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.message import (
Message as google___protobuf___message___Message,
)
from typing import (
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 TrainingEnvironmentInitialized(google___protobuf___message___Message):
DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
mlagents_version = ... # type: typing___Text
mlagents_envs_version = ... # type: typing___Text
python_version = ... # type: typing___Text
torch_version = ... # type: typing___Text
torch_device_type = ... # type: typing___Text
num_envs = ... # type: builtin___int
num_environment_parameters = ... # type: builtin___int
def __init__(self,
*,
mlagents_version : typing___Optional[typing___Text] = None,
mlagents_envs_version : typing___Optional[typing___Text] = None,
python_version : typing___Optional[typing___Text] = None,
torch_version : typing___Optional[typing___Text] = None,
torch_device_type : typing___Optional[typing___Text] = None,
num_envs : typing___Optional[builtin___int] = None,
num_environment_parameters : typing___Optional[builtin___int] = None,
) -> None: ...
@classmethod
def FromString(cls, s: builtin___bytes) -> TrainingEnvironmentInitialized: ...
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"mlagents_envs_version",u"mlagents_version",u"num_environment_parameters",u"num_envs",u"python_version",u"torch_device_type",u"torch_version"]) -> None: ...
else:
def ClearField(self, field_name: typing_extensions___Literal[u"mlagents_envs_version",b"mlagents_envs_version",u"mlagents_version",b"mlagents_version",u"num_environment_parameters",b"num_environment_parameters",u"num_envs",b"num_envs",u"python_version",b"python_version",u"torch_device_type",b"torch_device_type",u"torch_version",b"torch_version"]) -> None: ...
class TrainingBehaviorInitialized(google___protobuf___message___Message):
DESCRIPTOR: google___protobuf___descriptor___Descriptor = ...
behavior_name = ... # type: typing___Text
trainer_type = ... # type: typing___Text
extrinsic_reward_enabled = ... # type: builtin___bool
gail_reward_enabled = ... # type: builtin___bool
curiosity_reward_enabled = ... # type: builtin___bool
rnd_reward_enabled = ... # type: builtin___bool
behavioral_cloning_enabled = ... # type: builtin___bool
recurrent_enabled = ... # type: builtin___bool
visual_encoder = ... # type: typing___Text
num_network_layers = ... # type: builtin___int
num_network_hidden_units = ... # type: builtin___int
trainer_threaded = ... # type: builtin___bool
self_play_enabled = ... # type: builtin___bool
curriculum_enabled = ... # type: builtin___bool
def __init__(self,
*,
behavior_name : typing___Optional[typing___Text] = None,
trainer_type : typing___Optional[typing___Text] = None,
extrinsic_reward_enabled : typing___Optional[builtin___bool] = None,
gail_reward_enabled : typing___Optional[builtin___bool] = None,
curiosity_reward_enabled : typing___Optional[builtin___bool] = None,
rnd_reward_enabled : typing___Optional[builtin___bool] = None,
behavioral_cloning_enabled : typing___Optional[builtin___bool] = None,
recurrent_enabled : typing___Optional[builtin___bool] = None,
visual_encoder : typing___Optional[typing___Text] = None,
num_network_layers : typing___Optional[builtin___int] = None,
num_network_hidden_units : typing___Optional[builtin___int] = None,
trainer_threaded : typing___Optional[builtin___bool] = None,
self_play_enabled : typing___Optional[builtin___bool] = None,
curriculum_enabled : typing___Optional[builtin___bool] = None,
) -> None: ...
@classmethod
def FromString(cls, s: builtin___bytes) -> TrainingBehaviorInitialized: ...
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"behavior_name",u"behavioral_cloning_enabled",u"curiosity_reward_enabled",u"curriculum_enabled",u"extrinsic_reward_enabled",u"gail_reward_enabled",u"num_network_hidden_units",u"num_network_layers",u"recurrent_enabled",u"rnd_reward_enabled",u"self_play_enabled",u"trainer_threaded",u"trainer_type",u"visual_encoder"]) -> None: ...
else:
def ClearField(self, field_name: typing_extensions___Literal[u"behavior_name",b"behavior_name",u"behavioral_cloning_enabled",b"behavioral_cloning_enabled",u"curiosity_reward_enabled",b"curiosity_reward_enabled",u"curriculum_enabled",b"curriculum_enabled",u"extrinsic_reward_enabled",b"extrinsic_reward_enabled",u"gail_reward_enabled",b"gail_reward_enabled",u"num_network_hidden_units",b"num_network_hidden_units",u"num_network_layers",b"num_network_layers",u"recurrent_enabled",b"recurrent_enabled",u"rnd_reward_enabled",b"rnd_reward_enabled",u"self_play_enabled",b"self_play_enabled",u"trainer_threaded",b"trainer_threaded",u"trainer_type",b"trainer_type",u"visual_encoder",b"visual_encoder"]) -> None: ...