






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							:   int							=  "."

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





def 					lowercase_ (    __snake_case     :							str	,	__snake_case     :							Union[str, Any]	,	__snake_case     :							Tuple      )     -> Union[str, Any]:





				'''simple docstring'''


				snake_case__      :Any         =   SavedModel()
				snake_case__      :str         =   []

				with open(os.path.join(a__	,	"utils"	,	"tf_ops"	,	"onnx.json"      )      ) as f:
								snake_case__      :Dict         =   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()      )

				snake_case__      :List[str]         =   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
				snake_case__      :Tuple         =   sorted(a__      )
				snake_case__      :Union[str, Any]         =   []

				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							:   Optional[Any]							=  argparse.ArgumentParser()
							parser.add_argument("--saved_model_path", help="Path of the saved model to check (the .pb file).")
							parser.add_argument(
							    "--opset", default=1_2, 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							:   str							=  parser.parse_args()

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







from __future__ import annotations


class 					_snake_case						:






	def __init__(		self					,UpperCamelCase       )						->    None:
					snake_case__      :Union[str, Any]         =   data
					snake_case__      :Node | None         =   None
					snake_case__      :Node | None         =   None





def 					lowercase_ (    __snake_case     :							Node | None      )     -> None:  # In Order traversal of the tree





				'''simple docstring'''


				if tree:
								display(tree.left      )
								print(tree.data      )
								display(tree.right      )





def 					lowercase_ (    __snake_case     :							Node | None      )     -> int:





				'''simple docstring'''


				return 1 + max(depth_of_tree(tree.left      )	,	depth_of_tree(tree.right      )      ) if tree else 0





def 					lowercase_ (    __snake_case     :							Node      )     -> bool:





				'''simple docstring'''


				if not tree:
								return True
				if tree.left and tree.right:
								return is_full_binary_tree(tree.left      ) and is_full_binary_tree(tree.right      )
				else:
								return not tree.left and not tree.right





def 					lowercase_ (    )     -> None:  # Main function for testing.





				'''simple docstring'''


				snake_case__      :Dict         =   Node(1      )
				snake_case__      :int         =   Node(2      )
				snake_case__      :Optional[Any]         =   Node(3      )
				snake_case__      :Tuple         =   Node(4      )
				snake_case__      :str         =   Node(5      )
				snake_case__      :Optional[Any]         =   Node(6      )
				snake_case__      :List[Any]         =   Node(7      )
				snake_case__      :List[str]         =   Node(8      )
				snake_case__      :Tuple         =   Node(9      )

				print(is_full_binary_tree(__snake_case      )      )
				print(depth_of_tree(__snake_case      )      )
				print("Tree is: "      )
				display(__snake_case      )


if __name__ == "__main__":
	main()