import os

import numpy
import onnx






def 							UpperCAmelCase__(					__UpperCAmelCase			:     str     ,				__UpperCAmelCase			:     Optional[Any]       ):
   __snake_case   :			int										=						a.name
   __snake_case   :			Dict										=						b.name

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

   __snake_case   :			Optional[Any]										=						a == b

   __snake_case   :			str										=						name_a
   __snake_case   :			str										=						name_b

   return res






def 							UpperCAmelCase__(					__UpperCAmelCase			:     int     ,				__UpperCAmelCase			:     str     ,				__UpperCAmelCase			:     Dict       ):





   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__(					__UpperCAmelCase			:     Tuple     ,				__UpperCAmelCase			:     Optional[int]     ,				__UpperCAmelCase			:     Dict       ):





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






def 							UpperCAmelCase__(					__UpperCAmelCase			:     Tuple     ,				__UpperCAmelCase			:     Tuple     ,				__UpperCAmelCase			:     Any       ):
   __snake_case   :			str										=						list(model.graph.initializer       )
   __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

      __snake_case   :			List[str]										=						inits[i].name
      __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__(					__UpperCAmelCase			:     Dict       ):
   __snake_case   :			Tuple										=						os.path.dirname(lowerCamelCase_       )
   __snake_case   :			Tuple										=						os.path.basename(lowerCamelCase_       )

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

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

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

   __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_       )

            __snake_case   :			int										=						inits[j].data_type
            __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

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

            if name_i in dup_map:
               dup_map[name_i].append(lowerCamelCase_       )
            else:
               __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'       )

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

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

   return new_model









from __future__ import annotations





def        __UpperCAmelCase						(							lowerCamelCase_ :     list[float]  )       ->  float:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Tuple					  =      0.0_0
			SCREAMING_SNAKE_CASE_   : Tuple					  =      0
			for resistor in resistors:
						if resistor <= 0:
									SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      F'Resistor at index {index} has a negative or zero value!'
									raise ValueError(lowerCamelCase_  )
						first_sum += 1 / float(lowerCamelCase_  )
						index += 1
			return 1 / first_sum





def        __UpperCAmelCase						(							lowerCamelCase_ :     list[float]  )       ->  float:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Dict					  =      0.0_0
			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      0
			for resistor in resistors:
						sum_r += resistor
						if resistor < 0:
									SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      F'Resistor at index {index} has a negative value!'
									raise ValueError(lowerCamelCase_  )
						index += 1
			return sum_r


if __name__ == "__main__":
						import doctest

						doctest.testmod()



