

"""simple docstring"""





from __future__ import annotations

import time

import numpy as np

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







class 							SCREAMING_SNAKE_CASE   :






					"""simple docstring"""



					def __init__(			self     :							str  ,lowercase_     :							list[int]  ,lowercase_     :							list[list[int]]  ,lowercase_     :							list[list[int]]  ,):
						lowerCAmelCase__      :		Dict    							=      claim_vector
						lowerCAmelCase__      :		Union[str, Any]    							=      allocated_resources_table
						lowerCAmelCase__      :		str    							=      maximum_claim_table







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







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







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







					def 			__lowerCAmelCase					(			self     :							Union[str, Any]						):
						return {self.__need().index(lowercase_						): i for i in self.__need()}







					def 			__lowerCAmelCase					(			self     :							Tuple  ,**lowercase_     :							Tuple						):
						lowerCAmelCase__      :		Optional[int]    							=      self.__need()
						lowerCAmelCase__      :		str    							=      self.__allocated_resources_table
						lowerCAmelCase__      :		int    							=      self.__available_resources()
						lowerCAmelCase__      :		List[Any]    							=      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:
							lowerCAmelCase__      :		Optional[Any]    							=      False
							for each_need in need_list:
								lowerCAmelCase__      :		Optional[int]    							=      True
								for index, need in enumerate(lowercase_						):
									if need > available_resources[index]:
										lowerCAmelCase__      :		Union[str, Any]    							=      False
										break
								if execution:
									lowerCAmelCase__      :		Tuple    							=      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__      :		int    							=      original_need_index
									print(F'Process {process_number + 1} is executing.'						)
									# remove the process run from stack
									need_list.remove(lowercase_						)
									# update available/freed resources stack
									lowerCAmelCase__      :		int    							=      np.array(lowercase_						) + np.array(
									    alloc_resources_table[process_number]						)
									print(
									    '''Updated available resource stack for processes: '''
									    + ''' '''.join([str(lowercase_						) 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 			__lowerCAmelCase					(			self     :							Optional[Any]						):
						print(''' ''' * 9 + '''Allocated Resource Table'''						)
						for item in self.__allocated_resources_table:
							print(
							    F'P{self.__allocated_resources_table.index(lowercase_						) + 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(lowercase_						) + 1}'
							    + ''' '''.join(F'{it:>8}' for it in item						)
							    + '''\n'''						)
						print(
						    '''Current Usage by Active Processes: '''
						    + ''' '''.join(str(lowercase_						) for x in self.__claim_vector						)						)
						print(
						    '''Initial Available Resources:       '''
						    + ''' '''.join(str(lowercase_						) for x in self.__available_resources()						)						)
						time.sleep(1						)


if __name__ == "__main__":
							import doctest

							doctest.testmod()







"""simple docstring"""





from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


__UpperCamelCase    : List[Any]				 =						logging.get_logger(__name__)

__UpperCamelCase    : Any				 =						{
    '''t5-small''': '''https://huggingface.co/t5-small/resolve/main/config.json''',
    '''t5-base''': '''https://huggingface.co/t5-base/resolve/main/config.json''',
    '''t5-large''': '''https://huggingface.co/t5-large/resolve/main/config.json''',
    '''t5-3b''': '''https://huggingface.co/t5-3b/resolve/main/config.json''',
    '''t5-11b''': '''https://huggingface.co/t5-11b/resolve/main/config.json''',
}







class 							SCREAMING_SNAKE_CASE   (						a_			):






					"""simple docstring"""



					lowercase__												=			"t5"
					lowercase__												=			["past_key_values"]
					lowercase__												=			{"hidden_size": "d_model", "num_attention_heads": "num_heads", "num_hidden_layers": "num_layers"}







					def __init__(			self     :							Tuple  ,lowercase_     :							Tuple=3_2_1_2_8  ,lowercase_     :							Union[str, Any]=5_1_2  ,lowercase_     :							Dict=6_4  ,lowercase_     :							Any=2_0_4_8  ,lowercase_     :							Dict=6  ,lowercase_     :							Dict=None  ,lowercase_     :							Dict=8  ,lowercase_     :							Optional[int]=3_2  ,lowercase_     :							List[Any]=1_2_8  ,lowercase_     :							Any=0.1  ,lowercase_     :							Optional[Any]=1E-6  ,lowercase_     :							Any=1.0  ,lowercase_     :							Dict="relu"  ,lowercase_     :							Tuple=True  ,lowercase_     :							List[Any]=True  ,lowercase_     :							Tuple=0  ,lowercase_     :							Optional[Any]=1  ,**lowercase_     :							Any  ,):
						lowerCAmelCase__      :		Tuple    							=      vocab_size
						lowerCAmelCase__      :		List[str]    							=      d_model
						lowerCAmelCase__      :		Union[str, Any]    							=      d_kv
						lowerCAmelCase__      :		List[Any]    							=      d_ff
						lowerCAmelCase__      :		int    							=      num_layers
						lowerCAmelCase__      :		Union[str, Any]    							=      (
						    num_decoder_layers if num_decoder_layers is not None else self.num_layers
						)  # default = symmetry
						lowerCAmelCase__      :		Any    							=      num_heads
						lowerCAmelCase__      :		Optional[int]    							=      relative_attention_num_buckets
						lowerCAmelCase__      :		Union[str, Any]    							=      relative_attention_max_distance
						lowerCAmelCase__      :		List[Any]    							=      dropout_rate
						lowerCAmelCase__      :		str    							=      layer_norm_epsilon
						lowerCAmelCase__      :		int    							=      initializer_factor
						lowerCAmelCase__      :		Dict    							=      feed_forward_proj
						lowerCAmelCase__      :		int    							=      use_cache

						lowerCAmelCase__      :		int    							=      self.feed_forward_proj.split('''-'''						)
						lowerCAmelCase__      :		str    							=      act_info[-1]
						lowerCAmelCase__      :		Tuple    							=      act_info[0] == '''gated'''

						if len(lowercase_						) > 1 and act_info[0] != "gated" or len(lowercase_						) > 2:
							raise ValueError(
							    F'`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'
							    '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
							    '''\'gated-gelu\' or \'relu\''''						)

						# for backwards compatibility
						if feed_forward_proj == "gated-gelu":
							lowerCAmelCase__      :		Tuple    							=      '''gelu_new'''

						super().__init__(
						    pad_token_id=lowercase_  ,eos_token_id=lowercase_  ,is_encoder_decoder=lowercase_  ,**lowercase_  ,)







class 							SCREAMING_SNAKE_CASE   (						a_			):






					"""simple docstring"""



					@property
					def 			__lowerCAmelCase					(			self     :							List[Any]						):
						lowerCAmelCase__      :		int    							=      {
						    '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
						    '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
						}
						if self.use_past:
							lowerCAmelCase__      :		Union[str, Any]    							=      '''past_encoder_sequence + sequence'''
							lowerCAmelCase__      :		List[Any]    							=      {0: '''batch'''}
							lowerCAmelCase__      :		Union[str, Any]    							=      {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
						else:
							lowerCAmelCase__      :		Union[str, Any]    							=      {0: '''batch''', 1: '''decoder_sequence'''}
							lowerCAmelCase__      :		Any    							=      {0: '''batch''', 1: '''decoder_sequence'''}

						if self.use_past:
							self.fill_with_past_key_values_(lowercase_  ,direction='''inputs'''						)

						return common_inputs







					@property
					def 			__lowerCAmelCase					(			self     :							Optional[int]						):
						return 1_3




