code: 
  
  
  """simple docstring"""
  
  
  
  
  
  
  
  import argparse
  import os
  
  import torch
  from emmental.modules import ThresholdBinarizer, TopKBinarizer
  def _A		(		lowercase	):
  
  
  
  
  
  
  
      """simple docstring"""
      a					=args.serialization_dir
      a					=args.pruning_method
      a					=args.threshold
  
      a					=torch.load(os.path.join(lowercase ,					'''pytorch_model.bin'''	) ,					map_location='''cpu'''	)
  
      a					=0  # Number of remaining (not pruned) params in the encoder
      a					=0  # Number of params in the encoder
  
      print('''name'''.ljust(60 ,					''' '''	) ,					'''Remaining Weights %''' ,					'''Remaining Weight'''	)
      for name, param in st.items():
          if "encoder" not in name:
              continue
  
          if "mask_scores" in name:
              if pruning_method == "topK":
                  a					=TopKBinarizer.apply(lowercase ,					lowercase	).sum().item()
              elif pruning_method == "sigmoied_threshold":
                  a					=ThresholdBinarizer.apply(lowercase ,					lowercase ,					lowercase	).sum().item()
              elif pruning_method == "l0":
                  a	,   a					=-0.1, 1.1
                  a					=torch.sigmoid(lowercase	)
                  a					=s * (r - l) + l
                  a					=s_bar.clamp(min=0.0 ,					max=1.0	)
                  a					=(mask > 0.0).sum().item()
              else:
                  raise ValueError('''Unknown pruning method'''	)
              remaining_count += mask_ones
              print(name.ljust(60 ,					''' '''	) ,					str(round(1_00 * mask_ones / param.numel() ,					3	)	).ljust(20 ,					''' '''	) ,					str(lowercase	)	)
          else:
              encoder_count += param.numel()
              if "bias" in name or "LayerNorm" in name:
                  remaining_count += param.numel()
  
      print(''''''	)
      print('''Remaining Weights (global) %: ''' ,					1_00 * remaining_count / encoder_count	)
  
  
  if __name__ == "__main__":
         lowerCamelCase_     :     List[str]    		=						argparse.ArgumentParser()
  
         parser.add_argument(
             """--pruning_method""",
             choices=["""l0""", """topK""", """sigmoied_threshold"""],
             type=str,
             required=True,
             help=(
                 """Pruning Method (l0 = L0 regularization, topK = Movement pruning, sigmoied_threshold = Soft movement"""
                 """ pruning)"""
             ),
         )
         parser.add_argument(
             """--threshold""",
             type=float,
             required=False,
             help=(
                 """For `topK`, it is the level of remaining weights (in %) in the fine-pruned model."""
                 """For `sigmoied_threshold`, it is the threshold \tau against which the (sigmoied) scores are compared."""
                 """Not needed for `l0`"""
             ),
         )
         parser.add_argument(
             """--serialization_dir""",
             type=str,
             required=True,
             help="""Folder containing the model that was previously fine-pruned""",
         )
  
         lowerCamelCase_     :     List[str]    		=						parser.parse_args()
  
         main(args)
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  
  
  
  from __future__ import annotations
  
  from random import randrange
  def _A		(		lowercase	):
  
  
  
  
  
  
  
      """simple docstring"""
      if len(lowercase	) < 2:
          return collection
      a					=randrange(len(lowercase	)	)  # Use random element as pivot
      a					=collection[pivot_index]
      a					=[]  # All elements greater than pivot
      a					=[]  # All elements less than or equal to pivot
  
      for element in collection[:pivot_index]:
          (greater if element > pivot else lesser).append(lowercase	)
  
      for element in collection[pivot_index + 1 :]:
          (greater if element > pivot else lesser).append(lowercase	)
  
      return [*quick_sort(lowercase	), pivot, *quick_sort(lowercase	)]
  
  
  if __name__ == "__main__":
         lowerCamelCase_     :     Union[str, Any]    		=						input("""Enter numbers separated by a comma:\n""").strip()
         lowerCamelCase_     :     Union[str, Any]    		=						[int(item) for item in user_input.split(""",""")]
         print(quick_sort(unsorted))