


from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_tf_available():
     import tensorflow as tf


snake_case							:       int										=	logging.get_logger(__name__)







@dataclass
class 						_snake_case    ( _snake_case				):
 SCREAMING_SNAKE_CASE__ =			[
     'no_inference',
     'no_cuda',
     'no_tpu',
     'no_speed',
     'no_memory',
     'no_env_print',
     'no_multi_process',
 ]




 def __init__(						self   ,    **_lowerCamelCase       ):
       for deprecated_arg in self.deprecated_args:
             if deprecated_arg in kwargs:
                   a		:List[Any]									=			deprecated_arg[3:]
                   a		:Dict									=			not kwargs.pop(_lowerCamelCase       )
                   logger.warning(
                       F'''{deprecated_arg} is depreciated. Please use --no-{positive_arg} or'''
                       F''' {positive_arg}={kwargs[positive_arg]}'''       )
       a		:Union[str, Any]									=			kwargs.pop('''tpu_name'''   ,    self.tpu_name       )
       a		:int									=			kwargs.pop('''device_idx'''   ,    self.device_idx       )
       a		:List[Any]									=			kwargs.pop('''eager_mode'''   ,    self.eager_mode       )
       a		:Dict									=			kwargs.pop('''use_xla'''   ,    self.use_xla       )
       super().__init__(**_lowerCamelCase       )

 SCREAMING_SNAKE_CASE__ =			field(
     default=_snake_case		,       metadata={'help': 'Name of TPU'}		,       )
 SCREAMING_SNAKE_CASE__ =			field(
     default=0		,       metadata={'help': 'CPU / GPU device index. Defaults to 0.'}		,       )
 SCREAMING_SNAKE_CASE__ =			field(default=_snake_case		,       metadata={'help': 'Benchmark models in eager model.'}				)
 SCREAMING_SNAKE_CASE__ =			field(
     default=_snake_case		,       metadata={
         'help': 'Benchmark models using XLA JIT compilation. Note that `eager_model` has to be set to `False`.'
     }		,       )




 @cached_property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       requires_backends(self   ,    ['''tf''']       )
       a		:Tuple									=			None
       if self.tpu:
             try:
                   if self.tpu_name:
                         a		:Optional[int]									=			tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name       )
                   else:
                         a		:Any									=			tf.distribute.cluster_resolver.TPUClusterResolver()
             except ValueError:
                   a		:Union[str, Any]									=			None
       return tpu




 @cached_property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       requires_backends(self   ,    ['''tf''']       )
       if self.is_tpu:
             tf.config.experimental_connect_to_cluster(self._setup_tpu       )
             tf.tpu.experimental.initialize_tpu_system(self._setup_tpu       )

             a		:Optional[Any]									=			tf.distribute.TPUStrategy(self._setup_tpu       )
       else:
             # currently no multi gpu is allowed
             if self.is_gpu:
                   # TODO: Currently only single GPU is supported
                   tf.config.set_visible_devices(self.gpu_list[self.device_idx]   ,    '''GPU'''       )
                   a		:List[str]									=			tf.distribute.OneDeviceStrategy(device=F'''/gpu:{self.device_idx}'''       )
             else:
                   tf.config.set_visible_devices([]   ,    '''GPU'''       )  # disable GPU
                   a		:str									=			tf.distribute.OneDeviceStrategy(device=F'''/cpu:{self.device_idx}'''       )

       return strategy




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       requires_backends(self   ,    ['''tf''']       )
       return self._setup_tpu is not None




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       requires_backends(self   ,    ['''tf''']       )
       return self._setup_strategy




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       requires_backends(self   ,    ['''tf''']       )
       return tf.config.list_physical_devices('''GPU'''       )




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       requires_backends(self   ,    ['''tf''']       )
       if self.cuda:
             return len(self.gpu_list       )
       return 0




 @property
 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       return self.n_gpu > 0









def 							__lowerCamelCase		(					UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





      while b:
            a				,							a		:int									=			b, a % b
      return a
def 							__lowerCamelCase		(					UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





      return a if b == 0 else euclidean_gcd_recursive(UpperCAmelCase_					,    a % b		)
def 							__lowerCamelCase		(					):




      """simple docstring"""





      print(F'''euclidean_gcd(3, 5) = {euclidean_gcd(3					,    5		)}'''		)
      print(F'''euclidean_gcd(5, 3) = {euclidean_gcd(5					,    3		)}'''		)
      print(F'''euclidean_gcd(1, 3) = {euclidean_gcd(1					,    3		)}'''		)
      print(F'''euclidean_gcd(3, 6) = {euclidean_gcd(3					,    6		)}'''		)
      print(F'''euclidean_gcd(6, 3) = {euclidean_gcd(6					,    3		)}'''		)

      print(F'''euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3					,    5		)}'''		)
      print(F'''euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5					,    3		)}'''		)
      print(F'''euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1					,    3		)}'''		)
      print(F'''euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3					,    6		)}'''		)
      print(F'''euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6					,    3		)}'''		)


if __name__ == "__main__":
     main()





