[新手教學] 執行 unity 3D ml-agents 深度學習可能會遇到的錯誤 your generated code is out of date and must be regenerated with protoc >= 3.19.0

剛剛執行unity3D 的 mlagents-learn 遇到一個錯誤

(py9ML) D:\MYWORK\unityProjects\unity3d_ml_test\ml-agents-envs>mlagents-learn
Traceback (most recent call last):
File "C:\Python39\py9ML\Scripts\mlagents-learn-script.py", line 33, in <module>
sys.exit(load_entry_point('mlagents', 'console_scripts', 'mlagents-learn')())
File "C:\Python39\py9ML\Scripts\mlagents-learn-script.py", line 25, in importlib_load_entry_point
return next(matches).load()
File "C:\Python39\lib\importlib\metadata.py", line 77, in load
module = import_module(match.group('module'))
File "C:\Python39\lib\importlib\__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1030, in _gcd_import
File "<frozen importlib._bootstrap>", line 1007, in _find_and_load
File "<frozen importlib._bootstrap>", line 986, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 680, in _load_unlocked
File "<frozen importlib._bootstrap_external>", line 790, in exec_module
File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents\mlagents\trainers\learn.py", line 2, in <module>
from mlagents import torch_utils
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents\mlagents\torch_utils\__init__.py", line 1, in <module>
from mlagents.torch_utils.torch import torch as torch # noqa
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents\mlagents\torch_utils\torch.py", line 6, in <module>
from mlagents.trainers.settings import TorchSettings
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents\mlagents\trainers\settings.py", line 25, in <module>
from mlagents.trainers.cli_utils import StoreConfigFile, DetectDefault, parser
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents\mlagents\trainers\cli_utils.py", line 5, in <module>
from mlagents_envs.environment import UnityEnvironment
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents-envs\mlagents_envs\environment.py", line 12, in <module>
from mlagents_envs.side_channel.side_channel import SideChannel
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents-envs\mlagents_envs\side_channel\__init__.py", line 5, in <module>
from mlagents_envs.side_channel.default_training_analytics_side_channel import ( # noqa
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents-envs\mlagents_envs\side_channel\default_training_analytics_side_channel.py", line 7, in <module>
from mlagents_envs.communicator_objects.training_analytics_pb2 import (
File "d:\mywork\unityprojects\unity3d_ml_test\ml-agents-envs\mlagents_envs\communicator_objects\training_analytics_pb2.py", line 35, in <module>
_descriptor.FieldDescriptor(
File "c:\python39\py9ml\lib\site-packages\google\protobuf\descriptor.py", line 561, in __new__
_message.Message._CheckCalledFromGeneratedFile()
TypeError: Descriptors cannot not be created directly.
If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0.
If you cannot immediately regenerate your protos, some other possible workarounds are:
1. Downgrade the protobuf package to 3.20.x or lower.
2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates

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