


from __future__ import annotations

import time

import numpy as np

SCREAMING_SNAKE_CASE       :      Optional[Any]												= [8, 5, 9, 7]
SCREAMING_SNAKE_CASE       :      int												= [
    [2, 0, 1, 1],
    [0, 1, 2, 1],
    [4, 0, 0, 3],
    [0, 2, 1, 0],
    [1, 0, 3, 0],
]
SCREAMING_SNAKE_CASE       :      Union[str, Any]												= [
    [3, 2, 1, 4],
    [0, 2, 5, 2],
    [5, 1, 0, 5],
    [1, 5, 3, 0],
    [3, 0, 3, 3],
]






class _lowerCamelCase:
       def __init__(					self,      lowerCamelCase,      lowerCamelCase,      lowerCamelCase,      )       ->   None:




           """simple docstring"""

           _lowercase       :							List[str]      		=		claim_vector
           _lowercase       :							int      		=		allocated_resources_table
           _lowercase       :							Dict      		=		maximum_claim_table
       def 			UpperCamelCase     (					self)       ->   list[int]:




           """simple docstring"""

           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]:




           """simple docstring"""

           return np.array(self.__claim_vector) - np.array(
               self.__processes_resource_summation())
       def 			UpperCamelCase     (					self)       ->   list[list[int]]:




           """simple docstring"""

           return [
               list(np.array(self.__maximum_claim_table[i]) - np.array(lowerCamelCase))
               for i, allocated_resource in enumerate(self.__allocated_resources_table)
           ]
       def 			UpperCamelCase     (					self)       ->   dict[int, list[int]]:




           """simple docstring"""

           return {self.__need().index(lowerCamelCase): i for i in self.__need()}
       def 			UpperCamelCase     (					self,      **lowerCamelCase)       ->   None:




           """simple docstring"""

           _lowercase       :							Union[str, Any]      		=		self.__need()
           _lowercase       :							List[str]      		=		self.__allocated_resources_table
           _lowercase       :							List[Any]      		=		self.__available_resources()
           _lowercase       :							Union[str, Any]      		=		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:
               _lowercase       :							int      		=		False
               for each_need in need_list:
                   _lowercase       :							Dict      		=		True
                   for index, need in enumerate(lowerCamelCase):
                       if need > available_resources[index]:
                           _lowercase       :							Tuple      		=		False
                           break
                   if execution:
                       _lowercase       :							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:
                               _lowercase       :							Tuple      		=		original_need_index
                       print(F'''Process {process_number + 1} is executing.''')
                       # remove the process run from stack
                       need_list.remove(lowerCamelCase)
                       # update available/freed resources stack
                       _lowercase       :							Optional[Any]      		=		np.array(lowerCamelCase) + np.array(
                           alloc_resources_table[process_number])
                       print(
                           'Updated available resource stack for processes: '
                           + ' '.join([str(lowerCamelCase) 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[Any]:




           """simple docstring"""

           print(' ' * 9 + 'Allocated Resource Table')
           for item in self.__allocated_resources_table:
               print(
                   F'''P{self.__allocated_resources_table.index(lowerCamelCase) + 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(lowerCamelCase) + 1}'''
                   + ' '.join(F'''{it:>8}''' for it in item)
                   + '\n')
           print(
               'Current Usage by Active Processes: '
               + ' '.join(str(lowerCamelCase) for x in self.__claim_vector))
           print(
               'Initial Available Resources:       '
               + ' '.join(str(lowerCamelCase) for x in self.__available_resources()))
           time.sleep(1)


if __name__ == "__main__":
 import doctest

 doctest.testmod()




import shutil
import tempfile
import unittest
from unittest.mock import patch

from transformers import (
    DefaultFlowCallback,
    IntervalStrategy,
    PrinterCallback,
    ProgressCallback,
    Trainer,
    TrainerCallback,
    TrainingArguments,
    is_torch_available,
)
from transformers.testing_utils import require_torch


if is_torch_available():
					from transformers.trainer import DEFAULT_CALLBACKS

					from .test_trainer import RegressionDataset, RegressionModelConfig, RegressionPreTrainedModel

class    lowerCAmelCase__     (	__lowercase			):






