Could not load dynamic library cudart64 101 dll on tensorflow CPU-only installation

Question

I just installed the latest version of Tensorflow via pip install tensorflow and whenever I run a program  I get the log message      W tensorflow stream executor platform default dso loader cc 55  Could not load dynamic library  cudart64 101 dll   dlerror  cudart64 101 dll not found   Is this bad  How do I fix the error

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In a conda environment  this is what solved my problem  I was missing cudart64-100 dll   Downloaded it from dll-files com CUDART64 100 DLL  Put it in my conda environment at C  Users  lt user gt  Anaconda3 envs  lt env name gt  Library bin   That s all it took  You can double check if it s working  import tensorflow as tf tf config experimental list physical devices  GPU

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This solution worked for me   I preinstalled the environnement with anaconda  here is the code  conda create -n YOURENVNAME python 3 6    3 6 gt  incompatible with keras conda activate YOURENVNAME conda install tensorflow-gpu conda install -c anaconda keras conda install -c anaconda scikit-learn conda install matplotlib  but after I had still these warnings 2020-02-23 13 31 44 910213  W tensorflow stream executor platform default dso loader cc 55  Could not load dynamic library  cudart64 101 dll   dlerror  cudart64 101 dll not found  2020-02-23 13 31 44 925815  I tensorflow stream executor platform default dso loader cc 44  Successfully opened dynamic library cublas64 10 dll  2020-02-23 13 31 44 941384  I tensorflow stream executor platform default dso loader cc 44  Successfully opened dynamic library cufft64 10 dll  2020-02-23 13 31 44 947427  I tensorflow stream executor platform default dso loader cc 44  Successfully opened dynamic library curand64 10 dll  2020-02-23 13 31 44 965893  I tensorflow stream executor platform default dso loader cc 44  Successfully opened dynamic library cusolver64 10 dll  2020-02-23 13 31 44 982990  I tensorflow stream executor platform default dso loader cc 44  Successfully opened dynamic library cusparse64 10 dll  2020-02-23 13 31 44 990036  W tensorflow stream executor platform default dso loader cc 55  Could not load dynamic library  cudnn64 7 dll   dlerror  cudnn64 7 dll not found  How I solved the first warning   I just download a zip file wich contained all the cudnn files  dll  etc  here   https   developer nvidia com cudnn How I solved the second warning   I looked the last missing file  cudart64 101 dll  in my virtual env created by conda and I just copy pasted it in the same lib folder than for the  dll cudnn

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Tensorflow gpu 2 2 and 2 3 nightly  along CUDA Toolkit 11 0 RC  To solve the same issue as OP  I just had to find cudart64 101 dll on my disk  in my case C  Program Files NVIDIA Corporation NvStreamSrv  and add it as variable environment  that is add value C  Program Files NVIDIA Corporation NvStreamSrv cudart64 101 dll to user s environment variable Path

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Tensorflow 2 1 works with Cuda 10 1    If you want a quick hack    Just download cudart64 101 dll from here  Extract the zip file and copy the cudart64 101 dll to your CUDA bin directory   Else    Install Cuda 10 1

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Tensorflow 2 1  What s going on  With the new Tensorflow 2 1 release  the default tensorflow pip package contains both CPU and GPU versions of TF  In previous TF versions  not finding the CUDA libraries would emit an error and raise an exception  while now the library dynamically searches for the correct CUDA version and  if it doesn t find it  emits the warning  The W in the beginning stands for warnings  errors have an E  or F for fatal errors  and falls back to CPU-only mode  In fact  this is also written in the log as an info message right after the warning  do note that if you have a higher minimum log level that the default  you might not see info messages   The full log is  emphasis mine    2020-01-20 12 27 44 554767  W tensorflow stream executor platform default dso loader cc 55  Could not load dynamic library  cudart64 101 dll   dlerror  cudart64 101 dll not found 2020-01-20 12 27 44 554964  I tensorflow stream executor cuda cudart stub cc 29  Ignore above cudart dlerror if you do not have a GPU set up on your machine   Should I worry  How do I fix it  If you don t have a CUDA-enabled GPU on your machine  or if you don t care about not having GPU acceleration  no need to worry  If  on the other hand  you installed tensorflow and wanted GPU acceleration  check your CUDA installation  TF 2 1 requires CUDA 10 1  not 10 2 or 10 0   If you just want to get rid of the warning  you can adapt TF s logging level to suppress warnings  but that might be overkill  as it will silence all warnings   Tensorflow 1 X or 2 0  Your CUDA setup is broken  ensure you have the correct version installed

