





'''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  lowerCAmelCase_						(       snake_case__      ):





  """simple docstring"""



  a_       :Optional[int]												=0
  a_       :Optional[Any]												=False
  a_       :Union[str, Any]												=3.0


class  lowerCAmelCase_						(       unittest.TestCase      ):





  """simple docstring"""



  def __a						(					self     :							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=2.2_5						).to_kwargs()				,							{"""a""": 2, """c""": 2.2_5}						)

  @require_cuda
  def __a						(					self     :							str						):





       '''simple docstring'''

       __a       =   GradScalerKwargs(init_scale=1_0_2_4				,							growth_factor=2						)
       AcceleratorState._reset_state()
       __a       =   Accelerator(mixed_precision="""fp16"""				,							kwargs_handlers=[scaler_handler]						)
       print(accelerator.use_fpaa						)
       __a       =   accelerator.scaler

       # Check the kwargs have been applied
       self.assertEqual(scaler._init_scale				,							1_0_2_4.0						)
       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				,							2_0_0_0						)
       self.assertEqual(scaler._enabled				,							_UpperCAmelCase						)


  @require_multi_gpu
  def __a						(					self     :							Union[str, Any]						):





       '''simple docstring'''

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


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE_      =			DistributedDataParallelKwargs(bucket_cap_mb=15, find_unused_parameters=True)
 SCREAMING_SNAKE_CASE_      =			Accelerator(kwargs_handlers=[ddp_scaler])
 SCREAMING_SNAKE_CASE_      =			torch.nn.Linear(1_00, 2_00)
 SCREAMING_SNAKE_CASE_      =			accelerator.prepare(model)

 # Check the values changed in kwargs
 SCREAMING_SNAKE_CASE_      =			''
 SCREAMING_SNAKE_CASE_      =			model.bucket_bytes_cap // (10_24 * 10_24)
 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'''







def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					bool:
     """simple docstring"""




     __a       =   [int(__SCREAMING_SNAKE_CASE		) for i in ip_va_address.split("""."""		) if i.isdigit()]
     return len(__SCREAMING_SNAKE_CASE		) == 4 and all(0 <= int(__SCREAMING_SNAKE_CASE		) <= 254 for octet in octets		)


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE_      =			input().strip()
 SCREAMING_SNAKE_CASE_      =			'valid' if is_ip_va_address_valid(ip) else 'invalid'
 print(f"""{ip} is a {valid_or_invalid} IP v4 address.""")






