


'''simple docstring'''






from __future__ import annotations

import time

import numpy as np

a_   :      Tuple				    =      [8, 5, 9, 7]
a_   :      Optional[int]				    =      [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
a_   :      Optional[Any]				    =      [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]




class 	a       :
 def __init__(	self ,			__magic_name__ ,			__magic_name__ ,			__magic_name__ ,			)   ->							None:
      _a      =							claim_vector
      _a      =							allocated_resources_table
      _a      =							maximum_claim_table
 def 							__UpperCAmelCase						(	self  )   ->							list[int]:
      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  )   ->							list[int]:
      return np.array(self.__claim_vector  ) - np.array(
          self.__processes_resource_summation()  )
 def 							__UpperCAmelCase						(	self  )   ->							list[list[int]]:
      return [
          list(np.array(self.__maximum_claim_table[i]  ) - np.array(__magic_name__  )  )
          for i, allocated_resource in enumerate(self.__allocated_resources_table  )
      ]
 def 							__UpperCAmelCase						(	self  )   ->							dict[int, list[int]]:
      return {self.__need().index(__magic_name__  ): i for i in self.__need()}
 def 							__UpperCAmelCase						(	self ,			**__magic_name__  )   ->							None:
      _a      =							self.__need()
      _a      =							self.__allocated_resources_table
      _a      =							self.__available_resources()
      _a      =							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:
           _a      =							False
           for each_need in need_list:
                _a      =							True
                for index, need in enumerate(__magic_name__  ):
                     if need > available_resources[index]:
                          _a      =							False
                          break
                if execution:
                     _a      =							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:
                               _a      =							original_need_index
                     print(f'Process {process_number + 1} is executing.'  )
                     # remove the process run from stack
                     need_list.remove(__magic_name__  )
                     # update available/freed resources stack
                     _a      =							np.array(__magic_name__  ) + np.array(
                         alloc_resources_table[process_number]  )
                     print(
                         'Updated available resource stack for processes: '
                         + ' '.join([str(__magic_name__  ) 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[str]:
      print(' ' * 9 + 'Allocated Resource Table'  )
      for item in self.__allocated_resources_table:
           print(
               f'P{self.__allocated_resources_table.index(__magic_name__  ) + 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(__magic_name__  ) + 1}'
               + ' '.join(f'{it:>8}' for it in item  )
               + '\n'  )
      print(
          'Current Usage by Active Processes: '
          + ' '.join(str(__magic_name__  ) for x in self.__claim_vector  )  )
      print(
          'Initial Available Resources:       '
          + ' '.join(str(__magic_name__  ) for x in self.__available_resources()  )  )
      time.sleep(1  )


if __name__ == "__main__":
 import doctest

 doctest.testmod()





'''simple docstring'''






from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


a_   :      List[Any]				    =      {"configuration_gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfig"]}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_   :      List[str]				    =      ["GPTNeoXTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_   :      List[Any]				    =      [
     "GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST",
     "GPTNeoXForCausalLM",
     "GPTNeoXForQuestionAnswering",
     "GPTNeoXForSequenceClassification",
     "GPTNeoXForTokenClassification",
     "GPTNeoXLayer",
     "GPTNeoXModel",
     "GPTNeoXPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_neox import (
      GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTNeoXForCausalLM,
      GPTNeoXForQuestionAnswering,
      GPTNeoXForSequenceClassification,
      GPTNeoXForTokenClassification,
      GPTNeoXLayer,
      GPTNeoXModel,
      GPTNeoXPreTrainedModel,
  )


else:
 import sys

 a_   :      Optional[Any]				    =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

