


'''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       ():
		raise RuntimeError("CUDA out of memory."      )






class 		lowerCAmelCase__	(	nn.Module		):




			def __init__(						self     :   Union[str, Any]       )      ->Any:



					'''simple docstring'''







					super().__init__()
					_UpperCAmelCase						:				Tuple	    =					nn.Linear(3		,     4       )
					_UpperCAmelCase						:				Tuple	    =					nn.BatchNormad(4       )
					_UpperCAmelCase						:				int	    =					nn.Linear(4		,     5       )






			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   Optional[int]       )      ->Any:



					'''simple docstring'''







					return self.lineara(self.batchnorm(self.lineara(lowerCamelCase__       )       )       )






class 		lowerCAmelCase__	(	unittest.TestCase		):




			def 							lowerCAmelCase__			(						self     :   Optional[Any]       )      ->Optional[Any]:



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[int]	    =					[]

					@find_executable_batch_size(starting_batch_size=1_28       )
					def mock_training_loop_function(lowerCamelCase__     :   Optional[int]       ):
							nonlocal batch_sizes
							batch_sizes.append(lowerCamelCase__       )
							if batch_size != 8:
									raise_fake_out_of_memory()

					mock_training_loop_function()
					self.assertListEqual(lowerCamelCase__		,     [1_28, 64, 32, 16, 8]       )




			def 							lowerCAmelCase__			(						self     :   Union[str, Any]       )      ->Any:



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[Any]	    =					[]

					@find_executable_batch_size(starting_batch_size=1_28       )
					def mock_training_loop_function(lowerCamelCase__     :   int		,     lowerCamelCase__     :   Any       ):
							nonlocal batch_sizes
							batch_sizes.append(lowerCamelCase__       )
							if batch_size != 8:
									raise_fake_out_of_memory()
							return batch_size, arga

					_UpperCAmelCase						:				Optional[int]	    =					mock_training_loop_function("hello"       )
					self.assertListEqual(lowerCamelCase__		,     [1_28, 64, 32, 16, 8]       )
					self.assertListEqual([bs, arga]		,     [8, "hello"]       )




			def 							lowerCAmelCase__			(						self     :   int       )      ->Any:



					'''simple docstring'''







					@find_executable_batch_size(starting_batch_size=0       )
					def mock_training_loop_function(lowerCamelCase__     :   Union[str, Any]       ):
							pass

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




			def 							lowerCAmelCase__			(						self     :   List[Any]       )      ->Optional[int]:



					'''simple docstring'''







					@find_executable_batch_size(starting_batch_size=16       )
					def mock_training_loop_function(lowerCamelCase__     :   Optional[Any]       ):
							if batch_size > 0:
									raise_fake_out_of_memory()
							pass

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




			def 							lowerCAmelCase__			(						self     :   List[Any]       )      ->Optional[Any]:



					'''simple docstring'''







					@find_executable_batch_size(starting_batch_size=1_28       )
					def mock_training_loop_function(lowerCamelCase__     :   Union[str, Any]		,     lowerCamelCase__     :   List[Any]		,     lowerCamelCase__     :   Dict       ):
							if batch_size != 8:
									raise raise_fake_out_of_memory()

					with self.assertRaises(lowerCamelCase__       ) as cm:
							mock_training_loop_function(1_28		,     "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 							lowerCAmelCase__			(						self     :   Dict       )      ->int:



					'''simple docstring'''







					@find_executable_batch_size(starting_batch_size=16       )
					def mock_training_loop_function(lowerCamelCase__     :   Optional[Any]       ):
							raise ValueError("Oops, we had an error!"       )

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






			@require_cuda
			def 							lowerCAmelCase__			(						self     :   int       )      ->Optional[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[Any]	    =					torch.cuda.memory_allocated()
					_UpperCAmelCase						:				List[str]	    =					ModelForTest()
					model.cuda()
					self.assertGreater(torch.cuda.memory_allocated()		,     lowerCamelCase__       )
					_UpperCAmelCase						:				Tuple	    =					release_memory(lowerCamelCase__       )
					self.assertEqual(torch.cuda.memory_allocated()		,     lowerCamelCase__       )








