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65 行
3.7 KiB
65 行
3.7 KiB
# @generated by generate_proto_mypy_stubs.py. Do not edit!
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import sys
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from google.protobuf.internal.containers import (
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RepeatedScalarFieldContainer as google___protobuf___internal___containers___RepeatedScalarFieldContainer,
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)
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from google.protobuf.message import (
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Message as google___protobuf___message___Message,
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)
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from mlagents.envs.communicator_objects.custom_observation_pb2 import (
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CustomObservation as mlagents___envs___communicator_objects___custom_observation_pb2___CustomObservation,
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)
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from typing import (
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Iterable as typing___Iterable,
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Optional as typing___Optional,
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Text as typing___Text,
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)
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from typing_extensions import (
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Literal as typing_extensions___Literal,
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)
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class AgentInfoProto(google___protobuf___message___Message):
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stacked_vector_observation = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[float]
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visual_observations = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[bytes]
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text_observation = ... # type: typing___Text
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stored_vector_actions = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[float]
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stored_text_actions = ... # type: typing___Text
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memories = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[float]
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reward = ... # type: float
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done = ... # type: bool
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max_step_reached = ... # type: bool
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id = ... # type: int
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action_mask = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[bool]
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@property
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def custom_observation(self) -> mlagents___envs___communicator_objects___custom_observation_pb2___CustomObservation: ...
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def __init__(self,
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stacked_vector_observation : typing___Optional[typing___Iterable[float]] = None,
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visual_observations : typing___Optional[typing___Iterable[bytes]] = None,
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text_observation : typing___Optional[typing___Text] = None,
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stored_vector_actions : typing___Optional[typing___Iterable[float]] = None,
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stored_text_actions : typing___Optional[typing___Text] = None,
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memories : typing___Optional[typing___Iterable[float]] = None,
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reward : typing___Optional[float] = None,
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done : typing___Optional[bool] = None,
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max_step_reached : typing___Optional[bool] = None,
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id : typing___Optional[int] = None,
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action_mask : typing___Optional[typing___Iterable[bool]] = None,
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custom_observation : typing___Optional[mlagents___envs___communicator_objects___custom_observation_pb2___CustomObservation] = None,
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) -> None: ...
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@classmethod
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def FromString(cls, s: bytes) -> AgentInfoProto: ...
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def MergeFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
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def CopyFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
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if sys.version_info >= (3,):
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def HasField(self, field_name: typing_extensions___Literal[u"custom_observation"]) -> bool: ...
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def ClearField(self, field_name: typing_extensions___Literal[u"action_mask",u"custom_observation",u"done",u"id",u"max_step_reached",u"memories",u"reward",u"stacked_vector_observation",u"stored_text_actions",u"stored_vector_actions",u"text_observation",u"visual_observations"]) -> None: ...
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else:
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def HasField(self, field_name: typing_extensions___Literal[u"custom_observation",b"custom_observation"]) -> bool: ...
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def ClearField(self, field_name: typing_extensions___Literal[b"action_mask",b"custom_observation",b"done",b"id",b"max_step_reached",b"memories",b"reward",b"stacked_vector_observation",b"stored_text_actions",b"stored_vector_actions",b"text_observation",b"visual_observations"]) -> None: ...
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