

'''simple docstring'''

import argparse
import os

import torch
from emmental.modules import ThresholdBinarizer, TopKBinarizer




def  UpperCamelCase(	UpperCAmelCase_      ):
 UpperCAmelCase			:      Union[str, Any]		   =					args.serialization_dir
 UpperCAmelCase			:      str		   =					args.pruning_method
 UpperCAmelCase			:      Dict		   =					args.threshold

 UpperCAmelCase			:      int		   =					torch.load(os.path.join(UpperCAmelCase_    ,			'pytorch_model.bin'      )    ,			map_location='cpu'      )

 UpperCAmelCase			:      Optional[int]		   =					0  # Number of remaining (not pruned) params in the encoder
 UpperCAmelCase			:      List[str]		   =					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":
    UpperCAmelCase			:      Union[str, Any]		   =					TopKBinarizer.apply(UpperCAmelCase_    ,			UpperCAmelCase_      ).sum().item()
   elif pruning_method == "sigmoied_threshold":
    UpperCAmelCase			:      int		   =					ThresholdBinarizer.apply(UpperCAmelCase_    ,			UpperCAmelCase_    ,			UpperCAmelCase_      ).sum().item()
   elif pruning_method == "l0":
    UpperCAmelCase   ,					UpperCAmelCase			:      Tuple		   =					-0.1, 1.1
    UpperCAmelCase			:      str		   =					torch.sigmoid(UpperCAmelCase_      )
    UpperCAmelCase			:      List[Any]		   =					s * (r - l) + l
    UpperCAmelCase			:      str		   =					s_bar.clamp(min=0.0    ,			max=1.0      )
    UpperCAmelCase			:      str		   =					(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(UpperCAmelCase_      )      )
  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__":
 lowercase__            =     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",
 )

 lowercase__            =     parser.parse_args()

 main(args)









'''simple docstring'''







def 			_lowerCAmelCase(      UpperCAmelCase_      :	list					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	int						) ->							int:
							lowerCAmelCase__  =   int((lower_bound + upper_bound) // 2						)
							if array[r] == value:
														return r
							if lower_bound >= upper_bound:
														return -1
							if array[r] < value:
														return binary_search(UpperCAmelCase_					, r + 1					, UpperCAmelCase_					, UpperCAmelCase_						)
							else:
														return binary_search(UpperCAmelCase_					, UpperCAmelCase_					, r - 1					, UpperCAmelCase_						)
def 			_lowerCAmelCase(      UpperCAmelCase_      :	int					, UpperCAmelCase_      :	list						) ->							list:
							lowerCAmelCase__  =   0
							if matrix[index][0] == value:
														return [index, 0]
							while index < len(UpperCAmelCase_						) and matrix[index][0] < value:
														lowerCAmelCase__  =   binary_search(matrix[index]					, 0					, len(matrix[index]						) - 1					, UpperCAmelCase_						)
														if r != -1:
																					return [index, r]
														index += 1
							return [-1, -1]


if __name__ == "__main__":
		import doctest

		doctest.testmod()





