Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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# @generated by generate_proto_mypy_stubs.py. Do not edit!
import sys
from google.protobuf.descriptor import (
Descriptor as google___protobuf___descriptor___Descriptor,
)
from google.protobuf.internal.containers import (
RepeatedCompositeFieldContainer as google___protobuf___internal___containers___RepeatedCompositeFieldContainer,
RepeatedScalarFieldContainer as google___protobuf___internal___containers___RepeatedScalarFieldContainer,
)
from google.protobuf.message import (
Message as google___protobuf___message___Message,
)
from mlagents.envs.communicator_objects.observation_pb2 import (
ObservationProto as mlagents___envs___communicator_objects___observation_pb2___ObservationProto,
)
from typing import (
Iterable as typing___Iterable,
Optional as typing___Optional,
)
from typing_extensions import (
Literal as typing_extensions___Literal,
)
builtin___bool = bool
builtin___bytes = bytes
builtin___float = float
builtin___int = int
class AgentInfoProto(google___protobuf___message___Message):
DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
stored_vector_actions = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___float]
reward = ... # type: builtin___float
done = ... # type: builtin___bool
max_step_reached = ... # type: builtin___bool
id = ... # type: builtin___int
action_mask = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___bool]
@property
def observations(self) -> google___protobuf___internal___containers___RepeatedCompositeFieldContainer[mlagents___envs___communicator_objects___observation_pb2___ObservationProto]: ...
def __init__(self,
*,
stored_vector_actions : typing___Optional[typing___Iterable[builtin___float]] = None,
reward : typing___Optional[builtin___float] = None,
done : typing___Optional[builtin___bool] = None,
max_step_reached : typing___Optional[builtin___bool] = None,
id : typing___Optional[builtin___int] = None,
action_mask : typing___Optional[typing___Iterable[builtin___bool]] = None,
observations : typing___Optional[typing___Iterable[mlagents___envs___communicator_objects___observation_pb2___ObservationProto]] = None,
) -> None: ...
@classmethod
def FromString(cls, s: builtin___bytes) -> AgentInfoProto: ...
def MergeFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
def CopyFrom(self, other_msg: google___protobuf___message___Message) -> None: ...
if sys.version_info >= (3,):
def ClearField(self, field_name: typing_extensions___Literal[u"action_mask",u"done",u"id",u"max_step_reached",u"observations",u"reward",u"stored_vector_actions"]) -> None: ...
else:
def ClearField(self, field_name: typing_extensions___Literal[u"action_mask",b"action_mask",u"done",b"done",u"id",b"id",u"max_step_reached",b"max_step_reached",u"observations",b"observations",u"reward",b"reward",u"stored_vector_actions",b"stored_vector_actions"]) -> None: ...