Скачать или смотреть How to Fix 'cudnn64_8.dll not found' Error in TensorFlow with GPU Setup

Encountering 'cudnn64_8.dll not found' error while setting up TensorFlow with GPU? Learn how to resolve this issue and ensure a smoother installation process.
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If you are setting up TensorFlow with GPU support and come across the error message, "Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found," you're not alone. This commonly occurs due to missing or improperly configured dependencies required for harnessing GPU capabilities in TensorFlow.

Why This Error Occurs?

The cudnn64_8.dll file is a part of NVIDIA's cuDNN library, which is essential for running deep learning frameworks like TensorFlow efficiently using GPU acceleration. TensorFlow relies on this library to provide fast and optimized implementations of several neural network operations.

Step-by-Step Solution

Download and Install cuDNN

Visit the NVIDIA cuDNN download page (you may need an NVIDIA developer account).

Select the version compatible with your CUDA toolkit.

Download and extract the cuDNN library to a directory on your machine.

Add cuDNN to the System Path

Copy the extracted cuDNN files (cudnn64_8.dll, cudnn64_8.lib, etc.) into your CUDA installation directory, often found at C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\vX.X\bin for Windows.

Ensure this directory is added to your system's environment PATH variable:

Open System Properties (Right-click on This PC -> Properties -> Advanced system settings -> Environment Variables).

Find the PATH variable in the System variables section, and click Edit.

Add the path to the cuDNN bin directory, e.g., C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\vX.X\bin.

Verify CUDA and cuDNN Installation

Open a new command prompt and run nvcc --version to check CUDA installation.

TensorFlow should now be able to locate cudnn64_8.dll during runtime.

Additional Tips

Correct Version Matching: Make sure the versions of CUDA and cuDNN match with the version of TensorFlow you are using. TensorFlow's Installation Guide provides guidance on compatible versions.

Check Permissions: Sometimes, the issue may arise due to insufficient permissions. Ensure your user account has the right permissions for the directories where CUDA and cuDNN are installed.

Following these steps should help you resolve the cudnn64_8.dll not found error and get TensorFlow running with GPU support.