

'''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
lowerCAmelCase__										= "."

# Internal TensorFlow ops that can be safely ignored (mostly specific to a saved model)
lowerCAmelCase__										= [
    "Assert",
    "AssignVariableOp",
    "EmptyTensorList",
    "MergeV2Checkpoints",
    "ReadVariableOp",
    "ResourceGather",
    "RestoreV2",
    "SaveV2",
    "ShardedFilename",
    "StatefulPartitionedCall",
    "StaticRegexFullMatch",
    "VarHandleOp",
]







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase   ,UpperCamelCase   ,UpperCamelCase  )    ->    Tuple:
	UpperCAmelCase_		:      Optional[int]       	=					SavedModel()
	UpperCAmelCase_		:      Dict       	=					[]

	with open(os.path.join(UpperCamelCase   ,'utils'   ,'tf_ops'   ,'onnx.json'  )  ) as f:
		UpperCAmelCase_		:      Any       	=					json.load(UpperCamelCase  )['opsets']

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

	with open(UpperCamelCase   ,'rb'  ) as f:
		saved_model.ParseFromString(f.read()  )

	UpperCAmelCase_		:      Dict       	=					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
	UpperCAmelCase_		:      Tuple       	=					sorted(UpperCamelCase  )
	UpperCAmelCase_		:      Union[str, Any]       	=					[]

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

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


if __name__ == "__main__":
						lowerCAmelCase__										= 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)"
						)
						lowerCAmelCase__										= parser.parse_args()

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









'''simple docstring'''


import math



class 					lowercase						:


							def __init__(			self    ,			_snake_case=0)							->				Union[str, Any]:  # a graph with Node 0,1,...,N-1
								UpperCAmelCase_		:      Tuple       	=					n
								UpperCAmelCase_		:      Optional[Any]       	=					[
								    [math.inf for j in range(0    ,			_snake_case)] for i in range(0    ,			_snake_case)
								]  # adjacency matrix for weight
								UpperCAmelCase_		:      Tuple       	=					[
								    [math.inf for j in range(0    ,			_snake_case)] for i in range(0    ,			_snake_case)
								]  # dp[i][j] stores minimum distance from i to j


							def 						_snake_case							(			self    ,			_snake_case    ,			_snake_case    ,			_snake_case)							->				List[Any]:
								UpperCAmelCase_		:      Union[str, Any]       	=					w


							def 						_snake_case							(			self)							->				str:
								for k in range(0    ,			self.n):
									for i in range(0    ,			self.n):
										for j in range(0    ,			self.n):
											UpperCAmelCase_		:      Optional[int]       	=					min(self.dp[i][j]    ,			self.dp[i][k] + self.dp[k][j])





							def 						_snake_case							(			self    ,			_snake_case    ,			_snake_case)							->				str:
								return self.dp[u][v]


if __name__ == "__main__":
						lowerCAmelCase__										= Graph(5)
						graph.add_edge(0, 2, 9)
						graph.add_edge(0, 4, 10)
						graph.add_edge(1, 3, 5)
						graph.add_edge(2, 3, 7)
						graph.add_edge(3, 0, 10)
						graph.add_edge(3, 1, 2)
						graph.add_edge(3, 2, 1)
						graph.add_edge(3, 4, 6)
						graph.add_edge(4, 1, 3)
						graph.add_edge(4, 2, 4)
						graph.add_edge(4, 3, 9)
						graph.floyd_warshall()
						graph.show_min(1, 4)
						graph.show_min(0, 3)






