





"""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_			=      """."""

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







def 		__lowercase					(       snake_case_  :  str    ,snake_case_  :  Optional[int]    ,snake_case_  :  Tuple						)       ->Dict:



    '''simple docstring'''







    __A   :						int									=					SavedModel()
    __A   :						List[Any]									=					[]

    with open(os.path.join(snake_case_    ,'''utils'''    ,'''tf_ops'''    ,'''onnx.json'''						)						) as f:
        __A   :						Tuple									=					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()						)

    __A   :						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
    __A   :						Optional[Any]									=					sorted(snake_case_						)
    __A   :						str									=					[]

    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__":
 a_			=      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_			=      parser.parse_args()

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











"""simple docstring"""



from decimal import Decimal, getcontext
from math import ceil, factorial







def 		__lowercase					(       snake_case_  :  int						)       ->str:



    '''simple docstring'''







    if not isinstance(snake_case_    ,snake_case_						):
        raise TypeError('''Undefined for non-integers'''						)
    elif precision < 1:
        raise ValueError('''Undefined for non-natural numbers'''						)

    __A   :						int									=					precision
    __A   :						Tuple									=					ceil(precision / 14						)
    __A   :						Dict									=					426880 * Decimal(10005						).sqrt()
    __A   :						Optional[Any]									=					1
    __A   :						int									=					13591409
    __A   :						Optional[int]									=					Decimal(snake_case_						)
    for k in range(1    ,snake_case_						):
        __A   :						int									=					factorial(6 * k						) // (factorial(3 * k						) * factorial(snake_case_						) ** 3)
        linear_term += 545140134
        exponential_term *= -262537412640768000
        partial_sum += Decimal(multinomial_term * linear_term						) / exponential_term
    return str(constant_term / partial_sum						)[:-1]


if __name__ == "__main__":
       a_			=      50
       print(f'''The first {n} digits of pi is: {pi(n)}''')




