





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


lowercase_          =		logging.get_logger(__name__)
@dataclass
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		Dict			 =	[
       'no_inference',
       'no_cuda',
       'no_tpu',
       'no_speed',
       'no_memory',
       'no_env_print',
       'no_multi_process',
   ]


   def __init__(   self      :    List[Any]      ,					**a      :    List[str]	)->       Tuple:





     """simple docstring"""







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

     lowercase__           =  kwargs.pop('torchscript'      ,					self.torchscript	)
     lowercase__           =  kwargs.pop('torch_xla_tpu_print_metrics'      ,					self.torch_xla_tpu_print_metrics	)
     lowercase__           =  kwargs.pop('fp16_opt_level'      ,					self.fpaa_opt_level	)
     super().__init__(**a	)

   _UpperCamelCase   :		bool			 =	field(default=UpperCAmelCase      ,     metadata={'help': 'Trace the models using torchscript'}				)
   _UpperCamelCase   :		bool			 =	field(default=UpperCAmelCase      ,     metadata={'help': 'Print Xla/PyTorch tpu metrics'}				)
   _UpperCamelCase   :		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 	SCREAMING_SNAKE_CASE_							(   self      :    Dict	)->       Tuple["torch.device", int]:





     """simple docstring"""







     requires_backends(self      ,					['torch']	)
     logger.info('PyTorch: setting up devices'	)
     if not self.cuda:
       lowercase__           =  torch.device('cpu'	)
       lowercase__           =  0
     elif is_torch_tpu_available():
       lowercase__           =  xm.xla_device()
       lowercase__           =  0
     else:
       lowercase__           =  torch.device('cuda' if torch.cuda.is_available() else 'cpu'	)
       lowercase__           =  torch.cuda.device_count()
     return device, n_gpu


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       int:





     """simple docstring"""







     return is_torch_tpu_available() and self.tpu


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    int	)->       int:





     """simple docstring"""







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


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





     """simple docstring"""







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


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





     """simple docstring"""







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


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    int	)->       List[str]:





     """simple docstring"""







     return self.n_gpu > 0









class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   pass






class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   pass






class     SCREAMING_SNAKE_CASE       :


   def __init__(   self      :    Dict	)->       Optional[int]:





     """simple docstring"""







     lowercase__           =  [
         [],
         [],
         [],
     ]


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Dict      ,					a      :    int      ,					a      :    int	)->       None:





     """simple docstring"""







     try:
       if len(self.queues[priority]	) >= 100:
         raise OverflowError('Maximum queue size is 100'	)
       self.queues[priority].append(a	)
     except IndexError:
       raise ValueError('Valid priorities are 0, 1, and 2'	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    int	)->       int:





     """simple docstring"""







     for queue in self.queues:
       if queue:
         return queue.pop(0	)
     raise UnderFlowError('All queues are empty'	)


   def __str__(   self      :    Dict	)->       str:





     """simple docstring"""







     return "\n".join(f"""Priority {i}: {q}""" for i, q in enumerate(self.queues	)	)






class     SCREAMING_SNAKE_CASE       :


   def __init__(   self      :    Optional[Any]	)->       Any:





     """simple docstring"""







     lowercase__           =  []


   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]      ,					a      :    int	)->       None:





     """simple docstring"""







     if len(self.queue	) == 100:
       raise OverFlowError('Maximum queue size is 100'	)
     self.queue.append(a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[Any]	)->       int:





     """simple docstring"""







     if not self.queue:
       raise UnderFlowError('The queue is empty'	)
     else:
       lowercase__           =  min(self.queue	)
       self.queue.remove(a	)
       return data


   def __str__(   self      :    Union[str, Any]	)->       str:





     """simple docstring"""







     return str(self.queue	)






def       __UpperCamelCase  ()    ->       str:
  lowercase__           =  FixedPriorityQueue()
  fpq.enqueue(0		,						10		)
  fpq.enqueue(1		,						70		)
  fpq.enqueue(0		,						100		)
  fpq.enqueue(2		,						1		)
  fpq.enqueue(2		,						5		)
  fpq.enqueue(1		,						7		)
  fpq.enqueue(2		,						4		)
  fpq.enqueue(1		,						64		)
  fpq.enqueue(0		,						128		)
  print(_SCREAMING_SNAKE_CASE		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)
  print(_SCREAMING_SNAKE_CASE		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)
  print(fpq.dequeue()		)




def       __UpperCamelCase  ()    ->       List[str]:
  lowercase__           =  ElementPriorityQueue()
  epq.enqueue(10		)
  epq.enqueue(70		)
  epq.enqueue(100		)
  epq.enqueue(1		)
  epq.enqueue(5		)
  epq.enqueue(7		)
  epq.enqueue(4		)
  epq.enqueue(64		)
  epq.enqueue(128		)
  print(_SCREAMING_SNAKE_CASE		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)
  print(_SCREAMING_SNAKE_CASE		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)
  print(epq.dequeue()		)


if __name__ == "__main__":
      fixed_priority_queue()
      element_priority_queue()


