

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    _lowercase				(					nn.Module			):

   def __init__(				self	:    int       ) ->			int:
         """simple docstring"""





         super().__init__()
         A_							       =		nn.Linear(3			,						4       )
         A_							       =		nn.BatchNormad(4       )
         A_							       =		nn.Linear(4			,						5       )





   def     UpperCamelCase					(				self	:    List[str]			,						lowerCamelCase__	:    Dict       ) ->			Optional[int]:
         """simple docstring"""





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



class    _lowercase				(					unittest.TestCase			):

   def     UpperCamelCase					(				self	:    Any       ) ->			Optional[Any]:
         """simple docstring"""





         A_							       =		[]

         @find_executable_batch_size(starting_batch_size=1_2_8       )
         def mock_training_loop_function(lowerCamelCase__	:    Tuple       ):
               nonlocal batch_sizes
               batch_sizes.append(lowerCamelCase__       )
               if batch_size != 8:
                     raise_fake_out_of_memory()

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

   def     UpperCamelCase					(				self	:    int       ) ->			Union[str, Any]:
         """simple docstring"""





         A_							       =		[]

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

         A_       ,A_							       =		mock_training_loop_function('''hello'''       )
         self.assertListEqual(lowerCamelCase__			,						[1_2_8, 6_4, 3_2, 1_6, 8]       )
         self.assertListEqual([bs, arga]			,						[8, '''hello''']       )

   def     UpperCamelCase					(				self	:    Tuple       ) ->			Dict:
         """simple docstring"""





         @find_executable_batch_size(starting_batch_size=0       )
         def mock_training_loop_function(lowerCamelCase__	:    List[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     UpperCamelCase					(				self	:    Optional[Any]       ) ->			str:
         """simple docstring"""





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

   def     UpperCamelCase					(				self	:    str       ) ->			Union[str, Any]:
         """simple docstring"""





         @find_executable_batch_size(starting_batch_size=1_2_8       )
         def mock_training_loop_function(lowerCamelCase__	:    str			,						lowerCamelCase__	:    Optional[Any]			,						lowerCamelCase__	:    Any       ):
               if batch_size != 8:
                     raise raise_fake_out_of_memory()

         with self.assertRaises(lowerCamelCase__       ) 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     UpperCamelCase					(				self	:    List[Any]       ) ->			Optional[int]:
         """simple docstring"""





         @find_executable_batch_size(starting_batch_size=1_6       )
         def mock_training_loop_function(lowerCamelCase__	:    Tuple       ):
               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     UpperCamelCase					(				self	:    Tuple       ) ->			Any:
         """simple docstring"""





         A_							       =		torch.cuda.memory_allocated()
         A_							       =		ModelForTest()
         model.cuda()
         self.assertGreater(torch.cuda.memory_allocated()			,						lowerCamelCase__       )
         A_							       =		release_memory(lowerCamelCase__       )
         self.assertEqual(torch.cuda.memory_allocated()			,						lowerCamelCase__       )








from __future__ import annotations







def 							_lowerCamelCase   (			SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE = None		,				SCREAMING_SNAKE_CASE = None   ):
      '''simple docstring'''







      if start is None:
            A_							       =		0

      if end is None:
            A_							       =		len(SCREAMING_SNAKE_CASE   ) - 1

      if start >= end:
            return

      A_							       =		(start + end) // 2

      slowsort(SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE   )
      slowsort(SCREAMING_SNAKE_CASE		,				mid + 1		,				SCREAMING_SNAKE_CASE   )

      if sequence[end] < sequence[mid]:
            A_       ,A_							       =		sequence[mid], sequence[end]

      slowsort(SCREAMING_SNAKE_CASE		,				SCREAMING_SNAKE_CASE		,				end - 1   )


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

      testmod()





