



'''simple docstring'''





import os

import numpy
import onnx




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     _a      =  a.name
     _a      =  b.name

     _a      =  ''''''
     _a      =  ''''''

     _a      =  a == b

     _a      =  name_a
     _a      =  name_b

     return res




def lowerCAmelCase  (__A  ,	__A  ,	__A):



     """simple docstring"""



     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 lowerCAmelCase  (__A  ,	__A  ,	__A):



     """simple docstring"""



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




def lowerCAmelCase  (__A  ,	__A  ,	__A):



     """simple docstring"""



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

          _a      =  inits[i].name
          _a      =  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 lowerCAmelCase  (__A):



     """simple docstring"""



     _a      =  os.path.dirname(a__)
     _a      =  os.path.basename(a__)

     _a      =  onnx.load(os.path.join(a__  ,	a__))

     _a      =  list(model.graph.initializer)

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

     _a      =  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__)

                    _a      =  inits[j].data_type
                    _a      =  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

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

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

     print('''total reduced size: '''  ,	total_reduced_size / 1_024 / 1_024 / 1_024  ,	'''GB''')

     _a      =  sorted(a__)
     _remove_dup_initializers_from_model(a__  ,	a__  ,	a__)

     _a      =  '''optimized_''' + model_file_name
     _a      =  os.path.join(a__  ,	a__)
     onnx.save(a__  ,	a__)

     return new_model





def     __lowerCAmelCase			(			a__						,    a__						,    a__  )       ->  list:
				__a										=    len(a__  )
				__a										=    [[0] * n for i in range(a__  )]
				for i in range(a__  ):
								__a										=    y_points[i]

				for i in range(2						,    a__  ):
								for j in range(a__						,    a__  ):
												__a										=    (
												    (xa - x_points[j - i + 1]) * q[j][i - 1]
												    - (xa - x_points[j]) * q[j - 1][i - 1]
												) / (x_points[j] - x_points[j - i + 1])

				return [q[n - 1][n - 1], q]


if __name__ == "__main__":
					import doctest

					doctest.testmod()