






# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation

import warnings

from .state import AcceleratorState, GradientState


warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_scheduler""")


class     _a							:






  """simple docstring"""





  def __init__(  self		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase = True		,		_UpperCAmelCase = False			)      ->			str:
     UpperCamelCase_						=  scheduler
     UpperCamelCase_						=  optimizers if isinstance(_UpperCAmelCase		,		(list, tuple)			) else [optimizers]
     UpperCamelCase_						=  split_batches
     UpperCamelCase_						=  step_with_optimizer
     UpperCamelCase_						=  GradientState()




  def  _UpperCAmelCase  (  self		,		*_UpperCAmelCase		,		**_UpperCAmelCase			)      ->			List[Any]:
     if not self.step_with_optimizer:
        # No link between scheduler and optimizer -> just step
        self.scheduler.step(*_UpperCAmelCase		,		**_UpperCAmelCase			)
        return

     # Otherwise, first make sure the optimizer was stepped.
     if not self.gradient_state.sync_gradients:
        if self.gradient_state.adjust_scheduler:
           self.scheduler._step_count += 1
        return

     for opt in self.optimizers:
        if opt.step_was_skipped:
           return
     if self.split_batches:
        # Split batches -> the training dataloader batch size is not changed so one step per training step
        self.scheduler.step(*_UpperCAmelCase		,		**_UpperCAmelCase			)
     else:
        # Otherwise the training dataloader batch size was multiplied by `num_processes`, so we need to do
        # num_processes steps per training step
        UpperCamelCase_						=  AcceleratorState().num_processes
        for _ in range(_UpperCAmelCase			):
           # Special case when using OneCycle and `drop_last` was not used
           if hasattr(self.scheduler		,		'total_steps'			):
              if self.scheduler._step_count <= self.scheduler.total_steps:
                 self.scheduler.step(*_UpperCAmelCase		,		**_UpperCAmelCase			)
           else:
              self.scheduler.step(*_UpperCAmelCase		,		**_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self			)      ->			List[Any]:
     return self.scheduler.get_last_lr()




  def  _UpperCAmelCase  (  self			)      ->			Union[str, Any]:
     return self.scheduler.state_dict()




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			List[str]:
     self.scheduler.load_state_dict(_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self			)      ->			List[Any]:
     return self.scheduler.get_lr()




  def  _UpperCAmelCase  (  self		,		*_UpperCAmelCase		,		**_UpperCAmelCase			)      ->			Optional[Any]:
     return self.scheduler.print_lr(*_UpperCAmelCase		,		**_UpperCAmelCase			)








'''simple docstring'''

import os
from collections.abc import Iterator

def 					__UpperCamelCase				(						lowercase__    :	str = "."			):






     '''simple docstring'''





     for dir_path, dir_names, filenames in os.walk(lowercase__			):
          __lowercase      		=[d for d in dir_names if d != 'scripts' and d[0] not in '._']
          for filename in filenames:
               if filename == "__init__.py":
                    continue
               if os.path.splitext(lowercase__			)[1] in (".py", ".ipynb"):
                    yield os.path.join(lowercase__,       lowercase__			).lstrip('./'			)

def 					__UpperCamelCase				(						lowercase__    :	Optional[Any]			):






     '''simple docstring'''





     return F'''{i * "  "}*''' if i else "\n##"

def 					__UpperCamelCase				(						lowercase__    :	str,       lowercase__    :	str			):






     '''simple docstring'''





     __lowercase      		=old_path.split(os.sep			)
     for i, new_part in enumerate(new_path.split(os.sep			)			):
          if (i + 1 > len(lowercase__			) or old_parts[i] != new_part) and new_part:
               print(F'''{md_prefix(lowercase__			)} {new_part.replace("_",       " "			).title()}'''			)
     return new_path

def 					__UpperCamelCase				(						lowercase__    :	str = "."			):






     '''simple docstring'''





     __lowercase      		=''
     for filepath in sorted(good_file_paths(lowercase__			)			):
          __lowercase		,  __lowercase      		=os.path.split(lowercase__			)
          if filepath != old_path:
               __lowercase      		=print_path(lowercase__,       lowercase__			)
          __lowercase      		=(filepath.count(os.sep			) + 1) if filepath else 0
          __lowercase      		=F'''{filepath}/{filename}'''.replace(' ',       '%20'			)
          __lowercase      		=os.path.splitext(filename.replace('_',       ' '			).title()			)[0]
          print(F'''{md_prefix(lowercase__			)} [{filename}]({url})'''			)


if __name__ == "__main__":
       print_directory_md('''.''')


