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 the protocol buffer compiler. DO NOT EDIT!
# source: mlagents_envs/communicator_objects/command.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf.internal import enum_type_wrapper
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
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name='mlagents_envs/communicator_objects/command.proto',
package='communicator_objects',
syntax='proto3',
serialized_pb=_b('\n0mlagents_envs/communicator_objects/command.proto\x12\x14\x63ommunicator_objects*-\n\x0c\x43ommandProto\x12\x08\n\x04STEP\x10\x00\x12\t\n\x05RESET\x10\x01\x12\x08\n\x04QUIT\x10\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
)
_COMMANDPROTO = _descriptor.EnumDescriptor(
name='CommandProto',
full_name='communicator_objects.CommandProto',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='STEP', index=0, number=0,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='RESET', index=1, number=1,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='QUIT', index=2, number=2,
options=None,
type=None),
],
containing_type=None,
options=None,
serialized_start=74,
serialized_end=119,
)
_sym_db.RegisterEnumDescriptor(_COMMANDPROTO)
CommandProto = enum_type_wrapper.EnumTypeWrapper(_COMMANDPROTO)
STEP = 0
RESET = 1
QUIT = 2
DESCRIPTOR.enum_types_by_name['CommandProto'] = _COMMANDPROTO
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
DESCRIPTOR.has_options = True
DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\252\002\034MLAgents.CommunicatorObjects'))
# @@protoc_insertion_point(module_scope)