
from __future__ import annotations

import time

import numpy as np

__a         =   [8, 5, 9, 7]
__a         =   [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
__a         =   [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]
class 					lowercase__:



	"""simple docstring"""




	def __init__(			self    :     int			,				SCREAMING_SNAKE_CASE_    :     list[int]			,				SCREAMING_SNAKE_CASE_    :     list[list[int]]			,				SCREAMING_SNAKE_CASE_    :     list[list[int]]			,				)			->	None:
					lowercase_	    =   claim_vector
					lowercase_	    =   allocated_resources_table
					lowercase_	    =   maximum_claim_table
	def 		_lowercase    (			self    :     Dict			)			->	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 		_lowercase    (			self    :     int			)			->	list[int]:
					return np.array(self.__claim_vector			) - np.array(
					    self.__processes_resource_summation()			)
	def 		_lowercase    (			self    :     Tuple			)			->	list[list[int]]:
					return [
					    list(np.array(self.__maximum_claim_table[i]			) - np.array(SCREAMING_SNAKE_CASE_			)			)
					    for i, allocated_resource in enumerate(self.__allocated_resources_table			)
					]
	def 		_lowercase    (			self    :     List[str]			)			->	dict[int, list[int]]:
					return {self.__need().index(SCREAMING_SNAKE_CASE_			): i for i in self.__need()}
	def 		_lowercase    (			self    :     Tuple			,				**SCREAMING_SNAKE_CASE_    :     List[Any]			)			->	None:
					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(SCREAMING_SNAKE_CASE_			):
																	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(SCREAMING_SNAKE_CASE_			)
																	# update available/freed resources stack
																	lowercase_	    =   np.array(SCREAMING_SNAKE_CASE_			) + np.array(
																	    alloc_resources_table[process_number]			)
																	print(
																	    '''Updated available resource stack for processes: '''
																	    + ''' '''.join([str(SCREAMING_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 		_lowercase    (			self    :     Tuple			)			->	Optional[Any]:
					print(''' ''' * 9 + '''Allocated Resource Table'''			)
					for item in self.__allocated_resources_table:
									print(
									    f'''P{self.__allocated_resources_table.index(SCREAMING_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(SCREAMING_SNAKE_CASE_			) + 1}'''
									    + ''' '''.join(f'''{it:>8}''' for it in item			)
									    + '''\n'''			)
					print(
					    '''Current Usage by Active Processes: '''
					    + ''' '''.join(str(SCREAMING_SNAKE_CASE_			) for x in self.__claim_vector			)			)
					print(
					    '''Initial Available Resources:       '''
					    + ''' '''.join(str(SCREAMING_SNAKE_CASE_			) for x in self.__available_resources()			)			)
					time.sleep(1			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()









from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_								=       logging.get_logger(__name__)

a_								=       {
    """google/canine-s""": """https://huggingface.co/google/canine-s/resolve/main/config.json""",
    # See all CANINE models at https://huggingface.co/models?filter=canine
}



class 			__lowerCAmelCase  (						lowerCAmelCase__ ):
 lowerCAmelCase__							       =	"""canine"""




 def __init__(    self						,					__UpperCAmelCase=768						,					__UpperCAmelCase=12						,					__UpperCAmelCase=12						,					__UpperCAmelCase=3072						,					__UpperCAmelCase="gelu"						,					__UpperCAmelCase=0.1						,					__UpperCAmelCase=0.1						,					__UpperCAmelCase=16384						,					__UpperCAmelCase=16						,					__UpperCAmelCase=0.02						,					__UpperCAmelCase=1E-1_2						,					__UpperCAmelCase=0						,					__UpperCAmelCase=0Xe_000						,					__UpperCAmelCase=0Xe_001						,					__UpperCAmelCase=4						,					__UpperCAmelCase=4						,					__UpperCAmelCase=8						,					__UpperCAmelCase=16384						,					__UpperCAmelCase=128						,					**__UpperCAmelCase						,					):



    '''simple docstring'''
    super().__init__(pad_token_id=__UpperCAmelCase						,					bos_token_id=__UpperCAmelCase						,					eos_token_id=__UpperCAmelCase						,					**__UpperCAmelCase					)

    __lowerCamelCase    				=     max_position_embeddings
    __lowerCamelCase    				=     hidden_size
    __lowerCamelCase    				=     num_hidden_layers
    __lowerCamelCase    				=     num_attention_heads
    __lowerCamelCase    				=     intermediate_size
    __lowerCamelCase    				=     hidden_act
    __lowerCamelCase    				=     hidden_dropout_prob
    __lowerCamelCase    				=     attention_probs_dropout_prob
    __lowerCamelCase    				=     initializer_range
    __lowerCamelCase    				=     type_vocab_size
    __lowerCamelCase    				=     layer_norm_eps

    # Character config:
    __lowerCamelCase    				=     downsampling_rate
    __lowerCamelCase    				=     upsampling_kernel_size
    __lowerCamelCase    				=     num_hash_functions
    __lowerCamelCase    				=     num_hash_buckets
    __lowerCamelCase    				=     local_transformer_stride






