
"""simple docstring"""





import argparse
import json
import os

from tensorflow.core.protobuf.saved_model_pba import SavedModel


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase_       :    Tuple						      =			'''.'''

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
UpperCamelCase_       :    List[Any]						      =			[
    '''Assert''',
    '''AssignVariableOp''',
    '''EmptyTensorList''',
    '''MergeV2Checkpoints''',
    '''ReadVariableOp''',
    '''ResourceGather''',
    '''RestoreV2''',
    '''SaveV2''',
    '''ShardedFilename''',
    '''StatefulPartitionedCall''',
    '''StaticRegexFullMatch''',
    '''VarHandleOp''',
]
def 				A_  (__a					, __a					, __a					):

					'''simple docstring'''





					A_								=    SavedModel()
					A_								=    []

					with open(os.path.join(__a					, "utils"					, "tf_ops"					, "onnx.json"					)					) as f:
										A_								=    json.load(__a					)["opsets"]

					for i in range(1					, opset + 1					):
										onnx_ops.extend(onnx_opsets[str(__a					)]					)

					with open(__a					, "rb"					) as f:
										saved_model.ParseFromString(f.read()					)

					A_								=    set()

					# Iterate over every metagraph in case there is more than one (a saved model can contain multiple graphs)
					for meta_graph in saved_model.meta_graphs:
										# Add operations in the graph definition
										model_op_names.update(node.op for node in meta_graph.graph_def.node					)

										# Go through the functions in the graph definition
										for func in meta_graph.graph_def.library.function:
															# Add operations in each function
															model_op_names.update(node.op for node in func.node_def					)

    # Convert to list, sorted if you want
					A_								=    sorted(__a					)
					A_								=    []

					for op in model_op_names:
										if op not in onnx_ops and op not in INTERNAL_OPS:
															incompatible_ops.append(__a					)

					if strict and len(__a					) > 0:
										raise Exception(f'Found the following incompatible ops for the opset {opset}:\n' + incompatible_ops					)
					elif len(__a					) > 0:
										print(f'Found the following incompatible ops for the opset {opset}:'					)
										print(*__a					, sep="\n"					)
					else:
										print(f'The saved model {saved_model_path} can properly be converted with ONNX.'					)


if __name__ == "__main__":
		UpperCamelCase_       :    str						      =			argparse.ArgumentParser()
		parser.add_argument('''--saved_model_path''', help='''Path of the saved model to check (the .pb file).''')
		parser.add_argument(
		    '''--opset''', default=12, type=int, help='''The ONNX opset against which the model has to be tested.'''
		)
		parser.add_argument(
		    '''--framework''', choices=['''onnx'''], default='''onnx''', help='''Frameworks against which to test the saved model.'''
		)
		parser.add_argument(
		    '''--strict''', action='''store_true''', help='''Whether make the checking strict (raise errors) or not (raise warnings)'''
		)
		UpperCamelCase_       :    List[Any]						      =			parser.parse_args()

		if args.framework == "onnx":
				onnx_compliancy(args.saved_model_path, args.strict, args.opset)






"""simple docstring"""





from __future__ import annotations
def 				A_  (__a					, __a = None					, __a = None					):

					'''simple docstring'''





					if start is None:
										A_								=    0

					if end is None:
										A_								=    len(__a					) - 1

					if start >= end:
										return

					A_								=    (start + end) // 2

					slowsort(__a					, __a					, __a					)
					slowsort(__a					, mid + 1					, __a					)

					if sequence[end] < sequence[mid]:
										A_			,     A_								=    sequence[mid], sequence[end]

					slowsort(__a					, __a					, end - 1					)


if __name__ == "__main__":
		from doctest import testmod

		testmod()




