
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


lowercase_ 				=			logging.get_logger(__name__)





@dataclass
class     __UpperCamelCase (							lowerCAmelCase__       ):






     """simple docstring"""







     lowerCAmelCase_							   =			[
         '''no_inference''',
         '''no_cuda''',
         '''no_tpu''',
         '''no_speed''',
         '''no_memory''',
         '''no_env_print''',
         '''no_multi_process''',
     ]



     def __init__(				self							:							Union[str, Any]     ,						**_A							:							List[str] ):







       """simple docstring"""




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

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



     @cached_property
     def  UpperCAmelCase__							(				self							:							Optional[int] ):







       """simple docstring"""




       requires_backends(self     ,						['''tf'''] )
       __SCREAMING_SNAKE_CASE      :	str					=		None
       if self.tpu:
         try:
           if self.tpu_name:
             __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name )
           else:
             __SCREAMING_SNAKE_CASE      :	List[str]					=		tf.distribute.cluster_resolver.TPUClusterResolver()
         except ValueError:
           __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		None
       return tpu



     @cached_property
     def  UpperCAmelCase__							(				self							:							str ):







       """simple docstring"""




       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 )

         __SCREAMING_SNAKE_CASE      :	List[str]					=		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''' )
           __SCREAMING_SNAKE_CASE      :	List[Any]					=		tf.distribute.OneDeviceStrategy(device=F'''/gpu:{self.device_idx}''' )
         else:
           tf.config.set_visible_devices([]     ,						'''GPU''' )  # disable GPU
           __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		tf.distribute.OneDeviceStrategy(device=F'''/cpu:{self.device_idx}''' )

       return strategy



     @property
     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       requires_backends(self     ,						['''tf'''] )
       return self._setup_tpu is not None



     @property
     def  UpperCAmelCase__							(				self							:							Dict ):







       """simple docstring"""




       requires_backends(self     ,						['''tf'''] )
       return self._setup_strategy



     @property
     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       requires_backends(self     ,						['''tf'''] )
       return tf.config.list_physical_devices('''GPU''' )



     @property
     def  UpperCAmelCase__							(				self							:							Optional[int] ):







       """simple docstring"""




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




     @property
     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       return self.n_gpu > 0





'''simple docstring'''

from abc import ABC, abstractmethod
from argparse import ArgumentParser

class       __magic_name__		(       _UpperCamelCase  ):







							@staticmethod
							@abstractmethod
							def 				__lowercase     (				_UpperCAmelCase   :			ArgumentParser						):
									raise NotImplementedError()







							@abstractmethod
							def 				__lowercase     (				self   :			str						):
									raise NotImplementedError()




