为什么 rasa nlu 不识别安装了 tensorflow?
Why doesn't the rasa nlu recognize that tensorflow is installed?
我正在使用带 supervised_embedding 管道的 rasa nlu,我正在尝试训练我的模型。在我的本地机器上,我可以毫无问题地训练。当我尝试在我的服务器上训练模型时,出现以下错误:
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File ".\nlp\train_nlp_model.py", line 83, in <module>
train_models(intents, number_of_threads, True)
File ".\nlp\train_nlp_model.py", line 61, in train_models
p.starmap(train_model, [(m, archive_existing) for m in model_types])
File "D:\Python\Python36\lib\multiprocessing\pool.py", line 274, in starmap
return self._map_async(func, iterable, starmapstar, chunksize).get()
File "D:\Python\Python36\lib\multiprocessing\pool.py", line 644, in get
raise self._value
Exception: Not all required packages are installed. To use this pipeline, you need to install the missing dependencies. Please install tensorflow
但是,如果我执行 pip freeze,它表明确实安装了 tensorflow:
absl-py==0.9.0
astor==0.8.1
astroid==2.2.5
atomicwrites==1.3.0
attrs==19.1.0
Automat==0.7.0
bleach==1.5.0
boto3==1.9.196
botocore==1.12.196
cachetools==3.1.1
certifi==2019.6.16
cffi==1.13.2
characteristic==14.3.0
chardet==3.0.4
Click==7.0
cloudpickle==0.6.1
colorama==0.4.1
coloredlogs==10.0
constantly==15.1.0
cx-Oracle==6.3.1
cycler==0.10.0
cymem==1.31.2
cytoolz==0.9.0.1
dill==0.2.9
docutils==0.14
en-core-web-sm==2.0.0
et-xmlfile==1.0.1
Flask==1.0.2
future==0.17.1
fuzzywuzzy==0.16.0
gast==0.3.3
gevent==1.4.0
greenlet==0.4.15
grpcio==1.27.2
html5lib==0.9999999
humanfriendly==4.18
hyperlink==19.0.0
idna==2.8
importlib-metadata==0.23
incremental==17.5.0
isort==4.3.21
itsdangerous==1.1.0
jdcal==1.4.1
Jinja2==2.10.1
jmespath==0.9.4
joblib==0.13.2
jsonschema==2.6.0
kiwisolver==1.1.0
klein==17.10.0
lazy-object-proxy==1.4.1
Markdown==3.2.1
MarkupSafe==1.1.1
matplotlib==3.1.1
mccabe==0.6.1
more-itertools==7.2.0
msgpack==0.6.1
msgpack-numpy==0.4.3.2
murmurhash==0.28.0
numpy==1.16.4+mkl
openpyxl==2.6.2
packaging==18.0
pandas==0.25.3
pathlib==1.0.1
plac==0.9.6
pluggy==0.13.0
preshed==1.0.1
protobuf==3.11.3
py==1.8.0
pycparser==2.19
PyHamcrest==1.9.0
pylint==2.3.1
pyodbc==4.0.23
pyparsing==2.4.1.1
pyreadline==2.1
pyrsistent==0.15.3
pytest==5.2.1
python-crfsuite==0.9.6
python-dateutil==2.8.0
python-Levenshtein==0.12.0
pytz==2019.1
pywin32==223
PyYAML==5.1.1
rasa-nlu==0.15.1
regex==2017.4.5
requests==2.22.0
rope==0.14.0
ruamel.yaml==0.15.100
s3transfer==0.2.1
scikit-learn==0.20.3
scipy==1.1.0
simplejson==3.16.0
six==1.12.0
sklearn==0.0
sklearn-crfsuite==0.3.6
spacy==2.0.11
tabulate==0.8.3
tensorboard==1.7.0
tensorflow==1.7.0
termcolor==1.1.0
thinc==6.10.3
toolz==0.10.0
tqdm==4.32.2
Tubes==0.2.0
Twisted==19.10.0
typed-ast==1.4.0
typing==3.7.4
ujson==1.35
urllib3==1.25.3
wcwidth==0.1.7
Werkzeug==0.15.5
word2number==1.1
wrapt==1.10.11
zipp==0.6.0
zope.interface==4.6.0
为什么 tensorflow 没有被识别?
