The kernel appears to have died it will restart automatically что делать
Как отладить умирающее ядро Jupyter Python3?
Я запускаю некоторый код, используя scipy и scikits.learn на ноутбуке Jupyter с использованием ядра Python 3. Во время вычислений ядро перезапускается с помощью диалогового окна с сообщением о том, что «ядро, похоже, умерло. Оно перезапустится автоматически». Stderr базового процесса Jupyter просто регистрирует тот факт, что ядро умирает и будет перезапущено без каких-либо полезных сообщений. Есть ли способ проверить основную ошибку? Это может быть ошибка, исходящая из некоторого кода C ++, но я могу только догадываться. Я искал любые соответствующие журналы на сервере и не смог найти ничего полезного.
2 ответа
Теперь вернемся к вашему вопросу: отображаемое диалоговое окно: «Ядро, похоже, умерло. Оно автоматически перезапустится». сама по себе не является «ошибкой». Это больше похоже на «Jupyter Notebook, помогающий самому себе», очищающий все переменные и перезагружающий ядро. Это Jupyter Notebook, посылающий сигнал SOS и получающий помощь от себя, чтобы он не зависал. Что в противном случае привело бы к тому, что перезапущенный ноутбук Jupyter не имел несохраненных изменений. (Хорошо, это автосохранение, но не «автоматическая контрольная точка»)
Но вместо этого разработчики были достаточно любезны, чтобы позволить ему позаботиться о себе.
Примечание 2: Если вы используете CUDA, помните, что Jupyter Notebook не может освободить ресурсы CUDA даже после завершения сеанса. Так что это может быть причиной перезапуска.
During the computation the kernel is being restarted with a message dialogue saying that “The kernel appears to have died. It will restart automatically.”.
Можете ли вы опубликовать сообщение об ошибке (может отображаться в форме терминала, где вы запускаете ноутбук) и фрагмент кода, который вы пытаетесь запустить? Таким образом, мы можем ответить лучше!
Jupyter | The kernel appears to have died. It will restart automatically |
I have been running a particular python script for some time. All of the script had been running perfectly fine (including in Jupyter) for many months before this. Now, somehow, the jupyter in my system has started showing the following error message at one particular line of the code (the last line of the below mentioned code). All parts of the code run fine, except for the last line of the code (where I call a user defined function to do pair counts). The user defined function (correlation.polepy) can be found from https://github.com/OMGitsHongyu/N-body-analysis
This is the error message that I am getting:
And, here is the skeleton of my Python Code:
Similar problem happens (last line of the code) when I try to use IPython. When I try to use Python (implement in terminal), I get an error message (at the last line) which says «Segmentation fault: 11«. I am using Python 2.7.13 :: Anaconda 2.5.0 (x86_64).
I have tried the following methods already in search for a solution:
1.> I checked some of the previous links on stackoverflow where this problem has been asked: The kernel appears to have died. It will restart automatically
I tried the solution given in the link above; sadly it doesn’t seem to work for my case. This is the solution that was mention in the link given above:
2.> Just to check if the system is running out of memory, I closed all applications which are heavy on memory. My system has 16 GB physical memory and even when there is over 9 GB of free memory, this problem happens (again, this problem had not been happening before, even when I had been using 14 GB in other tasks and had less than 2 GB of memory. It’s very surprising that I could run task with given inputs before and I am not able to replicate calculation with the same exact inputs now.)
This one appears to tackle similar problems and it speaks about there not being enough memory for the docker container. I had doubts about how to implement the suggestions mentioned in there.
All in all, I am not sure how this problem arose in the first place. How do I solve this problem? Any help will be much appreciated.
Keras code not working in Jupyter: «The kernel appears to have died. It will restart automatically.»
I am writing code in Keras for a simple deep learning based 30×30 cat image classifier. When I get to the portion of my code that is supposed to train the model, Jupyter stops running and gives the error message «The kernel appears to have died. It will restart automatically.» I do not know what is causing this to happen. If I look in terminal I’m getting a CUDA_ERROR_OUT_OF_MEMORY: out of memory; total memory reported: 11520114688. I would think that a simple classifier would not be exhausting the resources of my PC. I have a RTX 2080TI, 32gb ram, i9-9900k.
