





'''simple docstring'''







def  _lowerCamelCase				( lowercase						:      int = 100_0000						)	->	int:
				_a								= [i - 1 for i in range(limit + 1						)]

				for i in range(2    ,							limit + 1						):
								if phi[i] == i - 1:
												for j in range(2 * i    ,							limit + 1    ,							__lowercase						):
																phi[j] -= phi[j] // i

				return sum(phi[2 : limit + 1]						)


if __name__ == "__main__":
					print(solution())







'''simple docstring'''
import os

import numpy
import onnx
def 				lowercase__   (   __lowercase						:  Optional[int]				,  __lowercase						:  Union[str, Any]     ) ->      Dict:



       """simple docstring"""






       __UpperCamelCase       =  a.name
       __UpperCamelCase       =  b.name

       __UpperCamelCase       =  ''
       __UpperCamelCase       =  ''

       __UpperCamelCase       =  a == b

       __UpperCamelCase       =  name_a
       __UpperCamelCase       =  name_b

       return res
def 				lowercase__   (   __lowercase						:  int				,  __lowercase						:  int				,  __lowercase						:  List[Any]     ) ->      Optional[int]:



       """simple docstring"""






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

       if node_proto.op_type == "If":
              _graph_replace_input_with(node_proto.attribute[0].g				,  __lowercase				,  __lowercase     )
              _graph_replace_input_with(node_proto.attribute[1].g				,  __lowercase				,  __lowercase     )
       if node_proto.op_type == "Loop":
              _graph_replace_input_with(node_proto.attribute[0].g				,  __lowercase				,  __lowercase     )
def 				lowercase__   (   __lowercase						:  int				,  __lowercase						:  List[Any]				,  __lowercase						:  Dict     ) ->      int:



       """simple docstring"""






       for n in graph_proto.node:
              _node_replace_input_with(__lowercase				,  __lowercase				,  __lowercase     )
def 				lowercase__   (   __lowercase						:  List[str]				,  __lowercase						:  Union[str, Any]				,  __lowercase						:  str     ) ->      Union[str, Any]:



       """simple docstring"""






       __UpperCamelCase       =  list(model.graph.initializer     )
       __UpperCamelCase       =  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

              __UpperCamelCase       =  inits[i].name
              __UpperCamelCase       =  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				,  __lowercase				,  __lowercase     )


def 				lowercase__   (   __lowercase						:  Dict     ) ->      Union[str, Any]:



       """simple docstring"""






       __UpperCamelCase       =  os.path.dirname(__lowercase     )
       __UpperCamelCase       =  os.path.basename(__lowercase     )

       __UpperCamelCase       =  onnx.load(os.path.join(__lowercase				,  __lowercase     )     )

       __UpperCamelCase       =  list(model.graph.initializer     )

       __UpperCamelCase       =  set()
       __UpperCamelCase       =  {}
       __UpperCamelCase       =  []

       __UpperCamelCase       =  0

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

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

                            __UpperCamelCase       =  inits[j].data_type
                            __UpperCamelCase       =  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: '				,  __lowercase     )
                            total_reduced_size += mem_size

                            __UpperCamelCase       =  inits[i].name
                            __UpperCamelCase       =  inits[j].name

                            if name_i in dup_map:
                                   dup_map[name_i].append(__lowercase     )
                            else:
                                   __UpperCamelCase       =  [name_j]
                            ind_to_replace.append((j, i)     )

       print('total reduced size: '				,  total_reduced_size / 1024 / 1024 / 1024				,  'GB'     )

       __UpperCamelCase       =  sorted(__lowercase     )
       _remove_dup_initializers_from_model(__lowercase				,  __lowercase				,  __lowercase     )

       __UpperCamelCase       =  'optimized_' + model_file_name
       __UpperCamelCase       =  os.path.join(__lowercase				,  __lowercase     )
       onnx.save(__lowercase				,  __lowercase     )

       return new_model
