我正在尝试在使用Tensorflow GPU的计算机群集上运行程序。我已经安装了公寓和所有必需的文件，如下所示
# packages in environment at /software/anaconda3:
#
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py36he11e457_0
_mutex_mxnet 0.0.20 gpu_mkl
alabaster 0.7.10 py36h306e16b_0
anaconda custom py36hbbc8b67_0
anaconda-client 1.6.5 py36h19c0dcd_0
anaconda-navigator 1.6.9 py36h11ddaaa_0
anaconda-project 0.8.0 py36h29abdf5_0
appdirs 1.4.3 <pip>
asn1crypto 0.22.0 py36h265ca7c_1
astroid 1.5.3 py36hbdb9df2_0
astropy 2.0.2 py36ha51211e_4
babel 2.5.0 py36h7d14adf_0
backports 1.0 py36hfa02d7e_1
backports.shutil_get_terminal_size 1.0.0 py36hfea85ff_2
beautifulsoup4 4.6.0 py36h49b8c8c_1
bitarray 0.8.1 py36h5834eb8_0
bkcharts 0.2 py36h735825a_0
blaze 0.11.3 py36h4e06776_0
bleach 1.5.0 py36_0 conda-forge
bokeh 0.12.10 py36hbb0e44a_0
boto 2.48.0 py36h6e4cd66_1
bottleneck 1.2.1 py36haac1ea0_0
bzip2 1.0.6 h0376d23_1
ca-certificates 2018.8.24 ha4d7672_0 conda-forge
cairo 1.14.10 haa5651f_5
certifi 2018.8.24 py36_1 conda-forge
cffi 1.10.0 py36had8d393_1
chardet 3.0.4 py36h0f667ec_1
click 6.7 py36h5253387_0
cloudpickle 0.4.0 py36h30f8c20_0
clyent 1.2.2 py36h7e57e65_1
colorama 0.3.9 py36h489cec4_0
conda 4.5.11 py36_0 conda-forge
conda-build 3.0.27 py36h940a66d_0
conda-env 2.6.0 0 conda-forge
conda-verify 2.0.0 py36h98955d8_0
contextlib2 0.5.5 py36h6c84a62_0
cryptography 2.0.3 py36ha225213_1
cudatoolkit 8.0 3
cudnn 7.0.5 cuda8.0_0
curl 7.55.1 hcb0b314_2
cycler 0.10.0 py36h93f1223_0
cython 0.26.1 py36h21c49d0_0
cytoolz 0.8.2 py36h708bfd4_0
dask 0.15.3 py36hdc2c8aa_0
dask-core 0.15.3 py36h10e6167_0
datashape 0.5.4 py36h3ad6b5c_0
dbus 1.10.22 h3b5a359_0
decorator 4.1.2 py36hd076ac8_0
distributed 1.19.1 py36h25f3894_0
docutils 0.14 py36hb0f60f5_0
entrypoints 0.2.3 py36h1aec115_2
et_xmlfile 1.0.1 py36hd6bccc3_0
expat 2.2.4 hc00ebd1_1
fastcache 1.0.2 py36h5b0c431_0
ffmpeg 4.0 h04d0a96_0
filelock 2.0.12 py36hacfa1f5_0
flask 0.12.2 py36hb24657c_0
flask-cors 3.0.3 py36h2d857d3_0
fontconfig 2.12.4 h88586e7_1
freetype 2.8 h52ed37b_0
get_terminal_size 1.0.0 haa9412d_0
gevent 1.2.2 py36h2fe25dc_0
glib 2.53.6 hc861d11_1
glob2 0.5 py36h2c1b292_1
gmp 6.1.2 hb3b607b_0
gmpy2 2.0.8 py36h55090d7_1
graphite2 1.3.10 hc526e54_0
greenlet 0.4.12 py36h2d503a6_0
gsl 2.2.1 h0c605f7_3
gst-plugins-base 1.12.2 he3457e5_0
gstreamer 1.12.2 h4f93127_0
h5py 2.7.1 py36_1 conda-forge
harfbuzz 1.5.0 h2545bd6_0
hdf4 4.2.13 0 conda-forge
hdf5 1.8.18 3 conda-forge
heapdict 1.0.0 py36h79797d7_0
html5lib 0.9999999 py36_0 conda-forge
icu 58.2 h211956c_0
idna 2.6 py36h82fb2a8_1
imageio 2.2.0 py36he555465_0
imagesize 0.7.1 py36h52d8127_0
intel-openmp 2018.0.3 0
ipykernel 4.6.1 py36hbf841aa_0
ipython 6.1.0 py36hc72a948_1
ipython_genutils 0.2.0 py36hb52b0d5_0
