

'''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


_lowerCAmelCase         =						logging.get_logger(__name__)






@dataclass
class   _SCREAMING_SNAKE_CASE   (   __a     ):
 __SCREAMING_SNAKE_CASE					:str      	=					[
     """no_inference""",
     """no_cuda""",
     """no_tpu""",
     """no_speed""",
     """no_memory""",
     """no_env_print""",
     """no_multi_process""",
 ]



 def __init__(   self		:   Optional[int]			,				**a__		:   Optional[int]      ):
      for deprecated_arg in self.deprecated_args:
           if deprecated_arg in kwargs:
                __magic_name__						       =    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]}'''      )

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

 __SCREAMING_SNAKE_CASE					:bool      	=					field(default=__a		,metadata={"""help""": """Trace the models using torchscript"""}     )
 __SCREAMING_SNAKE_CASE					:bool      	=					field(default=__a		,metadata={"""help""": """Print Xla/PyTorch tpu metrics"""}     )
 __SCREAMING_SNAKE_CASE					: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 			snake_case__  (   self		:   int      ):
      requires_backends(self			,				['''torch''']      )
      logger.info('''PyTorch: setting up devices'''      )
      if not self.cuda:
           __magic_name__						       =    torch.device('''cpu'''      )
           __magic_name__						       =    0
      elif is_torch_tpu_available():
           __magic_name__						       =    xm.xla_device()
           __magic_name__						       =    0
      else:
           __magic_name__						       =    torch.device('''cuda''' if torch.cuda.is_available() else '''cpu'''      )
           __magic_name__						       =    torch.cuda.device_count()
      return device, n_gpu



 @property
 def 			snake_case__  (   self		:   Union[str, Any]      ):
      return is_torch_tpu_available() and self.tpu



 @property
 def 			snake_case__  (   self		:   Optional[Any]      ):
      requires_backends(self			,				['''torch''']      )
      # TODO(PVP): currently only single GPU is supported
      return torch.cuda.current_device()



 @property
 def 			snake_case__  (   self		:   List[str]      ):
      requires_backends(self			,				['''torch''']      )
      return self._setup_devices[0]



 @property
 def 			snake_case__  (   self		:   List[str]      ):
      requires_backends(self			,				['''torch''']      )
      return self._setup_devices[1]



 @property
 def 			snake_case__  (   self		:   List[str]      ):
      return self.n_gpu > 0









'''simple docstring'''




from random import randint, random




def 						UpperCamelCase	(			a		,						a		,						a		,						a = False		,						a = False		,						a = 5		,						)				->     list:






     '''simple docstring'''
     __magic_name__						       =    [[-1] * number_of_cells]  # Create a highway without any car
     __magic_name__						       =    0
     __magic_name__						       =    max(a		,						0			)
     while i < number_of_cells:
          __magic_name__						       =    (
              randint(0		,						a			) if random_speed else initial_speed
          )  # Place the cars
          i += (
              randint(1		,						max_speed * 2			) if random_frequency else frequency
          )  # Arbitrary number, may need tuning
     return highway




def 						UpperCamelCase	(			a		,						a			)				->     int:






     '''simple docstring'''
     __magic_name__						       =    0
     __magic_name__						       =    highway_now[car_index + 1 :]
     for cell in range(len(a			)			):  # May need a better name for this
          if cells[cell] != -1:  # If the cell is not empty then
               return distance  # we have the distance we wanted
          distance += 1
     # Here if the car is near the end of the highway
     return distance + get_distance(a		,						-1			)




def 						UpperCamelCase	(			a		,						a		,						a			)				->     list:






     '''simple docstring'''
     __magic_name__						       =    len(a			)
     # Beforce calculations, the highway is empty
     __magic_name__						       =    [-1] * number_of_cells

     for car_index in range(a			):
          if highway_now[car_index] != -1:
               # Add 1 to the current speed of the car and cap the speed
               __magic_name__						       =    min(highway_now[car_index] + 1		,						a			)
               # Number of empty cell before the next car
               __magic_name__						       =    get_distance(a		,						a			) - 1
               # We can't have the car causing an accident
               __magic_name__						       =    min(next_highway[car_index]		,						a			)
               if random() < probability:
                    # Randomly, a driver will slow down
                    __magic_name__						       =    max(next_highway[car_index] - 1		,						0			)
     return next_highway




def 						UpperCamelCase	(			a		,						a		,						a		,						a			)				->     list:






     '''simple docstring'''
     __magic_name__						       =    len(highway[0]			)

     for i in range(a			):
          __magic_name__						       =    update(highway[i]		,						a		,						a			)
          __magic_name__						       =    [-1] * number_of_cells

          for car_index in range(a			):
               __magic_name__						       =    next_speeds_calculated[car_index]
               if speed != -1:
                    # Change the position based on the speed (with % to create the loop)
                    __magic_name__						       =    (car_index + speed) % number_of_cells
                    # Commit the change of position
                    __magic_name__						       =    speed
          highway.append(a			)

     return highway


if __name__ == "__main__":
      import doctest

      doctest.testmod()






