


import os

import numpy
import onnx



def     __lowerCAmelCase						(							snake_case	:    str						,      snake_case	:    Dict )       ->							List[Any]:
   __lowerCamelCase:				Tuple     =	a.name
   __lowerCamelCase:				Optional[int]     =	b.name

   __lowerCamelCase:				Dict     =	""""""
   __lowerCamelCase:				List[Any]     =	""""""

   __lowerCamelCase:				int     =	a == b

   __lowerCamelCase:				List[str]     =	name_a
   __lowerCamelCase:				int     =	name_b

   return res



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



def     __lowerCAmelCase						(							snake_case	:    List[str]						,      snake_case	:    Optional[Any]						,      snake_case	:    List[str] )       ->							Union[str, Any]:
   __lowerCamelCase:				Union[str, Any]     =	list(model.graph.initializer )
   __lowerCamelCase:				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

      __lowerCamelCase:				Any     =	inits[i].name
      __lowerCamelCase:				Any     =	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     __lowerCAmelCase						(							snake_case	:    Optional[Any] )       ->							Optional[Any]:
   __lowerCamelCase:				List[Any]     =	os.path.dirname(__lowerCAmelCase )
   __lowerCamelCase:				str     =	os.path.basename(__lowerCAmelCase )

   __lowerCamelCase:				Any     =	onnx.load(os.path.join(__lowerCAmelCase						,      __lowerCAmelCase ) )

   __lowerCamelCase:				List[str]     =	list(model.graph.initializer )

   __lowerCamelCase:				Tuple     =	set()
   __lowerCamelCase:				Optional[int]     =	{}
   __lowerCamelCase:				Tuple     =	[]

   __lowerCamelCase:				Optional[Any]     =	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 )

            __lowerCamelCase:				Any     =	inits[j].data_type
            __lowerCamelCase:				Any     =	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

            __lowerCamelCase:				List[str]     =	inits[i].name
            __lowerCamelCase:				int     =	inits[j].name

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

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

   __lowerCamelCase:				Union[str, Any]     =	sorted(__lowerCAmelCase )
   _remove_dup_initializers_from_model(__lowerCAmelCase						,      __lowerCAmelCase						,      __lowerCAmelCase )

   __lowerCamelCase:				Optional[int]     =	"""optimized_""" + model_file_name
   __lowerCamelCase:				int     =	os.path.join(__lowerCAmelCase						,      __lowerCAmelCase )
   onnx.save(__lowerCAmelCase						,      __lowerCAmelCase )

   return new_model






def     __lowerCAmelCase						(							snake_case	:    int = 100 )       ->							int:
   __lowerCamelCase:				List[Any]     =	0
   __lowerCamelCase:				int     =	0
   for i in range(1						,      n + 1 ):
      sum_of_squares += i**2
      sum_of_ints += i
   return sum_of_ints**2 - sum_of_squares


if __name__ == "__main__":
   print(F"""{solution() = }""")


