(rasa) unitree@ubuntu:~/rasa_ws$ rasa run --enable-api
/home/unitree/rasa/lib/python3.8/site-packages/rasa/core/tracker_store.py:1044: MovedIn20Warning: Deprecated API features detected! These feature(s) are not compatible with SQLAlchemy 2.0. To prevent incompatible upgrades prior to updating applications, ensure requirements files are pinned to "sqlalchemy<2.0". Set environment variable SQLALCHEMY_WARN_20=1 to show all deprecation warnings. Set environment variable SQLALCHEMY_SILENCE_UBER_WARNING=1 to silence this message. (Background on SQLAlchemy 2.0 at: https://sqlalche.me/e/b8d9)
Base: DeclarativeMeta = declarative_base()
/home/unitree/rasa/lib/python3.8/site-packages/rasa/shared/utils/validation.py:134: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
import pkg_resources
/home/unitree/rasa/lib/python3.8/site-packages/pkg_resources/__init__.py:3117: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('mpl_toolkits')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
/home/unitree/rasa/lib/python3.8/site-packages/pkg_resources/__init__.py:3117: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('ruamel')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
/home/unitree/rasa/lib/python3.8/site-packages/sanic_cors/extension.py:39: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead.
SANIC_VERSION = LooseVersion(sanic_version)
Traceback (most recent call last):
File "/home/unitree/rasa/lib/python3.8/site-packages/sklearn/__check_build/__init__.py", line 48, in <module>
from ._check_build import check_build # noqa
ImportError: /home/unitree/rasa/lib/python3.8/site-packages/sklearn/__check_build/../../scikit_learn.libs/libgomp-d22c30c5.so.1.0.0: cannot allocate memory in static TLS block
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/unitree/rasa/bin/rasa", line 8, in <module>
sys.exit(main())
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/__main__.py", line 133, in main
cmdline_arguments.func(cmdline_arguments)
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/cli/run.py", line 93, in run
rasa.run(**vars(args))
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/api.py", line 36, in run
import rasa.core.run
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/core/run.py", line 25, in <module>
from rasa import server, telemetry
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/server.py", line 59, in <module>
from rasa.core.agent import Agent
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/core/agent.py", line 22, in <module>
from rasa.core.policies.policy import PolicyPrediction
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/core/policies/policy.py", line 26, in <module>
from rasa.core.featurizers.tracker_featurizers import TrackerFeaturizer
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/core/featurizers/tracker_featurizers.py", line 31, in <module>
from rasa.core.featurizers.single_state_featurizer import SingleStateFeaturizer
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/core/featurizers/single_state_featurizer.py", line 8, in <module>
from rasa.nlu.extractors.extractor import EntityTagSpec
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/nlu/extractors/extractor.py", line 30, in <module>
import rasa.utils.train_utils
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/utils/train_utils.py", line 32, in <module>
from rasa.utils.tensorflow.data_generator import RasaBatchDataGenerator
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/utils/tensorflow/data_generator.py", line 10, in <module>
from rasa.utils.tensorflow.model_data import RasaModelData, Data, FeatureArray
File "/home/unitree/rasa/lib/python3.8/site-packages/rasa/utils/tensorflow/model_data.py", line 21, in <module>
from sklearn.model_selection import train_test_split
File "/home/unitree/rasa/lib/python3.8/site-packages/sklearn/__init__.py", line 81, in <module>
from . import __check_build # noqa: F401
File "/home/unitree/rasa/lib/python3.8/site-packages/sklearn/__check_build/__init__.py", line 50, in <module>
raise_build_error(e)
File "/home/unitree/rasa/lib/python3.8/site-packages/sklearn/__check_build/__init__.py", line 31, in raise_build_error
raise ImportError(
ImportError: /home/unitree/rasa/lib/python3.8/site-packages/sklearn/__check_build/../../scikit_learn.libs/libgomp-d22c30c5.so.1.0.0: cannot allocate memory in static TLS block
___________________________________________________________________________
Contents of /home/unitree/rasa/lib/python3.8/site-packages/sklearn/__check_build:
__pycache__ setup.py __init__.py
_check_build.cpython-38-aarch64-linux-gnu.so
___________________________________________________________________________
It seems that scikit-learn has not been built correctly.
If you have installed scikit-learn from source, please do not forget
to build the package before using it: run `python setup.py install` or
`make` in the source directory.
If you have used an installer, please check that it is suited for your
Python version, your operating system and your platform.
这是我出现的错误
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