




from __future__ import annotations

import typing
from collections import Counter



def      __lowerCAmelCase			(					UpperCamelCase      )     ->	typing.Counter[int]:
  lowerCAmelCase__				:  typing.Counter[int]		       =     Counter()
  for base in range(1	,      max_perimeter + 1      ):
    for perpendicular in range(UpperCamelCase	,      max_perimeter + 1      ):
      lowerCAmelCase__				:  Tuple		       =     (base * base + perpendicular * perpendicular) ** 0.5
      if hypotenuse == int(UpperCamelCase      ):
        lowerCAmelCase__				:  Any		       =     int(base + perpendicular + hypotenuse      )
        if perimeter > max_perimeter:
          continue
        triplets[perimeter] += 1
  return triplets



def      __lowerCAmelCase			(					UpperCamelCase = 1000      )     ->	int:
  lowerCAmelCase__				:  List[Any]		       =     pythagorean_triple(UpperCamelCase      )
  return triplets.most_common(1      )[0][0]


if __name__ == "__main__":
     print(F"""Perimeter {solution()} has maximum solutions""")







from datetime import datetime

import matplotlib.pyplot as plt
import torch



def      __lowerCAmelCase			(					UpperCamelCase      )     ->	str:
  for param in module.parameters():
    lowerCAmelCase__				:  int		       =     False



def      __lowerCAmelCase			(					)     ->	Optional[Any]:
  lowerCAmelCase__				:  List[Any]		       =     '''cuda''' if torch.cuda.is_available() else '''cpu'''
  if torch.backends.mps.is_available() and torch.backends.mps.is_built():
    lowerCAmelCase__				:  Optional[Any]		       =     '''mps'''
  if device == "mps":
    print(
        '''WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'''
        ''' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'''
        ''' with generations.'''      )
  return device



def      __lowerCAmelCase			(					UpperCamelCase      )     ->	List[Any]:
  lowerCAmelCase__				:  str		       =     plt.imshow(UpperCamelCase      )
  fig.axes.get_xaxis().set_visible(UpperCamelCase      )
  fig.axes.get_yaxis().set_visible(UpperCamelCase      )
  plt.show()



def      __lowerCAmelCase			(					)     ->	str:
  lowerCAmelCase__				:  Dict		       =     datetime.now()
  lowerCAmelCase__				:  Optional[int]		       =     current_time.strftime('''%H:%M:%S'''      )
  return timestamp