		def __init__(		self		:							int  )     ->							Optional[int]:
						__lowerCamelCase    					=	[]






		def  __A       (		self		:							Any							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							str							,			**SCREAMING_SNAKE_CASE__		:							List[Any]  )     ->							Tuple:
						self.events.append('''on_init_end'''  )






		def  __A       (		self		:							Tuple							,			SCREAMING_SNAKE_CASE__		:							Optional[int]							,			SCREAMING_SNAKE_CASE__		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							Optional[int]							,			**SCREAMING_SNAKE_CASE__		:							Optional[Any]  )     ->							Any:
						self.events.append('''on_train_begin'''  )






		def  __A       (		self		:							str							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							Any							,			SCREAMING_SNAKE_CASE__		:							Dict							,			**SCREAMING_SNAKE_CASE__		:							int  )     ->							Any:
						self.events.append('''on_train_end'''  )






		def  __A       (		self		:							Union[str, Any]							,			SCREAMING_SNAKE_CASE__		:							Dict							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			**SCREAMING_SNAKE_CASE__		:							List[Any]  )     ->							int:
						self.events.append('''on_epoch_begin'''  )






		def  __A       (		self		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							Any							,			SCREAMING_SNAKE_CASE__		:							Optional[Any]							,			**SCREAMING_SNAKE_CASE__		:							Tuple  )     ->							Optional[Any]:
						self.events.append('''on_epoch_end'''  )






		def  __A       (		self		:							str							,			SCREAMING_SNAKE_CASE__		:							Tuple							,			SCREAMING_SNAKE_CASE__		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							Union[str, Any]							,			**SCREAMING_SNAKE_CASE__		:							str  )     ->							List[Any]:
						self.events.append('''on_step_begin'''  )






		def  __A       (		self		:							Any							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							Any							,			**SCREAMING_SNAKE_CASE__		:							Optional[int]  )     ->							Tuple:
						self.events.append('''on_step_end'''  )






		def  __A       (		self		:							int							,			SCREAMING_SNAKE_CASE__		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							int							,			**SCREAMING_SNAKE_CASE__		:							List[Any]  )     ->							Union[str, Any]:
						self.events.append('''on_evaluate'''  )






		def  __A       (		self		:							Union[str, Any]							,			SCREAMING_SNAKE_CASE__		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							str							,			**SCREAMING_SNAKE_CASE__		:							str  )     ->							str:
						self.events.append('''on_predict'''  )






		def  __A       (		self		:							Optional[int]							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							Optional[int]							,			**SCREAMING_SNAKE_CASE__		:							Optional[Any]  )     ->							Tuple:
						self.events.append('''on_save'''  )






		def  __A       (		self		:							Optional[int]							,			SCREAMING_SNAKE_CASE__		:							Dict							,			SCREAMING_SNAKE_CASE__		:							Union[str, Any]							,			SCREAMING_SNAKE_CASE__		:							Union[str, Any]							,			**SCREAMING_SNAKE_CASE__		:							List[str]  )     ->							List[str]:
						self.events.append('''on_log'''  )







		def  __A       (		self		:							int							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							List[Any]							,			**SCREAMING_SNAKE_CASE__		:							Optional[int]  )     ->							str:
						self.events.append('''on_prediction_step'''  )





@require_torch
class    lowerCAmelCase__     (	unittest.TestCase			):






		def  __A       (		self		:							Union[str, Any]  )     ->							Optional[Any]:
						__lowerCamelCase    					=	tempfile.mkdtemp()






		def  __A       (		self		:							int  )     ->							List[str]:
						shutil.rmtree(self.output_dir  )






