inputs=_snake_case       ,  max_length=_snake_case       ,  padding_strategy=_snake_case       ,  pad_to_multiple_of=_snake_case       ,  return_attention_mask=_snake_case       ,  )

   # Load from model defaults
   if return_attention_mask is None:
    __lowerCAmelCase					:	Union[str, Any]      =       """attention_mask""" in self.model_input_names

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

    if needs_to_be_padded:
     __lowerCAmelCase					:	Optional[int]      =       len(_snake_case      ) - 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					:	Any      =       (
          encoded_inputs["""global_attention_mask"""] + [-1] * difference
      )
     elif self.padding_side == "left":
      __lowerCAmelCase					:	Union[str, Any]      =       [-1] * difference + encoded_inputs[
          """global_attention_mask"""
      ]
     else:
      raise ValueError("""Invalid padding strategy:""" + str(self.padding_side      )      )

   return encoded_inputs






from __future__ import annotations

import time

import numpy as np

_UpperCAmelCase             =							[8, 5, 9, 7]
_UpperCAmelCase             =							[
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
_UpperCAmelCase             =							[
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]






class        snake_case_    :






  def __init__(							self			:					Union[str, Any]       ,  _snake_case			:					list[int]       ,  _snake_case			:					list[list[int]]       ,  _snake_case			:					list[list[int]]       ,  )->None:






   '''simple docstring'''

   __lowerCAmelCase					:	str      =       claim_vector
   __lowerCAmelCase					:	List[Any]      =       allocated_resources_table
   __lowerCAmelCase					:	str      =       maximum_claim_table






  def 				UpperCAmelCase__						(							self			:					Tuple      )->list[int]:






   '''simple docstring'''

   return [
       sum(p_item[i] for p_item in self.__allocated_resources_table      )
       for i in range(len(self.__allocated_resources_table[0]      )      )
   ]






  def 				UpperCAmelCase__						(							self			:					int      )->list[int]:






   '''simple docstring'''

   return np.array(self.__claim_vector      ) - np.array(
       self.__processes_resource_summation()      )






  def 				UpperCAmelCase__						(							self			:					Optional[int]      )->list[list[int]]:






   '''simple docstring'''

   return [
       list(np.array(self.__maximum_claim_table[i]      ) - np.array(_snake_case      )      )
       for i, allocated_resource in enumerate(self.__allocated_resources_table      )
   ]






  def 				UpperCAmelCase__						(							self			:					Union[str, Any]      )->dict[int, list[int]]:






   '''simple docstring'''

   return {self.__need().index(_snake_case      ): i for i in self.__need()}






  def 				UpperCAmelCase__						(							self			:					Dict       ,  **_snake_case			:					Optional[Any]      )->None:






   '''simple docstring'''

   __lowerCAmelCase					:	Optional[int]      =       self.__need()
   __lowerCAmelCase					:	Any      =       self.__allocated_resources_table
   __lowerCAmelCase					:	List[Any]      =       self.__available_resources()
   __lowerCAmelCase					:	Optional[Any]      =       self.__need_index_manager()
   for kw, val in kwargs.items():
    if kw and val is True:
     self.__pretty_data()
   print("""_""" * 50 + """\n"""      )
   while need_list:
    __lowerCAmelCase					:	Optional[Any]      =       False
    for each_need in need_list:
     __lowerCAmelCase					:	Optional[int]      =       True
     for index, need in enumerate(_snake_case      ):
      if need > available_resources[index]:
       __lowerCAmelCase					:	int      =       False
       break
     if execution:
      __lowerCAmelCase					:	int      =       True
      # get the original index of the process from ind_ctrl db
      for original_need_index, need_clone in need_index_manager.items():
       if each_need == need_clone:
        __lowerCAmelCase					:	Any      =       original_need_index
      print(F'''Process {process_number + 1} is executing.'''      )
      # remove the process run from stack
      need_list.remove(_snake_case      )
      # update available/freed resources stack
      __lowerCAmelCase					:	int      =       np.array(_snake_case      ) + np.array(
          alloc_resources_table[process_number]      )
      print(
          """Updated available resource stack for processes: """
          + """ """.join([str(_snake_case      ) for x in available_resources]      )      )
      break
    if safe:
     print("""The process is in a safe state.\n"""      )
    else:
     print("""System in unsafe state. Aborting...\n"""      )
     break






  def 				UpperCAmelCase__						(							self			:					List[Any]      )->int:






   '''simple docstring'''

   print(""" """ * 9 + """Allocated Resource Table"""      )
   for item in self.__allocated_resources_table:
    print(
        F'''P{self.__allocated_resources_table.index(_snake_case      ) + 1}'''
        + """ """.join(F'''{it:>8}''' for it in item      )
        + """\n"""      )
   print(""" """ * 9 + """System Resource Table"""      )
   for item in self.__maximum_claim_table:
    print(
        F'''P{self.__maximum_claim_table.index(_snake_case      ) + 1}'''
        + """ """.join(F'''{it:>8}''' for it in item      )
        + """\n"""      )
   print(
       """Current Usage by Active Processes: """
       + """ """.join(str(_snake_case      ) for x in self.__claim_vector      )      )
   print(
       """Initial Available Resources:       """
       + """ """.join(str(_snake_case      ) for x in self.__available_resources()      )      )
   time.sleep(1      )


if __name__ == "__main__":
      import doctest

      doctest.testmod()