






from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any



@dataclass
class   lowerCamelCase				:







		'''simple docstring'''



		_snake_case   :   int
		_snake_case   :   Node | None							=  None
		_snake_case   :   Node | None							=  None





def 					lowercase__				(					):


					'''simple docstring'''


					UpperCAmelCase_   :				Optional[Any]						=						Node(1  )
					UpperCAmelCase_   :				Any						=						Node(2  )
					UpperCAmelCase_   :				int						=						Node(3  )
					UpperCAmelCase_   :				str						=						Node(4  )
					UpperCAmelCase_   :				List[str]						=						Node(5  )
					return tree




def 					lowercase__				(					__snake_case   :							Node | None  ):


					'''simple docstring'''


					return [root.data, *preorder(root.left  ), *preorder(root.right  )] if root else []




def 					lowercase__				(					__snake_case   :							Node | None  ):


					'''simple docstring'''


					return postorder(root.left  ) + postorder(root.right  ) + [root.data] if root else []




def 					lowercase__				(					__snake_case   :							Node | None  ):


					'''simple docstring'''


					return [*inorder(root.left  ), root.data, *inorder(root.right  )] if root else []




def 					lowercase__				(					__snake_case   :							Node | None  ):


					'''simple docstring'''


					return (max(height(root.left  )					,	height(root.right  )  ) + 1) if root else 0




def 					lowercase__				(					__snake_case   :							Node | None  ):


					'''simple docstring'''


					UpperCAmelCase_   :				list[Any]						=						[]

					if root is None:
										return output

					UpperCAmelCase_   :				Optional[Any]						=						deque([root]  )

					while process_queue:
										UpperCAmelCase_   :				List[Any]						=						process_queue.popleft()
										output.append(node.data  )

										if node.left:
															process_queue.append(node.left  )
										if node.right:
															process_queue.append(node.right  )
					return output




def 					lowercase__				(					__snake_case   :							Node | None					,	__snake_case   :							int  ):


					'''simple docstring'''


					UpperCAmelCase_   :				list[Any]						=						[]

					def populate_output(__snake_case   :							Node | None					,	__snake_case   :							int  ) -> None:
										if not root:
															return
										if level == 1:
															output.append(root.data  )
										elif level > 1:
															populate_output(root.left					,	level - 1  )
															populate_output(root.right					,	level - 1  )

					populate_output(__snake_case					,	__snake_case  )
					return output




def 					lowercase__				(					__snake_case   :							Node | None					,	__snake_case   :							int  ):


					'''simple docstring'''


					UpperCAmelCase_   :				list[Any]						=						[]

					def populate_output(__snake_case   :							Node | None					,	__snake_case   :							int  ) -> None:
										if root is None:
															return
										if level == 1:
															output.append(root.data  )
										elif level > 1:
															populate_output(root.right					,	level - 1  )
															populate_output(root.left					,	level - 1  )

					populate_output(__snake_case					,	__snake_case  )
					return output




def 					lowercase__				(					__snake_case   :							Node | None  ):


					'''simple docstring'''


					if root is None:
										return []

					UpperCAmelCase_   :				list[Sequence[Node | None]]						=						[]

					UpperCAmelCase_   :				List[Any]						=						0
					UpperCAmelCase_   :				int						=						height(__snake_case  )

					for h in range(1					,	height_tree + 1  ):
										if not flag:
															output.append(get_nodes_from_left_to_right(__snake_case					,	__snake_case  )  )
															UpperCAmelCase_   :				Dict						=						1
										else:
															output.append(get_nodes_from_right_to_left(__snake_case					,	__snake_case  )  )
															UpperCAmelCase_   :				str						=						0

					return output




def 					lowercase__				(					):  # Main function for testing.


					'''simple docstring'''


					UpperCAmelCase_   :				Optional[int]						=						make_tree()
					print(F"In-order Traversal: {inorder(__snake_case  )}"  )
					print(F"Pre-order Traversal: {preorder(__snake_case  )}"  )
					print(F"Post-order Traversal: {postorder(__snake_case  )}"					,	'\n'  )

					print(F"Height of Tree: {height(__snake_case  )}"					,	'\n'  )

					print('Complete Level Order Traversal: '  )
					print(level_order(__snake_case  )					,	'\n'  )

					print('Level-wise order Traversal: '  )

					for level in range(1					,	height(__snake_case  ) + 1  ):
										print(F"Level {level}:"					,	get_nodes_from_left_to_right(__snake_case					,	level=__snake_case  )  )

					print('\nZigZag order Traversal: '  )
					print(zigzag(__snake_case  )  )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()














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     							=						'.'

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




def 					lowercase__				(					__snake_case   :							Union[str, Any]					,	__snake_case   :							Optional[int]					,	__snake_case   :							Union[str, Any]  ):


					'''simple docstring'''


					UpperCAmelCase_   :				Optional[Any]						=						SavedModel()
					UpperCAmelCase_   :				Optional[Any]						=						[]

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

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

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

					UpperCAmelCase_   :				List[Any]						=						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_   :				Optional[int]						=						sorted(__snake_case  )
					UpperCAmelCase_   :				int						=						[]

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

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


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

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