		def  __A       (		self		:							Tuple							,			SCREAMING_SNAKE_CASE__		:							List[Any]=0							,			SCREAMING_SNAKE_CASE__		:							Any=0							,			SCREAMING_SNAKE_CASE__		:							List[str]=64							,			SCREAMING_SNAKE_CASE__		:							Optional[int]=64							,			SCREAMING_SNAKE_CASE__		:							Optional[int]=None							,			SCREAMING_SNAKE_CASE__		:							Optional[int]=False							,			**SCREAMING_SNAKE_CASE__		:							Optional[Any]  )     ->							Union[str, Any]:
						# disable_tqdm in TrainingArguments has a flaky default since it depends on the level of logging. We make sure
						# its set to False since the tests later on depend on its value.
						__lowerCamelCase    					=	RegressionDataset(length=SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase    					=	RegressionDataset(length=SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase    					=	RegressionModelConfig(a=SCREAMING_SNAKE_CASE__							,			b=SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase    					=	RegressionPreTrainedModel(SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	TrainingArguments(self.output_dir							,			disable_tqdm=SCREAMING_SNAKE_CASE__							,			report_to=[]							,			**SCREAMING_SNAKE_CASE__  )
						return Trainer(
						    SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__							,			train_dataset=SCREAMING_SNAKE_CASE__							,			eval_dataset=SCREAMING_SNAKE_CASE__							,			callbacks=SCREAMING_SNAKE_CASE__							,			)






		def  __A       (		self		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							str  )     ->							Optional[int]:
						self.assertEqual(len(SCREAMING_SNAKE_CASE__  )							,			len(SCREAMING_SNAKE_CASE__  )  )

						# Order doesn't matter
						__lowerCamelCase    					=	sorted(SCREAMING_SNAKE_CASE__							,			key=lambda SCREAMING_SNAKE_CASE__  : cb.__name__ if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else cb.__class__.__name__  )
						__lowerCamelCase    					=	sorted(SCREAMING_SNAKE_CASE__							,			key=lambda SCREAMING_SNAKE_CASE__  : cb.__name__ if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else cb.__class__.__name__  )

						for cba, cba in zip(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ):
										if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) and isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ):
														self.assertEqual(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  )
										elif isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) and not isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ):
														self.assertEqual(SCREAMING_SNAKE_CASE__							,			cba.__class__  )
										elif not isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) and isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ):
														self.assertEqual(cba.__class__							,			SCREAMING_SNAKE_CASE__  )
										else:
														self.assertEqual(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  )






		def  __A       (		self		:							Union[str, Any]							,			SCREAMING_SNAKE_CASE__		:							Optional[int]  )     ->							Tuple:
						__lowerCamelCase    					=	['''on_init_end''', '''on_train_begin''']
						__lowerCamelCase    					=	0
						__lowerCamelCase    					=	len(trainer.get_eval_dataloader()  )
						__lowerCamelCase    					=	['''on_prediction_step'''] * len(trainer.get_eval_dataloader()  ) + ['''on_log''', '''on_evaluate''']
						for _ in range(trainer.state.num_train_epochs  ):
										expected_events.append('''on_epoch_begin'''  )
										for _ in range(SCREAMING_SNAKE_CASE__  ):
														step += 1
														expected_events += ["on_step_begin", "on_step_end"]
														if step % trainer.args.logging_steps == 0:
																		expected_events.append('''on_log'''  )
														if trainer.args.evaluation_strategy == IntervalStrategy.STEPS and step % trainer.args.eval_steps == 0:
																		expected_events += evaluation_events.copy()
														if step % trainer.args.save_steps == 0:
																		expected_events.append('''on_save'''  )
										expected_events.append('''on_epoch_end'''  )
										if trainer.args.evaluation_strategy == IntervalStrategy.EPOCH:
														expected_events += evaluation_events.copy()
						expected_events += ["on_log", "on_train_end"]
						return expected_events






		def  __A       (		self		:							Union[str, Any]  )     ->							int:
						__lowerCamelCase    					=	self.get_trainer()
						__lowerCamelCase    					=	DEFAULT_CALLBACKS.copy() + [ProgressCallback]
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )

						# Callbacks passed at init are added to the default callbacks
						__lowerCamelCase    					=	self.get_trainer(callbacks=[MyTestTrainerCallback]  )
						expected_callbacks.append(SCREAMING_SNAKE_CASE__  )
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )

						# TrainingArguments.disable_tqdm controls if use ProgressCallback or PrinterCallback
						__lowerCamelCase    					=	self.get_trainer(disable_tqdm=SCREAMING_SNAKE_CASE__  )
						__lowerCamelCase    					=	DEFAULT_CALLBACKS.copy() + [PrinterCallback]
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )






		def  __A       (		self		:							List[Any]  )     ->							str:
						__lowerCamelCase    					=	DEFAULT_CALLBACKS.copy() + [ProgressCallback]
						__lowerCamelCase    					=	self.get_trainer()

