
'''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  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       =0
 lowerCamelCase				       =False
 lowerCamelCase				       =3.0







class  __A				( unittest.TestCase			):
 def 		lowercase_(   self			:    Optional[Any]       ):



   """simple docstring"""





   self.assertDictEqual(MockClass().to_kwargs()				,   {}       )
   self.assertDictEqual(MockClass(a=2       ).to_kwargs()				,   {"""a""": 2}       )
   self.assertDictEqual(MockClass(a=2				,   b=lowerCamelCase       ).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       ):



   """simple docstring"""





   __A		:     Optional[Any]												=		GradScalerKwargs(init_scale=10_24				,   growth_factor=2       )
   AcceleratorState._reset_state()
   __A		:     Tuple												=		Accelerator(mixed_precision="""fp16"""				,   kwargs_handlers=[scaler_handler]       )
   print(accelerator.use_fpaa       )
   __A		:     List[str]												=		accelerator.scaler

   # Check the kwargs have been applied
   self.assertEqual(scaler._init_scale				,   1_024.0       )
   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				,   20_00       )
   self.assertEqual(scaler._enabled				,   lowerCamelCase       )






 @require_multi_gpu
 def 		lowercase_(   self			:    Tuple       ):



   """simple docstring"""





   __A		:     int												=		["""torchrun""", f"--nproc_per_node={torch.cuda.device_count()}", inspect.getfile(self.__class__       )]
   execute_subprocess_async(lowerCamelCase				,   env=os.environ.copy()       )


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

     # Check the values changed in kwargs
     A__   :		int 		=''
     A__   :		Any 		=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'''
A__   :		int 		=8.3_1_4_4_6_2  # Unit - J mol-1 K-1







def        A_     (						__SCREAMING_SNAKE_CASE						:  float			,     __SCREAMING_SNAKE_CASE						:  float			,     __SCREAMING_SNAKE_CASE						:  float )				->       float:





  """simple docstring"""

  if moles < 0 or kelvin < 0 or volume < 0:
    raise ValueError("""Invalid inputs. Enter positive value.""" )
  return moles * kelvin * UNIVERSAL_GAS_CONSTANT / volume







def        A_     (						__SCREAMING_SNAKE_CASE						:  float			,     __SCREAMING_SNAKE_CASE						:  float			,     __SCREAMING_SNAKE_CASE						:  float )				->       float:





  """simple docstring"""

  if moles < 0 or kelvin < 0 or pressure < 0:
    raise ValueError("""Invalid inputs. Enter positive value.""" )
  return moles * kelvin * UNIVERSAL_GAS_CONSTANT / pressure


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

     testmod()



