




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 				_A  (		):
     """simple docstring"""

     raise RuntimeError("CUDA out of memory."     )





class 					__lowerCamelCase			(       nn.Module       ):




    """simple docstring"""

    def __init__(			self	:	Any  ) ->			str:
         super().__init__()
         lowerCAmelCase__            =					nn.Linear(3  ,      4  )
         lowerCAmelCase__            =					nn.BatchNormad(4  )
         lowerCAmelCase__            =					nn.Linear(4  ,      5  )


    def   a (			self	:	Dict  ,      SCREAMING_SNAKE_CASE__	:	Tuple  ) ->			int:
         return self.lineara(self.batchnorm(self.lineara(SCREAMING_SNAKE_CASE__  )  )  )






class 					__lowerCamelCase			(       unittest.TestCase       ):




    """simple docstring"""

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

         @find_executable_batch_size(starting_batch_size=128  )
         def mock_training_loop_function(SCREAMING_SNAKE_CASE__	:	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__  ,      [128, 64, 32, 16, 8]  )


    def   a (			self	:	Union[str, Any]  ) ->			Optional[int]:
         lowerCAmelCase__            =					[]

         @find_executable_batch_size(starting_batch_size=128  )
         def mock_training_loop_function(SCREAMING_SNAKE_CASE__	:	Any  ,      SCREAMING_SNAKE_CASE__	:	List[str]  ):
              nonlocal batch_sizes
              batch_sizes.append(SCREAMING_SNAKE_CASE__  )
              if batch_size != 8:
                   raise_fake_out_of_memory()
              return batch_size, arga

         lowerCAmelCase__      ,						lowerCAmelCase__            =					mock_training_loop_function("hello"  )
         self.assertListEqual(SCREAMING_SNAKE_CASE__  ,      [128, 64, 32, 16, 8]  )
         self.assertListEqual([bs, arga]  ,      [8, "hello"]  )


    def   a (			self	:	Union[str, Any]  ) ->			Any:
         @find_executable_batch_size(starting_batch_size=0  )
         def mock_training_loop_function(SCREAMING_SNAKE_CASE__	:	List[Any]  ):
              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   a (			self	:	List[str]  ) ->			Any:
         @find_executable_batch_size(starting_batch_size=16  )
         def mock_training_loop_function(SCREAMING_SNAKE_CASE__	:	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   a (			self	:	Dict  ) ->			Union[str, Any]:
         @find_executable_batch_size(starting_batch_size=128  )
         def mock_training_loop_function(SCREAMING_SNAKE_CASE__	:	List[Any]  ,      SCREAMING_SNAKE_CASE__	:	str  ,      SCREAMING_SNAKE_CASE__	:	Dict  ):
              if batch_size != 8:
                   raise raise_fake_out_of_memory()

         with self.assertRaises(SCREAMING_SNAKE_CASE__  ) as cm:
              mock_training_loop_function(128  ,      "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   a (			self	:	Optional[Any]  ) ->			List[Any]:
         @find_executable_batch_size(starting_batch_size=16  )
         def mock_training_loop_function(SCREAMING_SNAKE_CASE__	:	List[Any]  ):
              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   a (			self	:	Optional[Any]  ) ->			List[str]:
         lowerCAmelCase__            =					torch.cuda.memory_allocated()
         lowerCAmelCase__            =					ModelForTest()
         model.cuda()
         self.assertGreater(torch.cuda.memory_allocated()  ,      SCREAMING_SNAKE_CASE__  )
         lowerCAmelCase__            =					release_memory(SCREAMING_SNAKE_CASE__  )
         self.assertEqual(torch.cuda.memory_allocated()  ,      SCREAMING_SNAKE_CASE__  )







"""simple docstring"""






from __future__ import annotations






def      lowercase__ (					lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int			)    ->			tuple[int, int]:



			'''simple docstring'''
			if b == 0:
						return (1, 0)
			((a__) ,	(a__))  :	List[Any]		 =			extended_euclid(lowerCAmelCase__							,			a % b			)
			a__  :	str		 =			a // b
			return (y, x - k * y)






def      lowercase__ (					lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int			)    ->			int:



			'''simple docstring'''
			((a__) ,	(a__))  :	Tuple		 =			extended_euclid(lowerCAmelCase__							,			lowerCAmelCase__			)
			a__  :	List[str]		 =			na * na
			a__  :	Union[str, Any]		 =			ra * x * na + ra * y * na
			return (n % m + m) % m






def      lowercase__ (					lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int			)    ->			int:



			'''simple docstring'''
			((a__) ,	(a__))  :	Optional[Any]		 =			extended_euclid(lowerCAmelCase__							,			lowerCAmelCase__			)
			if b < 0:
						a__  :	Optional[int]		 =			(b % n + n) % n
			return b






def      lowercase__ (					lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int			)    ->			int:



			'''simple docstring'''
			a__ ,	a__  :	List[Any]		 =			invert_modulo(lowerCAmelCase__							,			lowerCAmelCase__			), invert_modulo(lowerCAmelCase__							,			lowerCAmelCase__			)
			a__  :	Dict		 =			na * na
			a__  :	Any		 =			ra * x * na + ra * y * na
			return (n % m + m) % m


if __name__ == "__main__":
		from doctest import testmod

		testmod(name='''chinese_remainder_theorem''', verbose=True)
		testmod(name='''chinese_remainder_theorem2''', verbose=True)
		testmod(name='''invert_modulo''', verbose=True)
		testmod(name='''extended_euclid''', verbose=True)