


"""simple docstring"""
import os

import numpy
import onnx






def 		lowercase							(     _snake_case						:      Any     ,   _snake_case						:      List[Any]     )     ->int:
	"""simple docstring"""





	__snake_case	:						str						=				a.name
	__snake_case	:						Any						=				b.name

	__snake_case	:						int						=				''''''
	__snake_case	:						Tuple						=				''''''

	__snake_case	:						str						=				a == b

	__snake_case	:						str						=				name_a
	__snake_case	:						Optional[Any]						=				name_b

	return res






def 		lowercase							(     _snake_case						:      Dict     ,   _snake_case						:      List[str]     ,   _snake_case						:      List[Any]     )     ->Optional[int]:
	"""simple docstring"""





	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						:      List[str]     ,   _snake_case						:      Optional[int]     ,   _snake_case						:      List[Any]     )     ->List[Any]:
	"""simple docstring"""





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






def 		lowercase							(     _snake_case						:      List[str]     ,   _snake_case						:      Optional[Any]     ,   _snake_case						:      Dict     )     ->int:
	"""simple docstring"""





	__snake_case	:						int						=				list(model.graph.initializer     )
	__snake_case	:						Union[str, 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

		__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     ,   _snake_case     ,   _snake_case     )






def 		lowercase							(     _snake_case						:      List[str]     )     ->str:
	"""simple docstring"""





	__snake_case	:						Union[str, Any]						=				os.path.dirname(_snake_case     )
	__snake_case	:						Optional[Any]						=				os.path.basename(_snake_case     )

	__snake_case	:						Any						=				onnx.load(os.path.join(_snake_case     ,   _snake_case     )     )

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

	__snake_case	:						Tuple						=				set()
	__snake_case	:						List[str]						=				{}
	__snake_case	:						Optional[int]						=				[]

	__snake_case	:						Optional[Any]						=				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     )

				__snake_case	:						List[Any]						=				inits[j].data_type
				__snake_case	:						List[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: '''     ,   _snake_case     )
				total_reduced_size += mem_size

				__snake_case	:						Optional[Any]						=				inits[i].name
				__snake_case	:						Dict						=				inits[j].name

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

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

	__snake_case	:						Any						=				sorted(_snake_case     )
	_remove_dup_initializers_from_model(_snake_case     ,   _snake_case     ,   _snake_case     )

	__snake_case	:						List[Any]						=				'''optimized_''' + model_file_name
	__snake_case	:						Any						=				os.path.join(_snake_case     ,   _snake_case     )
	onnx.save(_snake_case     ,   _snake_case     )

	return new_model









"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
#   python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since the output of this script is fed into Makefile commands it doesn't print a newline after the results

import re
import subprocess
import sys


SCREAMING_SNAKE_CASE :    Union[str, Any]									=				subprocess.check_output("""git merge-base main HEAD""".split()).decode("""utf-8""")
SCREAMING_SNAKE_CASE :    Any									=				subprocess.check_output(F'git diff --name-only {fork_point_sha}'.split()).decode("""utf-8""").split()

SCREAMING_SNAKE_CASE :    Union[str, Any]									=				"""|""".join(sys.argv[1:])
SCREAMING_SNAKE_CASE :    int									=				re.compile(rF'^({joined_dirs}).*?\.py$')

SCREAMING_SNAKE_CASE :    str									=				[x for x in modified_files if regex.match(x)]
print(""" """.join(relevant_modified_files), end="""""")





