
"""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
a		:       Any     						=       '.'

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



def     __magic_name__		(					UpperCamelCase     :		int							,		UpperCamelCase     :		List[str]							,		UpperCamelCase     :		str     )     ->						Union[str, Any]:
    a__		=			SavedModel()
    a__		=			[]

    with open(os.path.join(UpperCamelCase							,		'utils'							,		'tf_ops'							,		'onnx.json'     )     ) as f:
        a__		=			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()     )

    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(UpperCamelCase     )
    a__		=			[]

    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__":
    a		:       Dict     						=       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)'
    )
    a		:       str     						=       parser.parse_args()

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








'''simple docstring'''


def 						lowerCamelCase__   (				a							):
						__snake_case						 =   [0] * len(a							)
						__snake_case						 =   []
						__snake_case						 =   []
						__snake_case						 =   0

						for values in graph.values():
												for i in values:
																		indegree[i] += 1

						for i in range(len(a							)							):
												if indegree[i] == 0:
																		queue.append(a							)

						while queue:
												__snake_case						 =   queue.pop(0							)
												cnt += 1
												topo.append(a							)
												for x in graph[vertex]:
																		indegree[x] -= 1
																		if indegree[x] == 0:
																								queue.append(a							)

						if cnt != len(a							):
												print('Cycle exists'							)
						else:
												print(a							)


# Adjacency List of Graph
_lowercase  =			{0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}






topological_sort(graph)

