NVIDIA driver version/pytorch error message on Ubuntu 18.04

John_Price: <p>Hi,</p>
<p>in pycharm IDE I get the following error message:</p>
<p><code>RuntimeError: The NVIDIA driver on your system is too old (found version 9010). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver.</code></p>
<p>When I run <code>nvcc --version</code> in the console I get the following:</p>
<pre><code class="lang-auto">    nvcc: NVIDIA (R) Cuda compiler driver
    Copyright (c) 2005-2017 NVIDIA Corporation
    Built on Fri_Nov__3_21:07:56_CDT_2017
    Cuda compilation tools, release 9.1, V9.1.85
</code></pre>
<p>When I run <code>modinfo nvidia</code> I get this one:</p>
<pre><code class="lang-auto">    filename:       /lib/modules/4.15.0-58-generic/updates/dkms/nvidia.ko
    alias:          char-major-195-*
    version:        390.138
    supported:      external
    license:        NVIDIA
    srcversion:     9CF28EA4192CED46A545E30
    alias:          pci:v000010DEd00000E00sv*sd*bc04sc80i00*
    alias:          pci:v000010DEd*sv*sd*bc03sc02i00*
    alias:          pci:v000010DEd*sv*sd*bc03sc00i00*
    depends:        ipmi_msghandler
    retpoline:      Y
    name:           nvidia
    vermagic:       4.15.0-58-generic SMP mod_unload 
    signat:         PKCS#7
    signer:         
    sig_key:        
    sig_hashalgo:   md4
    parm:           NVreg_Mobile:int
    parm:           NVreg_ResmanDebugLevel:int
    parm:           NVreg_RmLogonRC:int
    parm:           NVreg_ModifyDeviceFiles:int
    parm:           NVreg_DeviceFileUID:int
    parm:           NVreg_DeviceFileGID:int
    parm:           NVreg_DeviceFileMode:int
    parm:           NVreg_UpdateMemoryTypes:int
    parm:           NVreg_InitializeSystemMemoryAllocations:int
    parm:           NVreg_UsePageAttributeTable:int
    parm:           NVreg_MapRegistersEarly:int
    parm:           NVreg_RegisterForACPIEvents:int
    parm:           NVreg_CheckPCIConfigSpace:int
    parm:           NVreg_EnablePCIeGen3:int
    parm:           NVreg_EnableMSI:int
    parm:           NVreg_TCEBypassMode:int
    parm:           NVreg_UseThreadedInterrupts:int
    parm:           NVreg_EnableStreamMemOPs:int
    parm:           NVreg_EnableBacklightHandler:int
    parm:           NVreg_RestrictProfilingToAdminUsers:int
    parm:           NVreg_EnableUserNUMAManagement:int
    parm:           NVreg_EnableIBMNPURelaxedOrderingMode:int
    parm:           NVreg_MemoryPoolSize:int
    parm:           NVreg_KMallocHeapMaxSize:int
    parm:           NVreg_VMallocHeapMaxSize:int
    parm:           NVreg_IgnoreMMIOCheck:int
    parm:           NVreg_RegistryDwords:charp
    parm:           NVreg_RegistryDwordsPerDevice:charp
    parm:           NVreg_RmMsg:charp
    parm:           NVreg_AssignGpus:charp
</code></pre>
<p>In another post I’ve seen that someone switched the drivers. Does somebody know how this works or has another hint for me?</p>

ptrblck: <p>Your installed NVIDIA driver 390.138 would allow to use CUDA&lt;=9.1 as seen <a href="https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility">here</a>.<br>
Assuming you’ve installed the PyTorch conda or pip binaries, you would have to update the driver to &gt;=396.26 to use the min. shipped CUDA9.2.</p>