Could not load dynamic library ‘cudart64_110.dll‘的解决方法

Could not load dynamic library 'cudart64_110.dll’的解决方法

问题本质就是GPU调用问题

tensorflow要调用GPU对程序进行训练, 但是并没有找到相应的驱动文件

How do I fix it?

First - 之前没有安装cuda

To install the prerequisites for GPU support in TensorFlow 2.1:

1. Install your latest GPU drivers.
2. 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.
3. Install cuDNN.
   1. Download cuDNN v7.6.4 for CUDA 10.1. This will require you to sign up to the NVIDIA Developer Program.
   2. Unzip to a suitable location and add the bin directory to your PATH.
4. Install tensorflow by pip install tensorflow.
5. You may need to restart your PC.

second - 安装了cuda-缺少了dll文件

In a conda environment, this is what solved my problem (I was missing cudart64-100.dll:

1. Downloaded it from dll-files.com/CUDART64_100.DLL
2. Put it in my conda environment at C:\Users\\Anaconda3\envs\\Library\bin

check if it’s working:

That’s all it took! You can double check if it’s working:

py import tensorflow as tf tf.config.experimental.list_physical_devices('GPU')