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After install and uninstall a package, python3 crashes with error "Segmentation fault (core dumped)"

The steps leading to the problem is as follows:
I installed a package using pip. The package is here and its install doc is here. The command I used is
pip install --upgrade tensorflow-graphics-gpu
Because I don't have super user privilege, the package was installed in my user space. pip prompted me for that.
I uninstalled the package using
pip uninstall tensorflow-graphics-gpu
I started python3 and type
import tensorflow as tf
This statement worked fine before. But this time, python quits with an error:
Segmentation fault (core dumped)
This is a screenshot: enter image description here.
The environment is as follows:
A remote Linux. Core version 5.8.0. I am not not a super user.
Python 3.8.6
CUDA 11.1
CPU: Core i9-10900K
nVidia RTX GPU
The same error crashes python if I tried to import PyTorch. The sys admin is very disagreeable so I can get no help from him, not to mention upgrading drivers or reinstalling python. I tried to clear cashes in my user space that I know of, but I didn't have luck. I searched internet for a solution but of no avail.
Can someone please tell me how to fix this issue? Thanks a lot.

I tried to clear cashes in my user space that I know of, but I didn't have luck.
It seems pretty clear that something in your $HOME directory is still being used, and is causing the system python to crash.
To discover what that something is, you can look at which files are being opened using this command:
strace -e file python -c 'import tensorflow'
Once you know which files are being opened, remove/reinstall corresponding packages, and you should be back in business.

error while import pytorch module. (The specified module could not be found.)

I just newly install python 3.8 via anaconda installer and install pytorch using command
conda install pytorch torchvision cpuonly -c pytorch
when i try to import torch, I got this error message.
OSError: [WinError 126] The specified module could not be found. Error loading "C:\Users\chunc\anaconda3\lib\site-packages\torch\lib\asmjit.dll" or one of its dependencies.
I can see dll files are still in the directory.
I ran Dependency Walker and it gave me this result.
I am with this problem for a day.
What should i do if i want to use PyTorch module?

I had the same problem, you should check if you installed Microsoft Visual C++ Redistributable, because if you didn't this may lead to the DLL load failure.
Here is a link to download it: https://aka.ms/vs/16/release/vc_redist.x64.exe

Problem solved by downgrade PyTorch version to 1.5.1

I tried so many different solutions but I couldn't get PyTorch to work on my main conda environment. So finally I created a new environment and installed PyTorch on it; everything worked on the first try.

Tensorflow GPU / CUDA installation on Ubuntu

I have set up a Ubuntu 18.04 and tried to make Tensorflow 2.2 GPU work (I have an Nvidia/CUDA graphic card) with Python.
Even after reading the documentation https://www.tensorflow.org/install/gpu#linux_setup, it failed (see below for details about how it failed).
Question: would you have a canonical "todo" list (starting point: freshly installed Ubuntu server) on how to install tensorflow-gpu and make it work, with a few steps?
Notes:
I have read many similar forum posts, and I think that having a canonical "todo" (from a fresh Ubuntu install to having tensorflow-gpu working) would be interesting, with a few steps/bash commands
the documentation I used involved
export LD_LIBRARY_PATH...
# Add NVIDIA package repository
sudo apt-key adv --fetch-keys http://developer.download...
...
# Install CUDA and tools. Include optional NCCL 2.x
sudo apt install cuda9.0 cuda...
Even after a lot of trial and errors (I don't copy/paste all the different errors here, would be too long), then at the end:
import tensorflow
always failed. Some reasons included `ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory. I have already read the relevant question here, or this very long (!) Github issue.
After some trial and error, import tensorflow works, but it doesn't use the GPU (see also Tensorflow not running on GPU).

Well, I was facing the same problem. The first thing to do is to look up, which Tensorflow version is required. In your case Tensorflow 2.2. requires CUDA 10.1. The correct cuDNN version is also important. In your case it would be cuDNN 7.4. An additional point is the installed python version. I would recommend Python 3.5-3.8. If one those mismatch, a fully compatibility is almost impossible.
So if you want a check list, here you go:
Install CUDA 10.1 by installing nvidia-cuda-toolkit.
Install the cuDNN version compatible with CUDA 10.1.
Export CUDA environment variables.
If Bazel is not installed, you will be asked on that.
Install TensorFlow 2.2 using pip. I would highly recommend the usage of a virtual environment.
You can find the compatibility check list of Tensorflow and CUDA here
You can find the CUDA Toolkit here
Finally get cuDNN in the correct version here
That's all.