'''simple docstring'''




from __future__ import annotations

import math

class 			UpperCamelCase_ :





	def __init__(  self		,		A    )			->			None:
								UpperCAmelCase     :		Optional[int]							     =		size
								# approximate the overall size of segment tree with given value
								UpperCAmelCase     :		Optional[int]							     =		[0 for i in range(0		,		4 * size    )]
								# create array to store lazy update
								UpperCAmelCase     :		Any							     =		[0 for i in range(0		,		4 * size    )]
								UpperCAmelCase     :		Tuple							     =		[0 for i in range(0		,		4 * size    )]  # flag for lazy update





	def  _lowercase(  self		,		A    )			->			int:
								return idx * 2





	def  _lowercase(  self		,		A    )			->			int:
								return idx * 2 + 1





	def  _lowercase(  self		,		A		,		A		,		A		,		A    )			->			None:
								if left_element == right_element:
															UpperCAmelCase     :		str							     =		a[left_element - 1]
								else:
															UpperCAmelCase     :		Tuple							     =		(left_element + right_element) // 2
															self.build(self.left(A    )		,		A		,		A		,		A    )
															self.build(self.right(A    )		,		mid + 1		,		A		,		A    )
															UpperCAmelCase     :		str							     =		max(
															    self.segment_tree[self.left(A    )]		,		self.segment_tree[self.right(A    )]    )





	def  _lowercase(  self		,		A		,		A		,		A		,		A		,		A		,		A    )			->			bool:
								if self.flag[idx] is True:
															UpperCAmelCase     :		Optional[Any]							     =		self.lazy[idx]
															UpperCAmelCase     :		int							     =		False
															if left_element != right_element:
																						UpperCAmelCase     :		List[str]							     =		self.lazy[idx]
																						UpperCAmelCase     :		Optional[Any]							     =		self.lazy[idx]
																						UpperCAmelCase     :		List[str]							     =		True
																						UpperCAmelCase     :		int							     =		True

								if right_element < a or left_element > b:
															return True
								if left_element >= a and right_element <= b:
															UpperCAmelCase     :		Optional[Any]							     =		val
															if left_element != right_element:
																						UpperCAmelCase     :		Tuple							     =		val
																						UpperCAmelCase     :		int							     =		val
																						UpperCAmelCase     :		Any							     =		True
																						UpperCAmelCase     :		str							     =		True
															return True
								UpperCAmelCase     :		str							     =		(left_element + right_element) // 2
								self.update(self.left(A    )		,		A		,		A		,		A		,		A		,		A    )
								self.update(self.right(A    )		,		mid + 1		,		A		,		A		,		A		,		A    )
								UpperCAmelCase     :		List[str]							     =		max(
								    self.segment_tree[self.left(A    )]		,		self.segment_tree[self.right(A    )]    )
								return True





	def  _lowercase(  self		,		A		,		A		,		A		,		A		,		A    )			->			int | float:
								if self.flag[idx] is True:
															UpperCAmelCase     :		Any							     =		self.lazy[idx]
															UpperCAmelCase     :		Any							     =		False
															if left_element != right_element:
																						UpperCAmelCase     :		Optional[Any]							     =		self.lazy[idx]
																						UpperCAmelCase     :		Tuple							     =		self.lazy[idx]
																						UpperCAmelCase     :		List[str]							     =		True
																						UpperCAmelCase     :		Tuple							     =		True
								if right_element < a or left_element > b:
															return -math.inf
								if left_element >= a and right_element <= b:
															return self.segment_tree[idx]
								UpperCAmelCase     :		Dict							     =		(left_element + right_element) // 2
								UpperCAmelCase     :		List[Any]							     =		self.query(self.left(A    )		,		A		,		A		,		A		,		A    )
								UpperCAmelCase     :		str							     =		self.query(self.right(A    )		,		mid + 1		,		A		,		A		,		A    )
								return max(A		,		A    )






	def __str__(  self    )			->			str:
								return str([self.query(1		,		1		,		self.size		,		A		,		A    ) for i in range(1		,		self.size + 1    )]    )


if __name__ == "__main__":
							a   :			Optional[int]					  =    [1, 2, -4, 7, 3, -5, 6, 1_1, -2_0, 9, 1_4, 1_5, 5, 2, -8]
							a   :			Optional[Any]					  =    1_5
							a   :			Union[str, Any]					  =    SegmentTree(size)
							segt.build(1, 1, size, A)
							print(segt.query(1, 1, size, 4, 6))
							print(segt.query(1, 1, size, 7, 1_1))
							print(segt.query(1, 1, size, 7, 1_2))
							segt.update(1, 1, size, 1, 3, 1_1_1)
							print(segt.query(1, 1, size, 1, 1_5))
							segt.update(1, 1, size, 7, 8, 2_3_5)
							print(segt)