ipywidgets 7.0.0 py36h7b55c3a_0
isort 4.2.15 py36had401c0_0
itsdangerous 0.24 py36h93cc618_1
jasper 1.900.1 4 conda-forge
jbig 2.1 hdba287a_0
jdcal 1.3 py36h4c697fb_0
jedi 0.10.2 py36h552def0_0
jinja2 2.9.6 py36h489bce4_1
jpeg 9c h470a237_0 conda-forge
jsonschema 2.6.0 py36h006f8b5_0
jupyter 1.0.0 py36h9896ce5_0
jupyter_client 5.1.0 py36h614e9ea_0
jupyter_console 5.2.0 py36he59e554_1
jupyter_core 4.3.0 py36h357a921_0
jupyterlab 0.27.0 py36h86377d0_2
jupyterlab_launcher 0.4.0 py36h4d8058d_0
krb5 1.14.2 0 conda-forge
lazy-object-proxy 1.3.1 py36h10fcdad_0
libedit 3.1 heed3624_0
libffi 3.2.1 h4deb6c0_3
libgcc 7.2.0 h69d50b8_2
libgcc-ng 7.2.0 h7cc24e2_2
libgfortran 3.0.0 1
libgfortran-ng 7.2.0 h9f7466a_2
libmklml 2018.0.3 0
libmxnet 1.2.1 gpu_mkl_h3d71631_1
libnetcdf 4.4.1.1 9 conda-forge
libopenblas 0.2.20 h9ac9557_7
libopencv 3.4.1 h62359dd_1
libopus 1.2.1 hb9ed12e_0
libpng 1.6.34 0 conda-forge
libprotobuf 3.5.2 hd28b015_1 conda-forge
libsodium 1.0.13 h31c71d8_2
libssh2 1.8.0 h8c220ad_2
libstdcxx-ng 7.2.0 h7a57d05_2
libtiff 4.0.9 he6b73bb_1 conda-forge
libtool 2.4.6 hd50d1a6_0
libvpx 1.7.0 h439df22_0
libxcb 1.12 h84ff03f_3
libxml2 2.9.4 h6b072ca_5
libxslt 1.1.29 hcf9102b_5
llvmlite 0.20.0 py36_0
locket 0.2.0 py36h787c0ad_1
lxml 4.1.0 py36h5b66e50_0
lzo 2.10 h1bfc0ba_1
Mako 1.0.7 <pip>
markdown 2.6.9 py36_0
markupsafe 1.0 py36hd9260cd_1
matplotlib 2.1.0 py36hba5de38_0
mccabe 0.6.1 py36h5ad9710_1
mistune 0.7.4 py36hbab8784_0
mkl 2018.0.0 hb491cac_4
mkl-dnn 0.14 h6bb024c_0
mkl-service 1.1.2 py36h17a0993_4
mpc 1.0.3 hf803216_4
mpfr 3.1.5 h12ff648_1
mpmath 0.19 py36h8cc018b_2
msgpack-python 0.4.8 py36hec4c5d1_0
multipledispatch 0.4.9 py36h41da3fb_0
mxnet 1.2.1 h8cc8929_0
mxnet-gpu 1.2.1 hf82a2c8_0
navigator-updater 0.1.0 py36h14770f7_0
nbconvert 5.3.1 py36hb41ffb7_0
nbformat 4.4.0 py36h31c9010_0
nccl 1.3.4 cuda8.0_1
ncurses 6.0 h06874d7_1
netcdf-fortran 4.4.4 5 conda-forge
networkx 2.0 py36h7e96fb8_0
ninja 1.8.2 h2d50403_1 conda-forge
nltk 3.2.4 py36h1a0979f_0
nose 1.3.7 py36hcdf7029_2
notebook 5.0.0 py36h0b20546_2
numba 0.35.0 np113py36_10
numexpr 2.6.2 py36hdd3393f_1
numpy 1.14.3 py36h28100ab_1
numpy-base 1.14.3 py36h0ea5e3f_1
numpydoc 0.7.0 py36h18f165f_0
odo 0.5.1 py36h90ed295_0
olefile 0.44 py36h79f9f78_0
openblas 0.2.20 7 conda-forge
openpyxl 2.4.8 py36h41dd2a8_1
openssl 1.0.2p h470a237_0 conda-forge
packaging 16.8 py36ha668100_1
pandas 0.20.3 py36h842e28d_2
pandoc 1.19.2.1 hea2e7c5_1
pandocfilters 1.4.2 py36ha6701b7_1
pango 1.40.11 h8191d47_0
partd 0.3.8 py36h36fd896_0
patchelf 0.9 hf79760b_2
path.py 10.3.1 py36he0c6f6d_0
pathlib2 2.3.0 py36h49efa8e_0
patsy 0.4.1 py36ha3be15e_0
pcre 8.41 hc71a17e_0
pep8 1.7.0 py36h26ade29_0