我试过 pip install rasa-nlu[tensorflow]
,但问题仍然存在。
看起来它不能在服务器上运行的原因是因为它上面的 CPU 没有 AVX 指令集。我已经设法在另一台具有 AVX 指令集的服务器上对其进行训练。
我正在使用带 supervised_embedding 管道的 rasa nlu,我正在尝试训练我的模型。在我的本地机器上,我可以毫无问题地训练。当我尝试在我的服务器上训练模型时,出现以下错误:
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File ".\nlp\train_nlp_model.py", line 83, in <module>
train_models(intents, number_of_threads, True)
File ".\nlp\train_nlp_model.py", line 61, in train_models
p.starmap(train_model, [(m, archive_existing) for m in model_types])
File "D:\Python\Python36\lib\multiprocessing\pool.py", line 274, in starmap
return self._map_async(func, iterable, starmapstar, chunksize).get()
File "D:\Python\Python36\lib\multiprocessing\pool.py", line 644, in get
raise self._value
Exception: Not all required packages are installed. To use this pipeline, you need to install the missing dependencies. Please install tensorflow
但是,如果我执行 pip freeze,它表明确实安装了 tensorflow:
absl-py==0.9.0
astor==0.8.1
astroid==2.2.5
atomicwrites==1.3.0
attrs==19.1.0
Automat==0.7.0
bleach==1.5.0
boto3==1.9.196
botocore==1.12.196
cachetools==3.1.1
certifi==2019.6.16
cffi==1.13.2
characteristic==14.3.0
chardet==3.0.4
Click==7.0
cloudpickle==0.6.1
colorama==0.4.1
coloredlogs==10.0
constantly==15.1.0
cx-Oracle==6.3.1
cycler==0.10.0
cymem==1.31.2
cytoolz==0.9.0.1
dill==0.2.9
docutils==0.14
en-core-web-sm==2.0.0
et-xmlfile==1.0.1
Flask==1.0.2
future==0.17.1
fuzzywuzzy==0.16.0
gast==0.3.3
gevent==1.4.0
greenlet==0.4.15
grpcio==1.27.2
html5lib==0.9999999
humanfriendly==4.18
hyperlink==19.0.0
idna==2.8
importlib-metadata==0.23
incremental==17.5.0
isort==4.3.21
itsdangerous==1.1.0
jdcal==1.4.1
Jinja2==2.10.1
jmespath==0.9.4
joblib==0.13.2
jsonschema==2.6.0
kiwisolver==1.1.0
klein==17.10.0
lazy-object-proxy==1.4.1
Markdown==3.2.1
MarkupSafe==1.1.1
matplotlib==3.1.1
mccabe==0.6.1
more-itertools==7.2.0
msgpack==0.6.1
msgpack-numpy==0.4.3.2
murmurhash==0.28.0
numpy==1.16.4+mkl
openpyxl==2.6.2
packaging==18.0
pandas==0.25.3
pathlib==1.0.1
plac==0.9.6
pluggy==0.13.0
preshed==1.0.1
protobuf==3.11.3
py==1.8.0
pycparser==2.19
PyHamcrest==1.9.0
pylint==2.3.1
pyodbc==4.0.23
pyparsing==2.4.1.1
pyreadline==2.1
pyrsistent==0.15.3
pytest==5.2.1
python-crfsuite==0.9.6
python-dateutil==2.8.0
python-Levenshtein==0.12.0
pytz==2019.1
pywin32==223
PyYAML==5.1.1
rasa-nlu==0.15.1
regex==2017.4.5
requests==2.22.0
rope==0.14.0
ruamel.yaml==0.15.100
s3transfer==0.2.1
scikit-learn==0.20.3
scipy==1.1.0
simplejson==3.16.0
six==1.12.0
sklearn==0.0
sklearn-crfsuite==0.3.6
spacy==2.0.11
tabulate==0.8.3
tensorboard==1.7.0
tensorflow==1.7.0
termcolor==1.1.0
thinc==6.10.3
toolz==0.10.0
tqdm==4.32.2
Tubes==0.2.0
Twisted==19.10.0
typed-ast==1.4.0
typing==3.7.4
ujson==1.35
urllib3==1.25.3
wcwidth==0.1.7
Werkzeug==0.15.5
word2number==1.1
wrapt==1.10.11
zipp==0.6.0
zope.interface==4.6.0
为什么 tensorflow 没有被识别?
我试过 pip install rasa-nlu[tensorflow]
,但问题仍然存在。
看起来它不能在服务器上运行的原因是因为它上面的 CPU 没有 AVX 指令集。我已经设法在另一台具有 AVX 指令集的服务器上对其进行训练。