





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


SCREAMING_SNAKE_CASE_						   =       logging.get_logger(__name__)

@dataclass
class 		UpperCamelCase__ (      lowerCAmelCase_   ):



     '''simple docstring'''

     __snake_case    :	Any			=			[
         "no_inference",
         "no_cuda",
         "no_tpu",
         "no_speed",
         "no_memory",
         "no_env_print",
         "no_multi_process",
     ]






     def __init__(							self						:    List[str]						,**lowerCamelCase__						:    Optional[int]       )     ->		List[Any]:




           '''simple docstring'''


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

           SCREAMING_SNAKE_CASE		=						kwargs.pop("""torchscript"""						,self.torchscript       )
           SCREAMING_SNAKE_CASE		=						kwargs.pop("""torch_xla_tpu_print_metrics"""						,self.torch_xla_tpu_print_metrics       )
           SCREAMING_SNAKE_CASE		=						kwargs.pop("""fp16_opt_level"""						,self.fpaa_opt_level       )
           super().__init__(**lowerCamelCase__       )

     __snake_case    :	bool			=			field(default=lowerCAmelCase_							,      metadata={"help": "Trace the models using torchscript"}   )
     __snake_case    :	bool			=			field(default=lowerCAmelCase_							,      metadata={"help": "Print Xla/PyTorch tpu metrics"}   )
     __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 				SCREAMING_SNAKE_CASE__  (							self						:    Tuple       )     ->		Tuple["torch.device", int]:




           '''simple docstring'''


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






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




           '''simple docstring'''


           return is_torch_tpu_available() and self.tpu






     @property
     def 				SCREAMING_SNAKE_CASE__  (							self						:    List[str]       )     ->		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						:    Union[str, Any]       )     ->		"torch.device":




           '''simple docstring'''


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






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




           '''simple docstring'''


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






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




           '''simple docstring'''


           return self.n_gpu > 0









from collections import defaultdict
from math import gcd



def    __lowercase   (      _SCREAMING_SNAKE_CASE = 1_50_00_00	) ->   int:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						defaultdict(_SCREAMING_SNAKE_CASE	)
      SCREAMING_SNAKE_CASE		=						2
      while 2 * euclid_m * (euclid_m + 1) <= limit:
            for euclid_n in range((euclid_m % 2) + 1 ,						_SCREAMING_SNAKE_CASE ,						2	):
                  if gcd(_SCREAMING_SNAKE_CASE ,						_SCREAMING_SNAKE_CASE	) > 1:
                        continue
                  SCREAMING_SNAKE_CASE		=						2 * euclid_m * (euclid_m + euclid_n)
                  for perimeter in range(_SCREAMING_SNAKE_CASE ,						limit + 1 ,						_SCREAMING_SNAKE_CASE	):
                        frequencies[perimeter] += 1
            euclid_m += 1
      return sum(1 for frequency in frequencies.values() if frequency == 1	)


if __name__ == "__main__":
      print(F'''{solution() = }''')


