





import os

import numpy
import onnx

def     a_       (					lowerCAmelCase_ :     List[str],      lowerCAmelCase_ :     List[Any]      ):
   __lowerCAmelCase				      =      a.name
   __lowerCAmelCase				      =      b.name

   __lowerCAmelCase				      =      ''
   __lowerCAmelCase				      =      ''

   __lowerCAmelCase				      =      a == b

   __lowerCAmelCase				      =      name_a
   __lowerCAmelCase				      =      name_b

   return res

def     a_       (					lowerCAmelCase_ :     int,      lowerCAmelCase_ :     str,      lowerCAmelCase_ :     List[Any]      ):



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

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

def     a_       (					lowerCAmelCase_ :     Optional[Any],      lowerCAmelCase_ :     Optional[Any],      lowerCAmelCase_ :     int      ):



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

def     a_       (					lowerCAmelCase_ :     Any,      lowerCAmelCase_ :     int,      lowerCAmelCase_ :     Dict      ):
   __lowerCAmelCase				      =      list(model.graph.initializer      )
   __lowerCAmelCase				      =      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

      __lowerCAmelCase				      =      inits[i].name
      __lowerCAmelCase				      =      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,      __A,      __A      )




def     a_       (					lowerCAmelCase_ :     int      ):
   __lowerCAmelCase				      =      os.path.dirname(__A      )
   __lowerCAmelCase				      =      os.path.basename(__A      )

   __lowerCAmelCase				      =      onnx.load(os.path.join(__A,      __A      )      )

   __lowerCAmelCase				      =      list(model.graph.initializer      )

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

   __lowerCAmelCase				      =      0

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

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

            __lowerCAmelCase				      =      inits[j].data_type
            __lowerCAmelCase				      =      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: ',      __A      )
            total_reduced_size += mem_size

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

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

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

   __lowerCAmelCase				      =      sorted(__A      )
   _remove_dup_initializers_from_model(__A,      __A,      __A      )

   __lowerCAmelCase				      =      'optimized_' + model_file_name
   __lowerCAmelCase				      =      os.path.join(__A,      __A      )
   onnx.save(__A,      __A      )

   return new_model






'''simple docstring'''





def lowerCAmelCase    (__A):



     """simple docstring"""



     if not isinstance(__A    ,      __A):
          raise ValueError('''multiplicative_persistence() only accepts integral values''')
     if num < 0:
          raise ValueError('''multiplicative_persistence() does not accept negative values''')

     _a           =    0
     _a           =    str(__A)

     while len(__A) != 1:
          _a           =    [int(__A) for i in num_string]

          _a           =    1
          for i in range(0    ,      len(__A)):
               total *= numbers[i]

          _a           =    str(__A)

          steps += 1
     return steps




def lowerCAmelCase    (__A):



     """simple docstring"""



     if not isinstance(__A    ,      __A):
          raise ValueError('''additive_persistence() only accepts integral values''')
     if num < 0:
          raise ValueError('''additive_persistence() does not accept negative values''')

     _a           =    0
     _a           =    str(__A)

     while len(__A) != 1:
          _a           =    [int(__A) for i in num_string]

          _a           =    0
          for i in range(0    ,      len(__A)):
               total += numbers[i]

          _a           =    str(__A)

          steps += 1
     return steps


if __name__ == "__main__":
  import doctest

  doctest.testmod()



