


"""simple docstring"""





def    _snake_case  (  _snake_case :	str = "The quick brown fox jumps over the lazy dog"       ,      ):
      lowerCAmelCase    :		List[str]				=      set()

      # Replace all the whitespace in our sentence
      lowerCAmelCase    :		List[Any]				=      input_str.replace(''' '''       ,      ''''''	)
      for alpha in input_str:
            if "a" <= alpha.lower() <= "z":
                  frequency.add(alpha.lower()	)
      return len(_snake_case	) == 26


def    _snake_case  (  _snake_case :	str = "The quick brown fox jumps over the lazy dog"       ,      ):
      lowerCAmelCase    :		Tuple				=      [False] * 26
      for char in input_str:
            if char.islower():
                  lowerCAmelCase    :		int				=      True
            elif char.isupper():
                  lowerCAmelCase    :		Optional[Any]				=      True
      return all(_snake_case	)


def    _snake_case  (  _snake_case :	str = "The quick brown fox jumps over the lazy dog"       ,      ):
      return len({char for char in input_str.lower() if char.isalpha()}	) == 26


def    _snake_case  (  ):
      from timeit import timeit

      lowerCAmelCase    :		Optional[Any]				=      '''from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'''
      print(timeit('''is_pangram()'''       ,      setup=_snake_case	)	)
      print(timeit('''is_pangram_faster()'''       ,      setup=_snake_case	)	)
      print(timeit('''is_pangram_fastest()'''       ,      setup=_snake_case	)	)
      # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
      # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()






"""simple docstring"""





from datetime import datetime

import matplotlib.pyplot as plt
import torch


def    _snake_case  (  _snake_case :	int	):
      for param in module.parameters():
            lowerCAmelCase    :		Optional[int]				=      False


def    _snake_case  (  ):
      lowerCAmelCase    :		List[str]				=      '''cuda''' if torch.cuda.is_available() else '''cpu'''
      if torch.backends.mps.is_available() and torch.backends.mps.is_built():
            lowerCAmelCase    :		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    _snake_case  (  _snake_case :	Dict	):
      lowerCAmelCase    :		Optional[int]				=      plt.imshow(_snake_case	)
      fig.axes.get_xaxis().set_visible(_snake_case	)
      fig.axes.get_yaxis().set_visible(_snake_case	)
      plt.show()






def    _snake_case  (  ):
      lowerCAmelCase    :		List[str]				=      datetime.now()
      lowerCAmelCase    :		Union[str, Any]				=      current_time.strftime('''%H:%M:%S'''	)
      return timestamp


