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: communicator_objects/agent_action_proto.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='communicator_objects/agent_action_proto.proto',
package='communicator_objects',
syntax='proto3',
serialized_options=_b('\252\002\034MLAgents.CommunicatorObjects'),
serialized_pb=_b('\n-communicator_objects/agent_action_proto.proto\x12\x14\x63ommunicator_objects\"a\n\x10\x41gentActionProto\x12\x16\n\x0evector_actions\x18\x01 \x03(\x02\x12\x14\n\x0ctext_actions\x18\x02 \x01(\t\x12\x10\n\x08memories\x18\x03 \x03(\x02\x12\r\n\x05value\x18\x04 \x01(\x02\x42\x1f\xaa\x02\x1cMLAgents.CommunicatorObjectsb\x06proto3')
)
_AGENTACTIONPROTO = _descriptor.Descriptor(
name='AgentActionProto',
full_name='communicator_objects.AgentActionProto',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='vector_actions', full_name='communicator_objects.AgentActionProto.vector_actions', index=0,
number=1, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='text_actions', full_name='communicator_objects.AgentActionProto.text_actions', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='memories', full_name='communicator_objects.AgentActionProto.memories', index=2,
number=3, type=2, cpp_type=6, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
_descriptor.FieldDescriptor(
name='value', full_name='communicator_objects.AgentActionProto.value', index=3,
number=4, type=2, cpp_type=6, label=1,
has_default_value=False, default_value=float(0),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=71,
serialized_end=168,
)
DESCRIPTOR.message_types_by_name['AgentActionProto'] = _AGENTACTIONPROTO
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
AgentActionProto = _reflection.GeneratedProtocolMessageType('AgentActionProto', (_message.Message,), dict(
DESCRIPTOR = _AGENTACTIONPROTO,
__module__ = 'communicator_objects.agent_action_proto_pb2'
# @@protoc_insertion_point(class_scope:communicator_objects.AgentActionProto)
))
_sym_db.RegisterMessage(AgentActionProto)
DESCRIPTOR._options = None
# @@protoc_insertion_point(module_scope)