




import os

import numpy
import onnx


def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase )->	List[Any]:
		SCREAMING_SNAKE_CASE_					      =							a.name
		SCREAMING_SNAKE_CASE_					      =							b.name

		SCREAMING_SNAKE_CASE_					      =							''
		SCREAMING_SNAKE_CASE_					      =							''

		SCREAMING_SNAKE_CASE_					      =							a == b

		SCREAMING_SNAKE_CASE_					      =							name_a
		SCREAMING_SNAKE_CASE_					      =							name_b

		return res


def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase    ,						lowerCAmelCase )->	List[Any]:
		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 					_a							(					lowerCAmelCase    ,						lowerCAmelCase    ,						lowerCAmelCase )->	List[str]:
		for n in graph_proto.node:
				_node_replace_input_with(lowerCAmelCase    ,						lowerCAmelCase    ,						lowerCAmelCase )


def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase    ,						lowerCAmelCase )->	List[Any]:
		SCREAMING_SNAKE_CASE_					      =							list(model.graph.initializer )
		SCREAMING_SNAKE_CASE_					      =							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

				SCREAMING_SNAKE_CASE_					      =							inits[i].name
				SCREAMING_SNAKE_CASE_					      =							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 					_a							(					lowerCAmelCase )->	Optional[Any]:
		SCREAMING_SNAKE_CASE_					      =							os.path.dirname(lowerCAmelCase )
		SCREAMING_SNAKE_CASE_					      =							os.path.basename(lowerCAmelCase )

		SCREAMING_SNAKE_CASE_					      =							onnx.load(os.path.join(lowerCAmelCase    ,						lowerCAmelCase ) )

		SCREAMING_SNAKE_CASE_					      =							list(model.graph.initializer )

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

		SCREAMING_SNAKE_CASE_					      =							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 )

								SCREAMING_SNAKE_CASE_					      =							inits[j].data_type
								SCREAMING_SNAKE_CASE_					      =							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

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

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

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

		SCREAMING_SNAKE_CASE_					      =							sorted(lowerCAmelCase )
		_remove_dup_initializers_from_model(lowerCAmelCase    ,						lowerCAmelCase    ,						lowerCAmelCase )

		SCREAMING_SNAKE_CASE_					      =							'optimized_' + model_file_name
		SCREAMING_SNAKE_CASE_					      =							os.path.join(lowerCAmelCase    ,						lowerCAmelCase )
		onnx.save(lowerCAmelCase    ,						lowerCAmelCase )

		return new_model





def 					_a							(					lowerCAmelCase    ,						lowerCAmelCase )->	List[str]:
		SCREAMING_SNAKE_CASE_					      =							[1]
		for i in range(2    ,						lowerCAmelCase ):
				factorials.append(factorials[-1] * i )
		assert 0 <= k < factorials[-1] * n, "k out of bounds"

		SCREAMING_SNAKE_CASE_					      =							[]
		SCREAMING_SNAKE_CASE_					      =							list(range(lowerCAmelCase ) )

		# Find permutation
		while factorials:
				SCREAMING_SNAKE_CASE_					      =							factorials.pop()
				SCREAMING_SNAKE_CASE_      ,				SCREAMING_SNAKE_CASE_					      =							divmod(lowerCAmelCase    ,						lowerCAmelCase )
				permutation.append(elements[number] )
				elements.remove(elements[number] )
		permutation.append(elements[0] )

		return permutation


if __name__ == "__main__":
						import doctest

						doctest.testmod()