Could Not Load Dynamic Library ‘cudart64_101.dll’ On Tensorflow CPU-only Installation

If you are encountering the error message "Could not load dynamic library ‘cudart64_101.dll’" in a TensorFlow installation that is CPU-only, it means that the CUDA-related libraries are not required but still being referenced.

To resolve this issue, you have a couple of options:

  1. Install the GPU version of TensorFlow: If you have a compatible NVIDIA GPU and CUDA toolkit installed, you can install the GPU version of TensorFlow to take advantage of GPU acceleration. This will require the ‘cudart64_101.dll’ library that is currently missing. Make sure your GPU is compatible and that you have CUDA installed correctly.

  2. Remove the CUDA references: If you don’t have a compatible GPU or don’t want to use GPU acceleration, you can remove the CUDA references from your TensorFlow installation. Run the following commands in your Python environment:

import os
os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
import tensorflow as tf

By setting the CUDA_VISIBLE_DEVICES environment variable to -1, TensorFlow will ignore any available GPUs and continue with the CPU-only installation.

By applying the above solutions, you should be able to run TensorFlow on CPU-only mode without encountering the ‘cudart64_101.dll’ error.

About the Author Rex

I'm a passionate tech blogger with an insatiable love for programming! From my early days tinkering with code, I've delved into web dev, mobile apps, and AI. Sharing insights and tutorials with the world is my joy, connecting me to a global community of like-minded tech enthusiasts. Python holds a special place in my heart, but I embrace all challenges. Constantly learning, I attend tech conferences, contribute to open-source projects, and engage in code review sessions. My ultimate goal is to inspire the next generation of developers and contribute positively to the ever-evolving tech landscape. Let's code together!