I don’t know if it’s a compatibility issue with software or what. But I do know that tensorflow-gpu is working because in my console it says so. The code I’m using is essentially verbatim from a deep learning in Keras book. The code ran fine on my 6 year old laptop, although trained very slow.
After running this block above: WARNING:tensorflow:From /home/name/venv/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version. Instructions for updating: Colocations handled automatically by placer. WARNING:tensorflow:From /home/name/venv/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:3445: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version. Instructions for updating:
After I run this, this is the output:
Additional copy-paste from terminal:
+——————————————————————————+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | 0 1253 G /usr/lib/xorg/Xorg 26MiB | | 0 1364 G /usr/bin/gnome-shell 58MiB | | 0 3027 G /usr/lib/xorg/Xorg 188MiB | | 0 3164 G /usr/bin/gnome-shell 139MiB | | 0 7687 G /usr/lib/firefox/firefox 6MiB | | 0 8085 G /usr/lib/firefox/firefox 6MiB | +——————————————————————————+
absl-py 0.7.0
astor 0.7.1
attrs 18.2.0
backcall 0.1.0
bleach 3.1.0
cycler 0.10.0
decorator 4.3.2
defusedxml 0.5.0
entrypoints 0.3
gast 0.2.2
grpcio 1.19.0
h5py 2.9.0
ipykernel 5.1.0
ipython 7.3.0
ipython-genutils 0.2.0
ipywidgets 7.4.2
jedi 0.13.3
Jinja2 2.10
jsonschema 3.0.0
jupyter 1.0.0
jupyter-client 5.2.4
jupyter-console 6.0.0
jupyter-core 4.4.0
Keras 2.2.4
Keras-Applications 1.0.7
Keras-Preprocessing 1.0.9
kiwisolver 1.0.1
Markdown 3.0.1
MarkupSafe 1.1.1
matplotlib 3.0.2
mistune 0.8.4
mock 2.0.0
nbconvert 5.4.1
nbformat 4.4.0
notebook 5.7.4
numpy 1.16.2
pandas 0.24.1
pandocfilters 1.4.2
parso 0.3.4
pbr 5.1.3
pexpect 4.6.0
pickleshare 0.7.5
Pillow 5.4.1
pip 19.3.1
pkg-resources 0.0.0
prometheus-client 0.6.0
prompt-toolkit 2.0.9
protobuf 3.7.0
ptyprocess 0.6.0
Pygments 2.3.1
pyparsing 2.3.1
pyrsistent 0.14.11
python-dateutil 2.8.0
pytz 2018.9
PyYAML 3.13
pyzmq 18.0.0
qtconsole 4.4.3
scikit-learn 0.20.2
scipy 1.2.1
Send2Trash 1.5.0
setuptools 40.8.0
six 1.12.0
tensorboard 1.13.0
tensorflow-estimator 1.13.0
tensorflow-gpu 1.13.1
termcolor 1.1.0
terminado 0.8.1
testpath 0.4.2
torch 1.0.1.post2 torchvision 0.2.2.post2 tornado 5.1.1
traitlets 4.3.2
wcwidth 0.1.7
webencodings 0.5.1
Werkzeug 0.14.1
wheel 0.33.1
widgetsnbextension 3.4.2
The kernel appears to have died. It will restart automatically. #51
Comments
silverswingkiller commented Dec 4, 2020
After modifying the name of the installation package, I successfully created a virtual environment with the official script and installed tensorflow, but when I use jupyter to run the code, it still fails to run。The kernel appears to have died when i training
The text was updated successfully, but these errors were encountered:
anna-tikhonova commented Dec 4, 2020
Thank you for reporting this issue. We will experiment with Jupyter notebooks.
icenando commented Dec 5, 2020
After modifying the name of the installation package, I successfully created a virtual environment with the official script and installed tensorflow, but when I use jupyter to run the code, it still fails to run。The kernel appears to have died when i training
I was having the same issue. Apparently it’s an architecture (chip) issue. If you run jupyter from terminal and observe the terminal, it will show you what the kernel is doing. Mine was giving me a «wrong architecture» error (or something like that) before the kernel died. I was using a Tensorflow 2.0 though, so I assumed that it didn’t work with my Mac M1. I since then haven’t been able to install the arm version of Tensorflow (see issue 48)
jmbernabotto commented Dec 6, 2020
jmbernabotto commented Dec 6, 2020
dmmajithia commented Dec 7, 2020
seongilp commented Dec 9, 2020
please refer to below links
anna-tikhonova commented Dec 15, 2020
@silverswingkiller Could you let me know if the discussion in #45 helps?
maeverst commented Dec 29, 2020
I am receiving the same error (Kernel appears to have died. ) when I launch jupyter notebook from the terminal. This just started happening.
