
"""simple docstring"""




from __future__ import annotations

import time

import numpy as np

lowercase__		:Tuple			  =   [8, 5, 9, 7]
lowercase__		:Tuple			  =   [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
lowercase__		:Dict			  =   [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]







class     lowercase		:




							def __init__(    self       ,A__       ,A__       ,A__       ,):
												lowercase						     =						claim_vector
												lowercase						     =						allocated_resources_table
												lowercase						     =						maximum_claim_table




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




							def 			A__				(    self):
												return np.array(self.__claim_vector) - np.array(
												    self.__processes_resource_summation())




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




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




							def 			A__				(    self       ,**A__):
												lowercase						     =						self.__need()
												lowercase						     =						self.__allocated_resources_table
												lowercase						     =						self.__available_resources()
												lowercase						     =						self.__need_index_manager()
												for kw, val in kwargs.items():
																	if kw and val is True:
																						self.__pretty_data()
												print('''_''' * 5_0 + '''\n''')
												while need_list:
																	lowercase						     =						False
																	for each_need in need_list:
																						lowercase						     =						True
																						for index, need in enumerate(A__):
																											if need > available_resources[index]:
																																lowercase						     =						False
																																break
																						if execution:
																											lowercase						     =						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:
																																					lowercase						     =						original_need_index
																											print(f'Process {process_number + 1} is executing.')
																											# remove the process run from stack
																											need_list.remove(A__)
																											# update available/freed resources stack
																											lowercase						     =						np.array(A__) + np.array(
																											    alloc_resources_table[process_number])
																											print(
																											    '''Updated available resource stack for processes: '''
																											    + ''' '''.join([str(A__) 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 			A__				(    self):
												print(''' ''' * 9 + '''Allocated Resource Table''')
												for item in self.__allocated_resources_table:
																	print(
																	    f'P{self.__allocated_resources_table.index(A__) + 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(A__) + 1}'
																	    + ''' '''.join(f'{it:>8}' for it in item)
																	    + '''\n''')
												print(
												    '''Current Usage by Active Processes: '''
												    + ''' '''.join(str(A__) for x in self.__claim_vector))
												print(
												    '''Initial Available Resources:       '''
												    + ''' '''.join(str(A__) for x in self.__available_resources()))
												time.sleep(1)


if __name__ == "__main__":
							import doctest

							doctest.testmod()






import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict







@dataclass
class     lowercase		( SCREAMING_SNAKE_CASE__		):
							lowercase_	:	int	 =ComputeEnvironment.AMAZON_SAGEMAKER
							lowercase_	:	Optional[int]	 =True
							lowercase_	:	Any	 ='''ml.p3.2xlarge'''
							lowercase_	:	Any	 ='''accelerate_sagemaker_execution_role'''
							lowercase_	:	Union[str, Any]	 ='''hf-sm'''
							lowercase_	:	Any	 ='''us-east-1'''
							lowercase_	:	List[str]	 =1
							lowercase_	:	Any	 ='''accelerate-sagemaker-1'''
							lowercase_	:	Union[str, Any]	 ='''1.6'''
							lowercase_	:	Any	 ='''4.4'''
							lowercase_	:	Any	 ='''train.py'''
							lowercase_	:	int	 =[
							    '''--model_name_or_path''',
							    '''bert''',
							    '''--do_train''',
							    '''False''',
							    '''--epochs''',
							    '''3''',
							    '''--learning_rate''',
							    '''5e-5''',
							    '''--max_steps''',
							    '''50.5''',
							]
							lowercase_	:	List[Any]	 =[
							    '''--model_name_or_path''',
							    '''bert''',
							    '''--do_train''',
							    '''--do_test''',
							    '''False''',
							    '''--do_predict''',
							    '''--epochs''',
							    '''3''',
							    '''--learning_rate''',
							    '''5e-5''',
							    '''--max_steps''',
							    '''50.5''',
							]







class     lowercase		( unittest.TestCase		):




							def 			A__				(    self):
												# If no defaults are changed, `to_kwargs` returns an empty dict.
												lowercase						     =						_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args)
												assert isinstance(converted_args['''model_name_or_path''']       ,A__)
												assert isinstance(converted_args['''do_train''']       ,A__)
												assert isinstance(converted_args['''epochs''']       ,A__)
												assert isinstance(converted_args['''learning_rate''']       ,A__)
												assert isinstance(converted_args['''max_steps''']       ,A__)

												with pytest.raises(A__):
																	_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args)




