






"""simple docstring"""

import unittest

import torch
from torch import nn

from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory






def _lowerCAmelCase	(  ):

						'''simple docstring'''






						raise RuntimeError("CUDA out of memory."   )

class 						A_							(      nn.Module  ):







				def __init__(							self							:						int	)				->					List[str]:
										super().__init__()
										__magic_name__            =     nn.Linear(3						,    4	)
										__magic_name__            =     nn.BatchNormad(4	)
										__magic_name__            =     nn.Linear(4						,    5	)







				def     _snake_case					(							self							:						Union[str, Any]						,    __lowerCamelCase							:						Any	)				->					List[Any]:
										return self.lineara(self.batchnorm(self.lineara(_SCREAMING_SNAKE_CASE	)	)	)





class 						A_							(      unittest.TestCase  ):







				def     _snake_case					(							self							:						str	)				->					Tuple:
										__magic_name__            =     []

										@find_executable_batch_size(starting_batch_size=1_2_8	)
										def mock_training_loop_function(__lowerCamelCase							:						Optional[int]	):
																nonlocal batch_sizes
																batch_sizes.append(_SCREAMING_SNAKE_CASE	)
																if batch_size != 8:
																						raise_fake_out_of_memory()

										mock_training_loop_function()
										self.assertListEqual(_SCREAMING_SNAKE_CASE						,    [1_2_8, 6_4, 3_2, 1_6, 8]	)







				def     _snake_case					(							self							:						Tuple	)				->					List[str]:
										__magic_name__            =     []

										@find_executable_batch_size(starting_batch_size=1_2_8	)
										def mock_training_loop_function(__lowerCamelCase							:						Any						,    __lowerCamelCase							:						Optional[Any]	):
																nonlocal batch_sizes
																batch_sizes.append(_SCREAMING_SNAKE_CASE	)
																if batch_size != 8:
																						raise_fake_out_of_memory()
																return batch_size, arga

										__magic_name__      ,    __magic_name__            =     mock_training_loop_function("hello"	)
										self.assertListEqual(_SCREAMING_SNAKE_CASE						,    [1_2_8, 6_4, 3_2, 1_6, 8]	)
										self.assertListEqual([bs, arga]						,    [8, "hello"]	)







				def     _snake_case					(							self							:						Optional[Any]	)				->					Dict:
										@find_executable_batch_size(starting_batch_size=0	)
										def mock_training_loop_function(__lowerCamelCase							:						str	):
																pass

										with self.assertRaises(_SCREAMING_SNAKE_CASE	) as cm:
																mock_training_loop_function()
																self.assertIn("No executable batch size found, reached zero."						,    cm.exception.args[0]	)







				def     _snake_case					(							self							:						int	)				->					Union[str, Any]:
										@find_executable_batch_size(starting_batch_size=1_6	)
										def mock_training_loop_function(__lowerCamelCase							:						str	):
																if batch_size > 0:
																						raise_fake_out_of_memory()
																pass

										with self.assertRaises(_SCREAMING_SNAKE_CASE	) as cm:
																mock_training_loop_function()
																self.assertIn("No executable batch size found, reached zero."						,    cm.exception.args[0]	)







				def     _snake_case					(							self							:						Tuple	)				->					Optional[int]:
										@find_executable_batch_size(starting_batch_size=1_2_8	)
										def mock_training_loop_function(__lowerCamelCase							:						Dict						,    __lowerCamelCase							:						Any						,    __lowerCamelCase							:						Optional[Any]	):
																if batch_size != 8:
																						raise raise_fake_out_of_memory()

										with self.assertRaises(_SCREAMING_SNAKE_CASE	) as cm:
																mock_training_loop_function(1_2_8						,    "hello"						,    "world"	)
																self.assertIn("Batch size was passed into `f`"						,    cm.exception.args[0]	)
																self.assertIn("`f(arg1='hello', arg2='world')"						,    cm.exception.args[0]	)







				def     _snake_case					(							self							:						int	)				->					Tuple:
										@find_executable_batch_size(starting_batch_size=1_6	)
										def mock_training_loop_function(__lowerCamelCase							:						Dict	):
																raise ValueError("Oops, we had an error!"	)

										with self.assertRaises(_SCREAMING_SNAKE_CASE	) as cm:
																mock_training_loop_function()
																self.assertIn("Oops, we had an error!"						,    cm.exception.args[0]	)







				@require_cuda
				def     _snake_case					(							self							:						List[str]	)				->					Union[str, Any]:
										__magic_name__            =     torch.cuda.memory_allocated()
										__magic_name__            =     ModelForTest()
										model.cuda()
										self.assertGreater(torch.cuda.memory_allocated()						,    _SCREAMING_SNAKE_CASE	)
										__magic_name__            =     release_memory(_SCREAMING_SNAKE_CASE	)
										self.assertEqual(torch.cuda.memory_allocated()						,    _SCREAMING_SNAKE_CASE	)











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:list   ):

						'''simple docstring'''






						__magic_name__            =     len(__lowerCamelCase   )
						for i in range(1 ,						__lowerCamelCase   ):
												__magic_name__            =     collection[i]
												__magic_name__            =     0
												__magic_name__            =     i - 1

												while low <= high:
																		__magic_name__            =     (low + high) // 2
																		if val < collection[mid]:
																								__magic_name__            =     mid - 1
																		else:
																								__magic_name__            =     mid + 1
												for j in range(__lowerCamelCase ,						__lowerCamelCase ,						-1   ):
																		__magic_name__            =     collection[j - 1]
												__magic_name__            =     val
						return collection


if __name__ == "__main__":
			lowercase    			=       input('''Enter numbers separated by a comma:\n''').strip()
			lowercase    			=       [int(item) for item in user_input.split(''',''')]
			print(binary_insertion_sort(unsorted))