pexpect 4.2.1 py36h3b9d41b_0
pickleshare 0.7.4 py36h63277f8_0
pillow 4.2.1 py36h9119f52_0
pip 9.0.1 py36h8ec8b28_3
pixman 0.34.0 h83dc358_2
pkginfo 1.4.1 py36h215d178_1
ply 3.10 py36hed35086_0
prompt_toolkit 1.0.15 py36h17d85b1_0
protobuf 3.5.1 py36_3 conda-forge
psutil 5.4.0 py36h84c53db_0
ptyprocess 0.5.2 py36h69acd42_0
py 1.4.34 py36h0712aa3_1
py-mxnet 1.2.1 py36h6c82189_0
pycodestyle 2.3.1 py36hf609f19_0
pycosat 0.6.3 py36_0 conda-forge
pycparser 2.18 py36hf9f622e_1
pycrypto 2.6.1 py36h6998063_1
pycuda 2017.1.1 <pip>
pycurl 7.43.0 py36h5e72054_3
pyflakes 1.6.0 py36h7bd6a15_0
pygments 2.2.0 py36h0d3125c_0
pylint 1.7.4 py36hb9d4533_0
pyodbc 4.0.17 py36h999153c_0
pyopenssl 17.2.0 py36h5cc804b_0
pyparsing 2.2.0 py36hee85983_1
pyqt 5.6.0 py36h0386399_5
pysocks 1.6.7 py36hd97a5b1_1
pytables 3.4.2 py36_6 conda-forge
pytest 3.2.1 py36h11ad3bb_1
python 3.6.3 hc9025b9_1
python-dateutil 2.6.1 py36h88d3b88_1
pytools 2017.6 <pip>
pytorch 0.4.1 py36_py35_py27__9.0.176_7.1.2_2 pytorch
pytz 2017.2 py36hc2ccc2a_1
pywavelets 0.5.2 py36he602eb0_0
pyyaml 3.12 py36hafb9ca4_1
pyzmq 16.0.2 py36h3b0cf96_2
qt 5.6.2 h974d657_12
qtawesome 0.4.4 py36h609ed8c_0
qtconsole 4.3.1 py36h8f73b5b_0
qtpy 1.3.1 py36h3691cc8_0
readline 7.0 hac23ff0_3
requests 2.18.4 py36he2e5f8d_1
rope 0.10.5 py36h1f8c17e_0
ruamel_yaml 0.11.14 py36ha2fb22d_2
scikit-cuda 0.5.1 <pip>
scikit-image 0.13.0 py36had3c07a_1
scikit-learn 0.19.1 py36h7aa7ec6_0
scipy 0.19.1 py36h9976243_3
seaborn 0.8.0 py36h197244f_0
setuptools 36.5.0 py36he42e2e1_0
simplegeneric 0.8.1 py36h2cb9092_0
singledispatch 3.4.0.3 py36h7a266c3_0
sip 4.18.1 py36h51ed4ed_2
six 1.11.0 py36h372c433_1
snowballstemmer 1.2.1 py36h6febd40_0
sortedcollections 0.5.3 py36h3c761f9_0
sortedcontainers 1.5.7 py36hdf89491_0
sphinx 1.6.3 py36he5f0bdb_0
sphinxcontrib 1.0 py36h6d0f590_1
sphinxcontrib-websupport 1.0.1 py36hb5cb234_1
spyder 3.2.4 py36hbe6152b_0
sqlalchemy 1.1.13 py36hfb5efd7_0
sqlite 3.20.1 h6d8b0f3_1
statsmodels 0.8.0 py36h8533d0b_0
sympy 1.1.1 py36hc6d1c1c_0
tblib 1.3.2 py36h34cf8b6_0
tensorflow-gpu 1.4.1 0
tensorflow-gpu-base 1.4.1 py36h01caf0a_0
tensorflow-tensorboard 0.1.5 py36_0
terminado 0.6 py36ha25a19f_0
testpath 0.3.1 py36h8cadb63_0
tk 8.6.7 h5979e9b_1
toolz 0.8.2 py36h81f2dff_0
torchvision 0.2.1 py36_1 pytorch
tornado 4.5.2 py36h1283b2a_0
traitlets 4.3.2 py36h674d592_0
typing 3.6.2 py36h7da032a_0
udunits2 2.2.25 2 conda-forge
unicodecsv 0.14.1 py36ha668878_0
unixodbc 2.3.4 hc36303a_1
urllib3 1.22 py36hbe7ace6_0
wcwidth 0.1.7 py36hdf4376a_0
webencodings 0.5.1 py36h800622e_1
werkzeug 0.12.2 py36hc703753_0
wheel 0.29.0 py36he7f4e38_1
widgetsnbextension 3.0.2 py36hd01bb71_1
wrapt 1.10.11 py36h28b7045_0
xlrd 1.1.0 py36h1db9f0c_1