Does anyone know why please?
vitdegtyarev commented Jan 3, 2021
I’m getting the same error («The kernel appears to have died. It will restart automatically») on Windows when I run the «import keras» or «import tensorflow» command. The commands worked fine about a week ago. Not sure what has changed.
icenando commented Jan 4, 2021
Same here. It was fine until about 2 weeks ago, when I last tested.
vitdegtyarev commented Jan 16, 2021
asima-azmat commented Jan 28, 2021
I am having the same issue when I run the cell where I am training my network.
Dying kernel on Jupiter notebook #1197
Comments
AMSolin commented Mar 2, 2020 •
Problem: After run model.fit() (CatBoostClassifier) in jupiter notebook i got message «The kernel appears to have died. It will restart automatically.». Its happens also on tutorial https://github.com/catboost/tutorials/blob/master/python_tutorial.ipynb
Re-installing anaconda don’t solve problem.
catboost version: 0.22 (same problem 0.21)
Operating System: Windows 10 Corporate LTSC
CPU: Intel(R) Core(TM)2 Quad_CPU 8400 2.66GHz
The text was updated successfully, but these errors were encountered:
kizill commented Mar 2, 2020
Hi! Could you check jupyter notebook output in console? I hope there could be something like exception or another kind of message.
AMSolin commented Mar 2, 2020
Hi! In output i got this:
AMSolin commented Mar 4, 2020 •
Hi! Could you check jupyter notebook output in console? I hope there could be something like exception or another kind of message.
my CPU doesn’t support AVX instructions. It can be a reason of my problem?
Also, using task_type=»GPU» dont cause kernel death.
kizill commented Mar 10, 2020
Could you try attaching a debugger to python.exe that runs your kernel and make crashdump? You may use WinDBG or another windows debugger.
annaveronika commented Mar 10, 2020
AMSolin commented Mar 14, 2020
sviperm commented Mar 27, 2020
I’ve got the same error on Ubuntu 18.04 on running cross validation code from here and here
notebook output in console:
Error is in jupyter lab too. Error missing after commenting task_type parameter. Thats very strange, because text processing needs GPU.
Does cross-validation works properly in this situation? Can I use it? or better to use custom methods to check training quality?
annaveronika commented May 7, 2020
I’ve got the same error on Ubuntu 18.04 on running cross validation code from here and here
notebook output in console:
Error is in jupyter lab too. Error missing after commenting task_type parameter. Thats very strange, because text processing needs GPU.
Does cross-validation works properly in this situation? Can I use it? or better to use custom methods to check training quality?
Text features were not supported on CPU before version 0.23, now they are supported, so you should not see this error msg.
aerosh commented Jun 22, 2020
@annaveronika I don’t know if these issues are related or not, but I get the same error when using the GPU. When I use the CPU, everything is normal. When using a GPU, my RAM is 100% full and I get a dead kernel error. When I use the CPU on the same data I have about 60% free RAM and everything works well.
maximrohit commented Feb 25, 2021
Getting the same error!
maximrohit commented Feb 25, 2021
nstoichkov7 commented Jun 24, 2021 •
I have the same issue under Windows 10, CPU Xeon E5-2670, GPU Nvidia GTX 1070, python 3.8
I do not change the value of grow_policy parameter, use it with its default value «SymmetricTree»
This problem only occur in version 0.26
In version 0.21 everything works fine for me
nateGeorge commented Jul 1, 2021
I’m getting the same error on Win10 with catboost version 0.26. With version 0.25.1, it works.
kizill commented Jul 5, 2021
@nateGeorge @nstoichkov7
Will merge fix in #1763 and then we will publish release 0.26.1 in a matter of days, thank you all for patience 😺
Closing as duplicate of #1735, more info here
v1lev commented Jul 26, 2021
garikhgh commented Jul 31, 2021
I have the same issue. windows 10
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