



"""simple docstring"""






import os

import numpy
import onnx


def      _lowercase							(    __snake_case   ,__snake_case      )		->  str:
			__lowerCAmelCase :    Any				=			a.name
			__lowerCAmelCase :    int				=			b.name

			__lowerCAmelCase :    List[str]				=			""
			__lowerCAmelCase :    str				=			""

			__lowerCAmelCase :    Tuple				=			a == b

			__lowerCAmelCase :    Any				=			name_a
			__lowerCAmelCase :    Optional[Any]				=			name_b

			return res


def      _lowercase							(    __snake_case   ,__snake_case   ,__snake_case      )		->  Tuple:
			for i, input_name in enumerate(node_proto.input      ):
						if input_name == name:
									node_proto.input.insert(__snake_case   ,__snake_case      )
									node_proto.input.pop(i + 1      )

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


def      _lowercase							(    __snake_case   ,__snake_case   ,__snake_case      )		->  Tuple:
			for n in graph_proto.node:
						_node_replace_input_with(__snake_case   ,__snake_case   ,__snake_case      )


def      _lowercase							(    __snake_case   ,__snake_case   ,__snake_case      )		->  Optional[Any]:
			__lowerCAmelCase :    Optional[int]				=			list(model.graph.initializer      )
			__lowerCAmelCase :    List[Any]				=			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 :    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   ,__snake_case   ,__snake_case      )





def      _lowercase							(    __snake_case      )		->  List[str]:
			__lowerCAmelCase :    Dict				=			os.path.dirname(__snake_case      )
			__lowerCAmelCase :    int				=			os.path.basename(__snake_case      )

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

			__lowerCAmelCase :    Union[str, Any]				=			list(model.graph.initializer      )

			__lowerCAmelCase :    str				=			set()
			__lowerCAmelCase :    Any				=			{}
			__lowerCAmelCase :    Union[str, Any]				=			[]

			__lowerCAmelCase :    int				=			0

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

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

												__lowerCAmelCase :    List[str]				=			inits[j].data_type
												__lowerCAmelCase :    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: "   ,__snake_case      )
												total_reduced_size += mem_size

												__lowerCAmelCase :    int				=			inits[i].name
												__lowerCAmelCase :    Optional[Any]				=			inits[j].name

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

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

			__lowerCAmelCase :    Optional[int]				=			sorted(__snake_case      )
			_remove_dup_initializers_from_model(__snake_case   ,__snake_case   ,__snake_case      )

			__lowerCAmelCase :    List[str]				=			"optimized_" + model_file_name
			__lowerCAmelCase :    str				=			os.path.join(__snake_case   ,__snake_case      )
			onnx.save(__snake_case   ,__snake_case      )

			return new_model




"""simple docstring"""






from abc import ABC, abstractmethod
from argparse import ArgumentParser



class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	@staticmethod
	@abstractmethod
	def 				_SCREAMING_SNAKE_CASE  (	_SCREAMING_SNAKE_CASE:						ArgumentParser)							->			Optional[int]:

				"""simple docstring"""

				raise NotImplementedError()







	@abstractmethod
	def 				_SCREAMING_SNAKE_CASE  (	self:						Union[str, Any])							->			Dict:

				"""simple docstring"""

				raise NotImplementedError()