

from __future__ import annotations

import time

import numpy as np

_UpperCAmelCase		:   Union[str, Any]										=       [8, 5, 9, 7]
_UpperCAmelCase		:   Dict										=       [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
_UpperCAmelCase		:   Optional[Any]										=       [
    [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      ,   snake_case      ,   snake_case      ,   snake_case      ,   ):
											snake_case_							=    claim_vector
											snake_case_							=    allocated_resources_table
											snake_case_							=    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(snake_case       )       )
											    for i, allocated_resource in enumerate(self.__allocated_resources_table       )
											]




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




				def     a							(					self      ,   **snake_case       ):
											snake_case_							=    self.__need()
											snake_case_							=    self.__allocated_resources_table
											snake_case_							=    self.__available_resources()
											snake_case_							=    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:
																		snake_case_							=    False
																		for each_need in need_list:
																									snake_case_							=    True
																									for index, need in enumerate(snake_case       ):
																																if need > available_resources[index]:
																																							snake_case_							=    False
																																							break
																									if execution:
																																snake_case_							=    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:
																																														snake_case_							=    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
																																snake_case_							=    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     a							(					self       ):
											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()







import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser





def 					__lowerCamelCase	( UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    {}
							snake_case_							=    tokenizer(example['content']   ,							truncation=UpperCamelCase__      )['input_ids']
							snake_case_							=    len(example['content']      ) / len(output['input_ids']      )
							return output


_UpperCAmelCase		:   Dict										=       HfArgumentParser(PretokenizationArguments)
_UpperCAmelCase		:   List[Any]										=       parser.parse_args()
if args.num_workers is None:
					_UpperCAmelCase		:   Union[str, Any]										=       multiprocessing.cpu_count()
_UpperCAmelCase		:   int										=       AutoTokenizer.from_pretrained(args.tokenizer_dir)

_UpperCAmelCase		:   Optional[int]										=       time.time()
_UpperCAmelCase		:   List[str]										=       load_dataset(args.dataset_name, split="""train""")
print(F'''Dataset loaded in {time.time()-t_start:.2f}s''')

_UpperCAmelCase		:   Tuple										=       time.time()
_UpperCAmelCase		:   Union[str, Any]										=       ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        """repo_name""",
        """path""",
        """copies""",
        """size""",
        """content""",
        """license""",
        """hash""",
        """line_mean""",
        """line_max""",
        """alpha_frac""",
        """autogenerated""",
    ],
)
print(F'''Dataset tokenized in {time.time()-t_start:.2f}s''')

_UpperCAmelCase		:   Dict										=       time.time()
ds.push_to_hub(args.tokenized_data_repo)


print(F'''Data pushed to the hub in {time.time()-t_start:.2f}s''')




