# @generated by protoc-gen-mypy.py. Do not edit! # mypy: disable-error-code=override from google.protobuf.message import ( # type: ignore Message, ) from typing import ( Iterable, List, Optional as OptionalType, Tuple, cast, ) from google.protobuf.internal.containers import ( # type: ignore RepeatedCompositeFieldContainer, RepeatedScalarFieldContainer, ) from onnx.onnx_ml_pb2 import ( SparseTensorProto, TensorProto, ) class SequenceProto(Message): class DataType(int): @classmethod def Name(cls, number: int) -> str: ... @classmethod def Value(cls, name: str) -> int: ... @classmethod def keys(cls) -> List[str]: ... @classmethod def values(cls) -> List[int]: ... @classmethod def items(cls) -> List[Tuple[str, int]]: ... UNDEFINED = cast(DataType, 0) TENSOR = cast(DataType, 1) SPARSE_TENSOR = cast(DataType, 2) SEQUENCE = cast(DataType, 3) MAP = cast(DataType, 4) OPTIONAL = cast(DataType, 5) name = ... # type: str elem_type = ... # type: int @property def tensor_values(self) -> RepeatedCompositeFieldContainer[TensorProto]: ... @property def sparse_tensor_values(self) -> RepeatedCompositeFieldContainer[SparseTensorProto]: ... @property def sequence_values(self) -> RepeatedCompositeFieldContainer[SequenceProto]: ... @property def map_values(self) -> RepeatedCompositeFieldContainer[MapProto]: ... @property def optional_values(self) -> RepeatedCompositeFieldContainer[OptionalProto]: ... def __init__(self, name : OptionalType[str] = None, elem_type : OptionalType[int] = None, tensor_values : OptionalType[Iterable[TensorProto]] = None, sparse_tensor_values : OptionalType[Iterable[SparseTensorProto]] = None, sequence_values : OptionalType[Iterable[SequenceProto]] = None, map_values : OptionalType[Iterable[MapProto]] = None, optional_values : OptionalType[Iterable[OptionalProto]] = None, ) -> None: ... @classmethod def FromString(cls, s: bytes) -> SequenceProto: ... def MergeFrom(self, other_msg: Message) -> None: ... def CopyFrom(self, other_msg: Message) -> None: ... class MapProto(Message): name = ... # type: str key_type = ... # type: int keys = ... # type: RepeatedScalarFieldContainer[int] string_keys = ... # type: RepeatedScalarFieldContainer[bytes] @property def values(self) -> SequenceProto: ... def __init__(self, name : OptionalType[str] = None, key_type : OptionalType[int] = None, keys : OptionalType[Iterable[int]] = None, string_keys : OptionalType[Iterable[bytes]] = None, values : OptionalType[SequenceProto] = None, ) -> None: ... @classmethod def FromString(cls, s: bytes) -> MapProto: ... def MergeFrom(self, other_msg: Message) -> None: ... def CopyFrom(self, other_msg: Message) -> None: ... class OptionalProto(Message): class DataType(int): @classmethod def Name(cls, number: int) -> str: ... @classmethod def Value(cls, name: str) -> int: ... @classmethod def keys(cls) -> List[str]: ... @classmethod def values(cls) -> List[int]: ... @classmethod def items(cls) -> List[Tuple[str, int]]: ... UNDEFINED = cast(DataType, 0) TENSOR = cast(DataType, 1) SPARSE_TENSOR = cast(DataType, 2) SEQUENCE = cast(DataType, 3) MAP = cast(DataType, 4) OPTIONAL = cast(DataType, 5) name = ... # type: str elem_type = ... # type: int @property def tensor_value(self) -> TensorProto: ... @property def sparse_tensor_value(self) -> SparseTensorProto: ... @property def sequence_value(self) -> SequenceProto: ... @property def map_value(self) -> MapProto: ... @property def optional_value(self) -> OptionalProto: ... def __init__(self, name : OptionalType[str] = None, elem_type : OptionalType[int] = None, tensor_value : OptionalType[TensorProto] = None, sparse_tensor_value : OptionalType[SparseTensorProto] = None, sequence_value : OptionalType[SequenceProto] = None, map_value : OptionalType[MapProto] = None, optional_value : OptionalType[OptionalProto] = None, ) -> None: ... @classmethod def FromString(cls, s: bytes) -> OptionalProto: ... def MergeFrom(self, other_msg: Message) -> None: ... def CopyFrom(self, other_msg: Message) -> None: ...