


'''simple docstring'''




def   _a		(lowercase__			:   str							,   lowercase__			:   str						)			->			float:






     """simple docstring"""

     def get_matched_characters(lowercase__			:   str							,   lowercase__			:   str						) -> str:
          __snake_case           =						[]
          __snake_case           =						min(len(_stra						)							,   len(_stra						)						) // 2
          for i, l in enumerate(_stra						):
               __snake_case           =						int(max(0							,   i - limit						)						)
               __snake_case           =						int(min(i + limit + 1							,   len(_stra						)						)						)
               if l in _stra[left:right]:
                    matched.append(lowercase__						)
                    __snake_case           =						f'{_stra[0:_stra.index(lowercase__						)]} {_stra[_stra.index(lowercase__						) + 1:]}'

          return "".join(lowercase__						)

     # matching characters
     __snake_case           =						get_matched_characters(lowercase__							,   lowercase__						)
     __snake_case           =						get_matched_characters(lowercase__							,   lowercase__						)
     __snake_case           =						len(lowercase__						)

     # transposition
     __snake_case           =						(
         len([(ca, ca) for ca, ca in zip(lowercase__							,   lowercase__						) if ca != ca]						) // 2
     )

     if not match_count:
          __snake_case           =						0.0
     else:
          __snake_case           =						(
              1
              / 3
              * (
                  match_count / len(lowercase__						)
                  + match_count / len(lowercase__						)
                  + (match_count - transpositions) / match_count
              )
          )

     # common prefix up to 4 characters
     __snake_case           =						0
     for ca, ca in zip(stra[:4]							,   stra[:4]						):
          if ca == ca:
               prefix_len += 1
          else:
               break

     return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(jaro_winkler("hello", "world"))










import os

import numpy
import onnx





def        __UpperCAmelCase						(							lowerCamelCase_ :     str  ,							lowerCamelCase_ :     Optional[Any]  )       ->  Optional[int]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : int					  =      a.name
			SCREAMING_SNAKE_CASE_   : Dict					  =      b.name

			SCREAMING_SNAKE_CASE_   : str					  =      ''
			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      ''

			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      a == b

			SCREAMING_SNAKE_CASE_   : str					  =      name_a
			SCREAMING_SNAKE_CASE_   : str					  =      name_b

			return res





def        __UpperCAmelCase						(							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     str  ,							lowerCamelCase_ :     Dict  )       ->  Optional[int]:







			"""simple docstring"""





			for i, input_name in enumerate(node_proto.input  ):
						if input_name == name:
									node_proto.input.insert(lowerCamelCase_  ,							lowerCamelCase_  )
									node_proto.input.pop(i + 1  )

			if node_proto.op_type == "If":
						_graph_replace_input_with(node_proto.attribute[0].g  ,							lowerCamelCase_  ,							lowerCamelCase_  )
						_graph_replace_input_with(node_proto.attribute[1].g  ,							lowerCamelCase_  ,							lowerCamelCase_  )
			if node_proto.op_type == "Loop":
						_graph_replace_input_with(node_proto.attribute[0].g  ,							lowerCamelCase_  ,							lowerCamelCase_  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     Tuple  ,							lowerCamelCase_ :     Optional[int]  ,							lowerCamelCase_ :     Dict  )       ->  List[Any]:







			"""simple docstring"""





			for n in graph_proto.node:
						_node_replace_input_with(lowerCamelCase_  ,							lowerCamelCase_  ,							lowerCamelCase_  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     Tuple  ,							lowerCamelCase_ :     Tuple  ,							lowerCamelCase_ :     Any  )       ->  str:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : str					  =      list(model.graph.initializer  )
			SCREAMING_SNAKE_CASE_   : List[str]					  =      list(model_without_ext.graph.initializer  )
			for i, ref_i in ind_to_replace:
						assert inits_with_data[i].name == inits[i].name
						assert inits_with_data[ref_i].name == inits[ref_i].name
						assert i > ref_i

						SCREAMING_SNAKE_CASE_   : List[str]					  =      inits[i].name
						SCREAMING_SNAKE_CASE_   : str					  =      inits[ref_i].name

						model_without_ext.graph.initializer.remove(inits[i]  )

						# for n in model.graph.node:
						_graph_replace_input_with(model_without_ext.graph  ,							lowerCamelCase_  ,							lowerCamelCase_  )





def        __UpperCAmelCase						(							lowerCamelCase_ :     Dict  )       ->  Dict:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Tuple					  =      os.path.dirname(lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : Tuple					  =      os.path.basename(lowerCamelCase_  )

			SCREAMING_SNAKE_CASE_   : int					  =      onnx.load(os.path.join(lowerCamelCase_  ,							lowerCamelCase_  )  )

			SCREAMING_SNAKE_CASE_   : Any					  =      list(model.graph.initializer  )

			SCREAMING_SNAKE_CASE_   : int					  =      set()
			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      {}
			SCREAMING_SNAKE_CASE_   : Dict					  =      []

			SCREAMING_SNAKE_CASE_   : int					  =      0

			for i in range(len(lowerCamelCase_  )  ):
						if i in dup_set:
									continue

						for j in range(i + 1  ,							len(lowerCamelCase_  )  ):
									if j in dup_set:
												continue
									if _is_equal_tensor_proto(inits[i]  ,							inits[j]  ):
												dup_set.add(lowerCamelCase_  )
												dup_set.add(lowerCamelCase_  )

												SCREAMING_SNAKE_CASE_   : int					  =      inits[j].data_type
												SCREAMING_SNAKE_CASE_   : str					  =      numpy.prod(inits[j].dims  )
												if dtype == 1:
															mem_size *= 4
												elif dtype == 6:
															mem_size *= 4
												elif dtype == 7 or dtype == 11:
															mem_size *= 8
												else:
															print('unexpected data type: '  ,							lowerCamelCase_  )
												total_reduced_size += mem_size

												SCREAMING_SNAKE_CASE_   : int					  =      inits[i].name
												SCREAMING_SNAKE_CASE_   : List[Any]					  =      inits[j].name

												if name_i in dup_map:
															dup_map[name_i].append(lowerCamelCase_  )
												else:
															SCREAMING_SNAKE_CASE_   : Optional[int]					  =      [name_j]
												ind_to_replace.append((j, i)  )

			print('total reduced size: '  ,							total_reduced_size / 10_24 / 10_24 / 10_24  ,							'GB'  )

			SCREAMING_SNAKE_CASE_   : int					  =      sorted(lowerCamelCase_  )
			_remove_dup_initializers_from_model(lowerCamelCase_  ,							lowerCamelCase_  ,							lowerCamelCase_  )

			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      'optimized_' + model_file_name
			SCREAMING_SNAKE_CASE_   : Optional[int]					  =      os.path.join(lowerCamelCase_  ,							lowerCamelCase_  )
			onnx.save(lowerCamelCase_  ,							lowerCamelCase_  )

			return new_model