xlsxwriter 1.0.2 py36h3de1aca_0
xlwt 1.3.0 py36h7b00a1f_0
xz 5.2.3 h2bcbf08_1
yaml 0.1.7 h96e3832_1
zeromq 4.2.2 hb0b69da_1
zict 0.1.3 py36h3a3bf81_0
zlib 1.2.11 h470a237_3 conda-forge
运行代码时，出现的错误是：
(myenv) [sbasumallik@hpc1 CNN]$ python state_CNN.py
Using TensorFlow backend.
Traceback (most recent call last):
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/imp.py", line 243, in load_module
return load_dynamic(name, filename, file)
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/imp.py", line 343, in load_dynamic
return _load(spec)
ImportError: /usr/lib64/libstdc++.so.6: version `GLIBCXX_3.4.20' not found (required by /home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "stateEstimator_CNN.py", line 12, in <module>
import keras as k
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/keras/__init__.py", line 3, in <module>
from . import utils
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/keras/utils/__init__.py", line 6, in <module>
from . import conv_utils
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/keras/utils/conv_utils.py", line 9, in <module>
from .. import backend as K
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/keras/backend/__init__.py", line 89, in <module>
from .tensorflow_backend import *
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 5, in <module>
import tensorflow as tf
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/__init__.py", line 34, in <module>
from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/__init__.py", line 49, in <module>
from tensorflow.python import pywrap_tensorflow
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.py", line 74, in <module>
raise ImportError(msg)
ImportError: Traceback (most recent call last):
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
from tensorflow.python.pywrap_tensorflow_internal import *
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
_pywrap_tensorflow_internal = swig_import_helper()
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
_mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/imp.py", line 243, in load_module
return load_dynamic(name, filename, file)
File "/home/sbasumallik/.conda/envs/myenv/lib/python3.6/imp.py", line 343, in load_dynamic
return _load(spec)
ImportError: /usr/lib64/libstdc++.so.6: version `GLIBCXX_3.4.20' not found (required by /home/sbasumallik/.conda/envs/myenv/lib/python3.6/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so)
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/errors
for some common reasons and solutions. Include the entire stack trace
above this error message when asking for help.
我已经尝试过所有不同版本的Tensorflow，如用户在Stackoverflow的相关文章中所述，但没有一个起作用。