I’m getting the following errors:
That happens every time I run this, or I get to this point in the code:
pred = model.predict(x)
print(pred)
When I run the next code I get the following output.
I’m getting the following errors:
That happens every time I run this, or I get to this point in the code:
pred = model.predict(x)
print(pred)
When I run the next code I get the following output.
This has been run in a MacBook Pro mid 2015 i7 2.8 16GB. I thing this machine is capable of running this simple program.
Thank you!
When you get the “Kernel Restarting” message, it means that Python has crashed. Unfortunately, it doesn’t really tell you why but it’s likely that there was a problem with Keras or TensorFlow.
Does the Terminal window from which you launched Jupyter notebook show any messages?
(By the way, after such a crash happens, you will need to run every cell in the notebook again, you can’t just continue with the next one.)
Hi,
I have the same problem. ‘The kernel appears to have died. It will restart automatically’.
Does anyone have an idea how to fix it?
The error occurs when executing
pred = model.predict(x)
print(pred)
In the terminal I see the following log output:
OMP: Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized.
OMP: Hint: This means that multiple copies of the OpenMP runtime have been linked into
the program. That is dangerous, since it can degrade performance or cause incorrect
results. The best thing to do is to ensure that only a single OpenMP runtime is linked into
the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an
unsafe, unsupported, undocumented workaround you can set the environment variable
KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may
cause crashes or silently produce incorrect results. For more information, please see
http://www.intel.com/software/products/support/
These are all installed packages in the Conda environment:
Name Version Build Channel
_tflow_select 2.3.0 mkl
absl-py 0.7.1 pypi_0 pypi
appnope 0.1.0 py36hf537a9a_0
astor 0.8.0 pypi_0 pypi
attrs 19.1.0 py36_1
backcall 0.1.0 py36_0
blas 1.0 mkl
bleach 3.1.0 py36_0
c-ares 1.15.0 h1de35cc_1
ca-certificates 2019.5.15 0
certifi 2019.6.16 py36_0
cloudpickle 1.1.1 py_0
coremltools 2.1.0 pypi_0 pypi
cycler 0.10.0 py36hfc81398_0
cytoolz 0.9.0.1 py36h1de35cc_1
dask-core 2.0.0 py_0
decorator 4.4.0 py36_1
defusedxml 0.6.0 py_0
entrypoints 0.3 py36_0
freetype 2.9.1 hb4e5f40_0
gast 0.2.2 pypi_0 pypi
google-pasta 0.1.7 pypi_0 pypi
grpcio 1.21.1 pypi_0 pypi
h5py 2.9.0 py36h3134771_0
hdf5 1.10.4 hfa1e0ec_0
imageio 2.5.0 py36_0
intel-openmp 2019.4 233
ipykernel 5.1.1 py36h39e3cac_0
ipython 7.5.0 py36h39e3cac_0
ipython_genutils 0.2.0 py36h241746c_0
jedi 0.13.3 py36_0
jinja2 2.10.1 py36_0
joblib 0.13.2 py36_0
jpeg 9b he5867d9_2
jsonschema 3.0.1 py36_0
jupyter_client 5.2.4 py36_0
jupyter_core 4.4.0 py36_0
keras 2.2.0 pypi_0 pypi
keras-applications 1.0.2 py36_0
keras-preprocessing 1.0.1 py36_0
kiwisolver 1.1.0 py36h0a44026_0
libcxx 4.0.1 hcfea43d_1
libcxxabi 4.0.1 hcfea43d_1
libedit 3.1.20181209 hb402a30_0
libffi 3.2.1 h475c297_4
libgfortran 3.0.1 h93005f0_2
libpng 1.6.37 ha441bb4_0
libprotobuf 3.8.0 hd9629dc_0
libsodium 1.0.16 h3efe00b_0
libtiff 4.0.10 hcb84e12_2
llvm-openmp 4.0.1 hcfea43d_1
markdown 3.1.1 py36_0
markupsafe 1.1.1 py36h1de35cc_0
matplotlib 3.1.0 py36h54f8f79_0
mistune 0.8.4 py36h1de35cc_0
mkl 2019.4 233
mkl-service 2.0.2 py36h1de35cc_0
mkl_fft 1.0.12 py36h5e564d8_0
mkl_random 1.0.2 py36h27c97d8_0
mock 3.0.5 py36_0
nbconvert 5.5.0 py_0
nbformat 4.4.0 py36h827af21_0
ncurses 6.1 h0a44026_1
networkx 2.3 py_0
notebook 5.7.8 py36_0
numpy 1.16.4 py36hacdab7b_0
numpy-base 1.16.4 py36h6575580_0
olefile 0.46 py36_0
openssl 1.1.1c h1de35cc_1
pandas 0.24.2 py36h0a44026_0
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py36_1
parso 0.4.0 py_0
patsy 0.5.1 py36_0
pexpect 4.7.0 py36_0
pickleshare 0.7.5 py36_0
pillow 6.0.0 py36hb68e598_0
pip 19.1.1 py36_0
prometheus_client 0.6.0 py36_0
prompt_toolkit 2.0.9 py36_0
protobuf 3.8.0 pypi_0 pypi
ptyprocess 0.6.0 py36_0
pygments 2.4.2 py_0
pyparsing 2.4.0 py_0
pyrsistent 0.14.11 py36h1de35cc_0
python 3.6.8 haf84260_0
python-dateutil 2.8.0 py36_0
pytz 2019.1 py_0
pywavelets 1.0.3 py36h1d22016_1
pyyaml 5.1.1 pypi_0 pypi
pyzmq 18.0.0 py36h0a44026_0
readline 7.0 h1de35cc_5
scikit-image 0.15.0 py36h0a44026_0
scikit-learn 0.21.2 py36h27c97d8_0
scipy 1.2.1 py36h1410ff5_0
seaborn 0.9.0 py36_0
send2trash 1.5.0 py36_0
setuptools 41.0.1 py36_0
six 1.12.0 py36_0
sqlite 3.28.0 ha441bb4_0
statsmodels 0.9.0 py36h1d22016_0
tensorboard 1.14.0 pypi_0 pypi
tensorflow 1.14.0 pypi_0 pypi
tensorflow-base 1.13.1 mkl_py36hc36dc97_0
tensorflow-estimator 1.14.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
terminado 0.8.2 py36_0
testpath 0.4.2 py36_0
tfcoreml 0.3.0 pypi_0 pypi
tk 8.6.8 ha441bb4_0
toolz 0.9.0 py36_0
tornado 6.0.2 py36h1de35cc_0
traitlets 4.3.2 py36h65bd3ce_0
wcwidth 0.1.7 py36h8c6ec74_0
webencodings 0.5.1 py36_1
werkzeug 0.15.4 py_0
wheel 0.33.4 py36_0
wrapt 1.11.2 pypi_0 pypi
xz 5.2.4 h1de35cc_4
yaml 0.1.7 hc338f04_2
zeromq 4.3.1 h0a44026_3
zlib 1.2.11 h1de35cc_3
zstd 1.3.7 h5bba6e5_0
I could eventually fix it. I did some Googling and after a bit of trial/error I got it working. It seems it’s a macOS only problem that occurs on Mojave.
The fix was adding this to the import statements at the top of the notebook:
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'