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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# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: mlagents/envs/communicator_objects/custom_action.proto
import sys
_b = sys.version_info[0] < 3 and (lambda x: x) or (lambda x: x.encode("latin1"))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name="mlagents/envs/communicator_objects/custom_action.proto",
package="communicator_objects",
syntax="proto3",
serialized_options=_b("\252\002\034MLAgents.CommunicatorObjects"),
serialized_pb=_b(
'\n6mlagents/envs/communicator_objects/custom_action.proto\x12\x14\x63ommunicator_objects"\x0e\n\x0c\x43ustomActionB\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3'
),
)
_CUSTOMACTION = _descriptor.Descriptor(
name="CustomAction",
full_name="communicator_objects.CustomAction",
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=None,
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=80,
serialized_end=94,
)
DESCRIPTOR.message_types_by_name["CustomAction"] = _CUSTOMACTION
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
CustomAction = _reflection.GeneratedProtocolMessageType(
"CustomAction",
(_message.Message,),
dict(
DESCRIPTOR=_CUSTOMACTION,
__module__="mlagents.envs.communicator_objects.custom_action_pb2"
# @@protoc_insertion_point(class_scope:communicator_objects.CustomAction)
),
)
_sym_db.RegisterMessage(CustomAction)
DESCRIPTOR._options = None
# @@protoc_insertion_point(module_scope)