





"""simple docstring"""






import argparse


lowerCAmelCase_			=							"docs/source/_static/js/custom.js"

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Optional[Any]:






       """simple docstring"""




       with open(_A,encoding='utf-8',newline='\n'							) as f:
              _UpperCAmelCase     =     f.readlines()
       _UpperCAmelCase     =     0

       # First let's put the right version
       while not lines[index].startswith('const stableVersion ='							):
              index += 1
       _UpperCAmelCase     =     F"""const stableVersion = \"v{version}\"\n"""

       # Then update the dictionary
       while not lines[index].startswith('const versionMapping = {'							):
              index += 1

       # We go until the end
       while not lines[index].startswith('}'							):
              index += 1
       # We add the new version at the end
       lines[index - 1] += F"""    \"v{version}\": \"v{version}\",\n"""

       with open(_A,'w',encoding='utf-8',newline='\n'							) as f:
              f.writelines(_A							)


if __name__ == "__main__":
   lowerCAmelCase_			=							argparse.ArgumentParser()
   parser.add_argument('''--version''', help='''Release version.''')
   lowerCAmelCase_			=							parser.parse_args()
   update_custom_js(args.version)













"""simple docstring"""






from datetime import datetime

import matplotlib.pyplot as plt
import torch

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Any:






       """simple docstring"""




       for param in module.parameters():
              _UpperCAmelCase     =     False

def       __lowerCamelCase    (       )		->       Dict:






       """simple docstring"""




       _UpperCAmelCase     =     'cuda' if torch.cuda.is_available() else 'cpu'
       if torch.backends.mps.is_available() and torch.backends.mps.is_built():
              _UpperCAmelCase     =     '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    (       SCREAMING_SNAKE_CASE							)		->       str:






       """simple docstring"""




       _UpperCAmelCase     =     plt.imshow(SCREAMING_SNAKE_CASE							)
       fig.axes.get_xaxis().set_visible(SCREAMING_SNAKE_CASE							)
       fig.axes.get_yaxis().set_visible(SCREAMING_SNAKE_CASE							)
       plt.show()


def       __lowerCamelCase    (       )		->       Dict:






       """simple docstring"""




       _UpperCAmelCase     =     datetime.now()
       _UpperCAmelCase     =     current_time.strftime('%H:%M:%S'							)
       return timestamp