I faced the problem as well when using the Google Cloud Platform for two projects involving deep learning. They provide servers with nothing but a freshly installed Ubuntu OS. Regarding my experience, I recommend doing the following steps:
Look up the cuda and cuDNN version supported by the current Tensorflow release on the Tensorflow page.
Install the targeted cuda version from the deb package retrieved from Nvidias cuda page and be careful that more recent cuda versions might not work! This will automatically install the corresponding Nvidia drivers.
Install the targeted cuDNN version from this page and again be careful that a more recent cuDNN version might not work.
Install tensorflow-gpu using pip.
This should work. Your problem is probably that you are using a more recent cuda version than targeted by the current Tensorflow release.

To install tensorflow-gpu, the guidelines which are provided on official website are very tedious for beginers, instead we can do these simple steps:
Note : NVIDIA driver must be installed before this(you can verify this using command nvidia-smi).
Install Anaconda https://www.anaconda.com/distribution/?
Create an virtual environment using command "conda create -n envname"
Then activate env using command "conda activate envname"
Finally install tensorflow using command "conda install tensorflow-gpu"
With the given code
import tensorflow as tf
if tf.test.gpu_device_name():
print('Default GPU Device{}'.format(tf.test.gpu_device_name()))
else:
print("not using gpu")
You can find the tutorial on link given below
https://www.pugetsystems.com/labs/hpc/Install-TensorFlow-with-GPU-Support-the-Easy-Way-on-Ubuntu-18-04-without-installing-CUDA-1170/?

I would suggest to first check the availability of GPU using nvidia-smi command.
I had faced the same issue, i was able to resolve it by using docker container, you can install docker using Install Docker Engine on Ubuntu or use the Digital Ocean guide (i used this one) How To Install and Use Docker on Ubuntu 18.04
After that it is simple just run the following command based on the requirements
NV_GPU='0' nvidia-docker run --runtime=nvidia -it -v /path/to/folder:/path/to/folder/for/docker/container nvcr.io/nvidia/tensorflow:17.11
NV_GPU='0' nvidia-docker run --runtime=nvidia -it -v /storage/research/:/storage/research/ nvcr.io/nvidia/tensorflow:20.12-tf2-py3
Here '0' represents the GPU number, if you want to use more than one GPU just use '0,1,2' and so on ....
Hope this solves the issue.

Tensorflow install failed inside Anaconda in Windows Machine

Well, I am so tired of trying to install Tensorflow in Anaconda, I have installed anaconda successfully, but when I am going to install form this link, Anaconda installation on Step 4, I am seeing some exception.
I have executed this line of command
pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.0.0-cp35-cp35m-win_x86_64.whl
However it's terminating showing a red single line exception.
Later I have searched for some solution on here and there. I have found some solution too. In this solution is done for only MAC OX and Linux only, not for Windows. Later I found somewhere to use the python version 2.7 so I have downgraded the Python in lower version, however it was same. But this time I can able to to execute the MAC OX command successfully and in my prompt it shows that install successful. But when I had gone to import Tensorflow then again an error is threading, like this
I have also found the some other solutions link1 link2, however none of them are done in which process I'm approaching. I am in a quiet confusion what kind of error or exception it is? And how do I overcome it?
Update:
Tensorflow has been installed successfully from this link, Now a different problem is being facing. When I am going to import tensorflow in my workspace it providing this error.

It looks like it cannot find the required CUDA libraries. Did you install the CUDA Toolkit 8.0 and cuDNN 5.1?
You will have to install the CUDA Toolkit 8.0 e.g. from here and the cuDNN package from e.g. here and then put the cuDNN-installation-path/win10/bin on your path (depending on your windows version of course)
Also the following two posts might help you out:
On Windows, running "import tensorflow" generates No module named "_pywrap_tensorflow" error
TensorFlow on Windows: "Couldn't open CUDA library cudnn64_5.dll"

How to install keras on Win10?

I know there are a lot of tutorials of installing keras on win. But I am faced with a weird problem and I cannot find a solution on Google.
The version of python I used is 2.7(anaconda 64bit).
When I typed 'pip install keras' in cmd, an error occurred.
It is said that no matching distribution found for tensorflow(from keras).
I googled it and one saying goes that this problem occurred when python is 32bit on windows. However, my python is 64-bit, so this saying does not hold.
I want to know how to handle this, given that I want to use theano as keras backend instead of tensorflow.

I think the problem is that TensorFlow on Windows only support Python 3.5.X.
You should try installing anaconda3.
Source: https://www.tensorflow.org/install/install_windows

using commad pip install -v -v -v keras may offer you more information about this
and I find this commad may download Keras tar file in site https://pypi.python.org/simple/keras/
and after download file, it will check the requires.txt in Keras.egg-info
then i find in Keras 2.0.0 it require tensorflow instead of theano in this version, otherwise you may fail to install
so the solution is, download the other keras in site which requires theano not tensorflow, and unpack it, then cd its directory, and use python setup.py install to install this version of keras