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 (
RepeatedScalarFieldContainer as google___protobuf___internal___containers___RepeatedScalarFieldContainer,
)
from google.protobuf.message import (
Message as google___protobuf___message___Message,
)
from mlagents_envs.communicator_objects.space_type_pb2 import (
SpaceTypeProto as mlagents_envs___communicator_objects___space_type_pb2___SpaceTypeProto,
)
from typing import (
Iterable as typing___Iterable,
Optional as typing___Optional,
Text as typing___Text,
)
from typing_extensions import (
Literal as typing_extensions___Literal,
)
builtin___bool = bool
builtin___bytes = bytes
builtin___float = float
builtin___int = int
class ActionSpecProto(google___protobuf___message___Message):
DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
num_continuous_actions = ... # type: builtin___int
num_discrete_actions = ... # type: builtin___int
discrete_branch_sizes = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___int]
action_descriptions = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[typing___Text]
def __init__(self,
*,
num_continuous_actions : typing___Optional[builtin___int] = None,
num_discrete_actions : typing___Optional[builtin___int] = None,
discrete_branch_sizes : typing___Optional[typing___Iterable[builtin___int]] = None,
action_descriptions : typing___Optional[typing___Iterable[typing___Text]] = None,
) -> None: ...
@classmethod
def FromString(cls, s: builtin___bytes) -> ActionSpecProto: ...
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_descriptions",u"discrete_branch_sizes",u"num_continuous_actions",u"num_discrete_actions"]) -> None: ...
else:
def ClearField(self, field_name: typing_extensions___Literal[u"action_descriptions",b"action_descriptions",u"discrete_branch_sizes",b"discrete_branch_sizes",u"num_continuous_actions",b"num_continuous_actions",u"num_discrete_actions",b"num_discrete_actions"]) -> None: ...
class BrainParametersProto(google___protobuf___message___Message):
DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
vector_action_size_deprecated = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[builtin___int]
vector_action_descriptions_deprecated = ... # type: google___protobuf___internal___containers___RepeatedScalarFieldContainer[typing___Text]
vector_action_space_type_deprecated = ... # type: mlagents_envs___communicator_objects___space_type_pb2___SpaceTypeProto
brain_name = ... # type: typing___Text
is_training = ... # type: builtin___bool
@property
def action_spec(self) -> ActionSpecProto: ...
def __init__(self,
*,
vector_action_size_deprecated : typing___Optional[typing___Iterable[builtin___int]] = None,
vector_action_descriptions_deprecated : typing___Optional[typing___Iterable[typing___Text]] = None,
vector_action_space_type_deprecated : typing___Optional[mlagents_envs___communicator_objects___space_type_pb2___SpaceTypeProto] = None,
brain_name : typing___Optional[typing___Text] = None,
is_training : typing___Optional[builtin___bool] = None,
action_spec : typing___Optional[ActionSpecProto] = None,
) -> None: ...
@classmethod
def FromString(cls, s: builtin___bytes) -> BrainParametersProto: ...
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 HasField(self, field_name: typing_extensions___Literal[u"action_spec"]) -> builtin___bool: ...
def ClearField(self, field_name: typing_extensions___Literal[u"action_spec",u"brain_name",u"is_training",u"vector_action_descriptions_deprecated",u"vector_action_size_deprecated",u"vector_action_space_type_deprecated"]) -> None: ...
else:
def HasField(self, field_name: typing_extensions___Literal[u"action_spec",b"action_spec"]) -> builtin___bool: ...
def ClearField(self, field_name: typing_extensions___Literal[u"action_spec",b"action_spec",u"brain_name",b"brain_name",u"is_training",b"is_training",u"vector_action_descriptions_deprecated",b"vector_action_descriptions_deprecated",u"vector_action_size_deprecated",b"vector_action_size_deprecated",u"vector_action_space_type_deprecated",b"vector_action_space_type_deprecated"]) -> None: ...