						# We can add, pop, or remove by class name
						trainer.remove_callback(SCREAMING_SNAKE_CASE__  )
						expected_callbacks.remove(SCREAMING_SNAKE_CASE__  )
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	self.get_trainer()
						__lowerCamelCase    					=	trainer.pop_callback(SCREAMING_SNAKE_CASE__  )
						self.assertEqual(cb.__class__							,			SCREAMING_SNAKE_CASE__  )
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )

						trainer.add_callback(SCREAMING_SNAKE_CASE__  )
						expected_callbacks.insert(0							,			SCREAMING_SNAKE_CASE__  )
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )

						# We can also add, pop, or remove by instance
						__lowerCamelCase    					=	self.get_trainer()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[0]
						trainer.remove_callback(SCREAMING_SNAKE_CASE__  )
						expected_callbacks.remove(SCREAMING_SNAKE_CASE__  )
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	self.get_trainer()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[0]
						__lowerCamelCase    					=	trainer.pop_callback(SCREAMING_SNAKE_CASE__  )
						self.assertEqual(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  )
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )

						trainer.add_callback(SCREAMING_SNAKE_CASE__  )
						expected_callbacks.insert(0							,			SCREAMING_SNAKE_CASE__  )
						self.check_callbacks_equality(trainer.callback_handler.callbacks							,			SCREAMING_SNAKE_CASE__  )







		def  __A       (		self		:							Union[str, Any]  )     ->							Any:
						import warnings

						# XXX: for now ignore scatter_gather warnings in this test since it's not relevant to what's being tested
						warnings.simplefilter(action='''ignore'''							,			category=SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	self.get_trainer(callbacks=[MyTestTrainerCallback]  )
						trainer.train()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[-2].events
						self.assertEqual(SCREAMING_SNAKE_CASE__							,			self.get_expected_events(SCREAMING_SNAKE_CASE__  )  )

						# Independent log/save/eval
						__lowerCamelCase    					=	self.get_trainer(callbacks=[MyTestTrainerCallback]							,			logging_steps=5  )
						trainer.train()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[-2].events
						self.assertEqual(SCREAMING_SNAKE_CASE__							,			self.get_expected_events(SCREAMING_SNAKE_CASE__  )  )

						__lowerCamelCase    					=	self.get_trainer(callbacks=[MyTestTrainerCallback]							,			save_steps=5  )
						trainer.train()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[-2].events
						self.assertEqual(SCREAMING_SNAKE_CASE__							,			self.get_expected_events(SCREAMING_SNAKE_CASE__  )  )

						__lowerCamelCase    					=	self.get_trainer(callbacks=[MyTestTrainerCallback]							,			eval_steps=5							,			evaluation_strategy='''steps'''  )
						trainer.train()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[-2].events
						self.assertEqual(SCREAMING_SNAKE_CASE__							,			self.get_expected_events(SCREAMING_SNAKE_CASE__  )  )

						__lowerCamelCase    					=	self.get_trainer(callbacks=[MyTestTrainerCallback]							,			evaluation_strategy='''epoch'''  )
						trainer.train()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[-2].events
						self.assertEqual(SCREAMING_SNAKE_CASE__							,			self.get_expected_events(SCREAMING_SNAKE_CASE__  )  )

						# A bit of everything
						__lowerCamelCase    					=	self.get_trainer(
						    callbacks=[MyTestTrainerCallback]							,			logging_steps=3							,			save_steps=10							,			eval_steps=5							,			evaluation_strategy='''steps'''							,			)
						trainer.train()
						__lowerCamelCase    					=	trainer.callback_handler.callbacks[-2].events
						self.assertEqual(SCREAMING_SNAKE_CASE__							,			self.get_expected_events(SCREAMING_SNAKE_CASE__  )  )

						# warning should be emitted for duplicated callbacks
						with patch('''transformers.trainer_callback.logger.warning'''  ) as warn_mock:
										__lowerCamelCase    					=	self.get_trainer(
										    callbacks=[MyTestTrainerCallback, MyTestTrainerCallback]							,			)
										assert str(SCREAMING_SNAKE_CASE__  ) in warn_mock.call_args[0][0]