User · Answer

In my case the tensorflow install was looking for cudart64 101 dll  The 101 part of cudart64 101 is the Cuda version - here 101   10 1 I had downloaded 11 x  so the version of cudart64 on my system was cudart64 110 dll  This is the wrong file   cudart64 101 dll   cudart64 110 dll Solution Download Cuda 10 1 from https   developer nvidia com  Install  mine crashes with NSight Visual Studio Integration  so I switched that off   When the install has finished you should have a Cuda 10 1 folder  and in the bin the dll the system was complaining about being missing  Check that the path to the 10 1 bin folder is registered as a system environmental variable  so it will be checked when loading the library  You may need a reboot if the path is not picked up by the system straight away

User · Answer

A simpler way would be to create a link called cudart64 101 dll to point to cudart64 102 dll  This is not very orthodox but since TensorFlow is looking for cudart64 101 dll exported symbols and the nvidia folks are not amateurs  they would most likely not remove symbols from 101 to 102  It works  based on this assumption  mileage may vary

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This answer might be helpful if you see above error but actually you have CUDA 10 installed  pip install tensorflow-gpu  2 0 0  output  I tensorflow stream executor platform default dso loader cc 44  Successfully opened dynamic library cudart64 100 dll  which was the solution for me

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To install the prerequisites for GPU support in TensorFlow 2 1    Install your latest GPU drivers  Install CUDA 10 1    If the CUDA installer reports  you are installing an older driver version   you may wish to choose a custom installation and deselect some components  Indeed  note that software bundled with CUDA including GeForce Experience  PhysX  a Display Driver  and Visual Studio integration are not required by TensorFlow  Also note that TensorFlow requires a specific version of the CUDA Toolkit unless you build from source  for TensorFlow 2 1 and 2 2  this is currently version 10 1   Install cuDNN    Download cuDNN v7 6 4 for CUDA 10 1  This will require you to sign up to the NVIDIA Developer Program  Unzip to a suitable location and add the bin directory to your PATH   Install tensorflow by pip install tensorflow  You may need to restart your PC

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TensorFlow 2 3 0 works fine with CUDA 11  But you have to install tf-nightly-gpu  after you installed tensorflow and CUDA 11   https   pypi org project tf-nightly-gpu  Try  pip install tf-nightly-gpu  Afterwards you ll get the message in your console  I tensorflow stream executor platform default dso loader cc 48  Successfully opened dynamic library cudart64 110 dll

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I installed cudatoolkit 11 and copy dll C  Program Files NVIDIA GPU Computing Toolkit CUDA v11 1 bin to C  Windows System32  It fixed for PyCharm but not for Anaconda jupyter    name   quot  device CPU 0 quot  device type   quot CPU quot  memory limit  268435456 locality     incarnation  6812190123916921346   name   quot  device GPU 0 quot  device type   quot GPU quot  memory limit  13429637120 locality     bus id  1 links         incarnation  18025633343883307728 physical device desc   quot device  0  name  Quadro P5000  pci bus id  0000 02 00 0  compute capability  6 1 quot

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I solved this another way  First of all I installed cuda 10 1 toolkit from this link  Where i selected installer type exe local   and installed 10 1 in custom mode means  without visual studio integration  NVIDIA PhysX because previously I installed CUDA 10 2 so required dependencies were installed automatically    After installation  From the Following Path  C  Program Files NVIDIA GPU Computing Toolkit CUDA v10 1 bin    in my case  I copied   cudart64 101 dll  file and pasted in   C  Program Files NVIDIA GPU Computing Toolkit CUDA v10 2 bin    Then importing Tensorflow worked smoothly   N B  Sorry for Bad English

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Was able to fix the issue by updating NVIDIA device drivers to the latest  v446 14   NVIDIA drivers download link here

[python] Could not load dynamic library 'cudart64_101.dll' on tensorflow CPU-only installation

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