



'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import _LazyModule


lowercase_      :				Dict   					=    {'''tokenization_bertweet''': ['''BertweetTokenizer''']}


if TYPE_CHECKING:
						from .tokenization_bertweet import BertweetTokenizer

else:
						import sys

						lowercase_      :				int   					=    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)







'''simple docstring'''


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_      :				Union[str, Any]   					=    logging.get_logger(__name__)




@dataclass
class      __UpperCamelCase       (_UpperCAmelCase			):
	__A			  =					[
	    '''no_inference''',
	    '''no_cuda''',
	    '''no_tpu''',
	    '''no_speed''',
	    '''no_memory''',
	    '''no_env_print''',
	    '''no_multi_process''',
	]







	def __init__(    self ,				**_lowerCAmelCase						)    ->    Optional[int]:
							'''simple docstring'''






							for deprecated_arg in self.deprecated_args:
													if deprecated_arg in kwargs:
																			lowercase        =							deprecated_arg[3:]
																			lowercase        =							not kwargs.pop(_lowerCAmelCase						)
																			logger.warning(
																			    F"""{deprecated_arg} is depreciated. Please use --no-{positive_arg} or"""
																			    F""" {positive_arg}={kwargs[positive_arg]}"""						)
							lowercase        =							kwargs.pop("""tpu_name""" ,				self.tpu_name						)
							lowercase        =							kwargs.pop("""device_idx""" ,				self.device_idx						)
							lowercase        =							kwargs.pop("""eager_mode""" ,				self.eager_mode						)
							lowercase        =							kwargs.pop("""use_xla""" ,				self.use_xla						)
							super().__init__(**_lowerCAmelCase						)

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







	@cached_property
	def   _a   (    self						)    ->    Tuple["tf.distribute.cluster_resolver.TPUClusterResolver"]:
							'''simple docstring'''






							requires_backends(self ,				["""tf"""]						)
							lowercase        =							None
							if self.tpu:
													try:
																			if self.tpu_name:
																									lowercase        =							tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name						)
																			else:
																									lowercase        =							tf.distribute.cluster_resolver.TPUClusterResolver()
													except ValueError:
																			lowercase        =							None
							return tpu







	@cached_property
	def   _a   (    self						)    ->    Tuple["tf.distribute.Strategy", "tf.distribute.cluster_resolver.TPUClusterResolver"]:
							'''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						)

													lowercase        =							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"""						)
																			lowercase        =							tf.distribute.OneDeviceStrategy(device=F"""/gpu:{self.device_idx}"""						)
													else:
																			tf.config.set_visible_devices([] ,				"""GPU"""						)  # disable GPU
																			lowercase        =							tf.distribute.OneDeviceStrategy(device=F"""/cpu:{self.device_idx}"""						)

							return strategy







	@property
	def   _a   (    self						)    ->    bool:
							'''simple docstring'''






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







	@property
	def   _a   (    self						)    ->    "tf.distribute.Strategy":
							'''simple docstring'''






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







	@property
	def   _a   (    self						)    ->    Tuple:
							'''simple docstring'''






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







	@property
	def   _a   (    self						)    ->    int:
							'''simple docstring'''






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







	@property
	def   _a   (    self						)    ->    bool:
							'''simple docstring'''






							return self.n_gpu > 0


