![]() ![]() (After I installed the driver418, I installed the cuda9.0 firstly,but it didn't work because the same reason.Then I uninstalled it and tried the cuda9. I installed nvidia-driver by sudo apt-get install nvidia-418Īnd I installed cuda by download the cuda_9.2.148_396.37_linux and use sudo sh cuda_9.2.148_396.37_linux,(without installing the driver and I have set the relevant PATH). It gave me ->CUDA driver version is insufficient for CUDA runtime version. Then Then I install cuda9.2(The reason why I didn't choose cuda10.0 is that I want to use pytorch0.4 but it doesn't support cuda10.0).Ĭopyright (c) 2005-2018 NVIDIA CorporationĬuda compilation tools, release 9.2, V9.2.148īut when I check, cd /usr/local/cuda-9.2/samples/1_Utilities/deviceQuery Save the ~/.bashrc file and run the following command to update the environment variables: source ~/.bashrcĪfter installing CUDA 9.0 and updating the environment variables, you can test Tensorflow to ensure that it is working correctly.Firstly,I install nvidia-driver 418, the result is good. To do this, add the following lines to your ~/.bashrc file: export PATH=/usr/local/cuda-9.0/bin$ Step 3: Update Environment VariablesĪfter installing CUDA 9.0, you need to update the environment variables to ensure that Tensorflow uses the correct version of CUDA. sudo dpkg -i nv-tensorrtx86 sudo dpkg -i nv-tensorrtcross sudo apt-key add /var/nv-tensorrtx86/. This command will install CUDA 9.0 on your system. Once the download is complete, run the following command to install CUDA 9.0: sudo dpkg -i cuda-repo-ubuntu-local_9.0.176-1_b On this page, select the operating system, architecture, and distribution that matches your system. To download CUDA 9.0, go to the following link: This command will remove all CUDA packages from your system. ![]() I was having the same problem, what I did, and solved it: sudo apt-get install gcc And then make. To uninstall CUDA, run the following command: sudo apt-get remove -auto-remove cuda Step 9: Test the installation is successful or not. If you have previously installed CUDA on your system, you need to uninstall it before installing CUDA 9.0. Next, run below commands: sudo apt-get install python-pip sudo python -m pip. In this case, you need to install CUDA 9.0, which includes the libcublas.so.9.0 library.įollow the steps below to fix the libcublas.so.9.0 error: Step 1: Uninstall existing versions of CUDA I want to get boto3 working in a python3 script. To fix the libcublas.so.9.0 error, you need to install the correct version of the CUDA toolkit that matches the version of Tensorflow you are using. Tensorflow uses the CUDA toolkit for GPU acceleration, which requires the libcublas.so.9.0 library to be present on the system. The libcublas.so.9.0 library is part of the CUDA toolkit, which is an SDK for developing applications that run on Nvidia GPUs. ![]() However, this library is not found on your system, which causes the error. This error occurs because Tensorflow is looking for the libcublas.so.9.0 library, which is required for running Tensorflow with CUDA 9.2. When you try to import Tensorflow with CUDA 9.2, you may encounter the following error: ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory This file contains step by step instructions to install cuda v9.0 and cudnn 7.3.0 in ubuntu 18.04. In this article, we will explain what the libcublas.so.9.0 error means and provide a step-by-step guide on how to fix it. Cuda 9.0 installation on Ubuntu 18.04 LTS. ![]() This error is caused by a mismatch between the version of CUDA installed on your system and the version of libcublas library required by Tensorflow. | Miscellaneous How to Fix libcublas.so.9.0 Error When Importing Tensorflow with CUDA 9.2Īs a data scientist or software engineer, you may have encountered the libcublas.so.9.0 error when trying to import Tensorflow with CUDA 9.2. ![]()
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