





'''simple docstring'''

from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_torch_available():
   import torch

if is_torch_tpu_available(check_device=False):
   import torch_xla.core.xla_model as xm


UpperCAmelCase					:		Tuple		=							logging.get_logger(__name__)





@dataclass
class lowerCamelCase						(a__					):
  _lowercase  :	Any       					=				[
      """no_inference""",
      """no_cuda""",
      """no_tpu""",
      """no_speed""",
      """no_memory""",
      """no_env_print""",
      """no_multi_process""",
  ]







  def __init__(		self     ,     **lowercase__		)		->						List[Any]:






        """simple docstring"""





        for deprecated_arg in self.deprecated_args:
              if deprecated_arg in kwargs:
                    _snake_case		:	Optional[int]					     =     deprecated_arg[3:]
                    setattr(self     ,     lowercase__     ,     not kwargs.pop(lowercase__		)		)
                    logger.warning(
                        F'''{deprecated_arg} is depreciated. Please use --no_{positive_arg} or'''
                        F''' {positive_arg}={kwargs[positive_arg]}'''		)

        _snake_case		:	Optional[Any]					     =     kwargs.pop('''torchscript'''     ,     self.torchscript		)
        _snake_case		:	Dict					     =     kwargs.pop('''torch_xla_tpu_print_metrics'''     ,     self.torch_xla_tpu_print_metrics		)
        _snake_case		:	Tuple					     =     kwargs.pop('''fp16_opt_level'''     ,     self.fpaa_opt_level		)
        super().__init__(**lowercase__		)

  _lowercase  :	bool       					=				field(default=a__						,      metadata={"""help""": """Trace the models using torchscript"""}					)
  _lowercase  :	bool       					=				field(default=a__						,      metadata={"""help""": """Print Xla/PyTorch tpu metrics"""}					)
  _lowercase  :	str       					=				field(
      default="""O1"""						,      metadata={
          """help""": (
              """For fp16: Apex AMP optimization level selected in ['O0', 'O1', 'O2', and 'O3']. """
              """See details at https://nvidia.github.io/apex/amp.html"""
          )
      }						,      )







  @cached_property
  def 				UpperCAmelCase_				(		self		)		->						Tuple["torch.device", int]:






        """simple docstring"""





        requires_backends(self     ,     ['''torch''']		)
        logger.info('''PyTorch: setting up devices'''		)
        if not self.cuda:
              _snake_case		:	List[str]					     =     torch.device('''cpu'''		)
              _snake_case		:	int					     =     0
        elif is_torch_tpu_available():
              _snake_case		:	Tuple					     =     xm.xla_device()
              _snake_case		:	int					     =     0
        else:
              _snake_case		:	Union[str, Any]					     =     torch.device('''cuda''' if torch.cuda.is_available() else '''cpu'''		)
              _snake_case		:	Optional[Any]					     =     torch.cuda.device_count()
        return device, n_gpu







  @property
  def 				UpperCAmelCase_				(		self		)		->						List[Any]:






        """simple docstring"""





        return is_torch_tpu_available() and self.tpu







  @property
  def 				UpperCAmelCase_				(		self		)		->						int:






        """simple docstring"""





        requires_backends(self     ,     ['''torch''']		)
        # TODO(PVP): currently only single GPU is supported
        return torch.cuda.current_device()







  @property
  def 				UpperCAmelCase_				(		self		)		->						"torch.device":






        """simple docstring"""





        requires_backends(self     ,     ['''torch''']		)
        return self._setup_devices[0]







  @property
  def 				UpperCAmelCase_				(		self		)		->						Dict:






        """simple docstring"""





        requires_backends(self     ,     ['''torch''']		)
        return self._setup_devices[1]







  @property
  def 				UpperCAmelCase_				(		self		)		->						Dict:






        """simple docstring"""





        return self.n_gpu > 0









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase					:		int		=							{
    'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase					:		Union[str, Any]		=							[
       'PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST',
       'PegasusXForConditionalGeneration',
       'PegasusXModel',
       'PegasusXPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_pegasus_x import (
          PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
          PegasusXForConditionalGeneration,
          PegasusXModel,
          PegasusXPreTrainedModel,
      )


else:
   import sys

   UpperCAmelCase					:		Dict		=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


