



"""simple docstring"""





import inspect
import os
import unittest
from dataclasses import dataclass

import torch

from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from accelerate.utils import KwargsHandler
@dataclass
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







							'''simple docstring'''


							UpperCamelCase		=  0
							UpperCamelCase		=  False
							UpperCamelCase		=  3.0



class    lowercase__     (					unittest.TestCase   ):







							'''simple docstring'''


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


													'''simple docstring'''




													self.assertDictEqual(MockClass().to_kwargs()	,       {}					)
													self.assertDictEqual(MockClass(a=2					).to_kwargs()	,       {"a": 2}					)
													self.assertDictEqual(MockClass(a=2	,       b=_UpperCAmelCase					).to_kwargs()	,       {"a": 2, "b": True}					)
													self.assertDictEqual(MockClass(a=2	,       c=2.25					).to_kwargs()	,       {"a": 2, "c": 2.25}					)



							@require_cuda
							def   lowercase__       (							self    :						str					)				->		str:


													'''simple docstring'''




													UpperCAmelCase_    				=							GradScalerKwargs(init_scale=1024	,       growth_factor=2					)
													AcceleratorState._reset_state()
													UpperCAmelCase_    				=							Accelerator(mixed_precision="fp16"	,       kwargs_handlers=[scaler_handler]					)
													print(accelerator.use_fpaa					)
													UpperCAmelCase_    				=							accelerator.scaler

													# Check the kwargs have been applied
													self.assertEqual(scaler._init_scale	,       1024.0					)
													self.assertEqual(scaler._growth_factor	,       2.0					)

													# Check the other values are at the default
													self.assertEqual(scaler._backoff_factor	,       0.5					)
													self.assertEqual(scaler._growth_interval	,       2000					)
													self.assertEqual(scaler._enabled	,       _UpperCAmelCase					)







							@require_multi_gpu
							def   lowercase__       (							self    :						Union[str, Any]					)				->		List[str]:


													'''simple docstring'''




													UpperCAmelCase_    				=							["torchrun", F"""--nproc_per_node={torch.cuda.device_count()}""", inspect.getfile(self.__class__					)]
													execute_subprocess_async(_UpperCAmelCase	,       env=os.environ.copy()					)


if __name__ == "__main__":
		lowerCamelCase      =		DistributedDataParallelKwargs(bucket_cap_mb=15, find_unused_parameters=True)
		lowerCamelCase      =		Accelerator(kwargs_handlers=[ddp_scaler])
		lowerCamelCase      =		torch.nn.Linear(100, 200)
		lowerCamelCase      =		accelerator.prepare(model)

		# Check the values changed in kwargs
		lowerCamelCase      =		""""""
		lowerCamelCase      =		model.bucket_bytes_cap // (1_024 * 1_024)
		if observed_bucket_cap_map != 15:
				error_msg += F"Kwargs badly passed, should have `15` but found {observed_bucket_cap_map}.\n"
		if model.find_unused_parameters is not True:
				error_msg += F"Kwargs badly passed, should have `True` but found {model.find_unused_parameters}.\n"

		# Check the values of the defaults
		if model.dim != 0:
				error_msg += F"Default value not respected, should have `0` but found {model.dim}.\n"
		if model.broadcast_buffers is not True:
				error_msg += F"Default value not respected, should have `True` but found {model.broadcast_buffers}.\n"
		if model.gradient_as_bucket_view is not False:
				error_msg += F"Default value not respected, should have `False` but found {model.gradient_as_bucket_view}.\n"

		# Raise error at the end to make sure we don't stop at the first failure.
		if len(error_msg) > 0:
				raise ValueError(error_msg)









"""simple docstring"""





from __future__ import annotations

import math
def      a__			(   lowerCAmelCase__   ):

      if 1 < number < 4:
            # 2 and 3 are primes
            return True
      elif number < 2 or number % 2 == 0 or number % 3 == 0:
            # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
            return False

      # All primes number are in format of 6k +/- 1
      for i in range(5			,    int(math.sqrt(lowerCAmelCase__   ) + 1   )			,    6   ):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True


lowerCamelCase      =		[num for num in range(3, 100_001, 2) if not is_prime(num)]
def      a__			(   lowerCAmelCase__   ):
      if not isinstance(lowerCAmelCase__			,    lowerCAmelCase__   ):
            raise ValueError("n must be an integer"   )
      if n <= 0:
            raise ValueError("n must be >= 0"   )

      UpperCAmelCase_    				=							[]
      for num in range(len(lowerCAmelCase__   )   ):
            UpperCAmelCase_    				=							0
            while 2 * i * i <= odd_composites[num]:
                  UpperCAmelCase_    				=							odd_composites[num] - 2 * i * i
                  if is_prime(lowerCAmelCase__   ):
                        break
                  i += 1
            else:
                  list_nums.append(odd_composites[num]   )
                  if len(lowerCAmelCase__   ) == n:
                        return list_nums

      return []
def      a__			(   ):
      return compute_nums(1   )[0]


if __name__ == "__main__":
  print(F"{solution() = }")




