Software⏱️ 3 min read📅 2026-06-11

How to Fix: Tensorflow gpu was working but is not working anymore error- Failed to get convolution algorithm. This is probably because cuDNN failed to initialize

Tensorflow gpu issue with cuDNN initialization

Quick Answer: Check for any recent updates or changes to your TensorFlow or Keras installation, and try reinstalling cuDNN or updating your CUDA version.

📋 Table of Contents

  1. ⚠️ Common Causes
  2. 🚀 How to Resolve This Issue
  3. 💡 Conclusion

TensorFlow GPU error: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize. The issue affects users who have installed TensorFlow GPU version 1.13.1 and CUDA version 10, specifically after importing a VGG16 model.

This error can be frustrating as it prevents the user from running any models in Keras. However, with the right steps, you can resolve this issue and get your TensorFlow GPU working again.

⚠️ Common Causes

  • The primary reason for this error is that cuDNN failed to initialize due to a mismatch between the CUDA version installed on the system and the one required by TensorFlow. This can occur when upgrading or reinstalling TensorFlow, resulting in an incompatible CUDA version.
  • Another possible cause is a corrupted or incomplete installation of TensorFlow GPU or CUDA, which may lead to issues with cuDNN initialization.

🚀 How to Resolve This Issue

Update CUDA Version and Reinstall TensorFlow

  1. Step 1: Step 1: Update the CUDA version on your system to the latest version compatible with TensorFlow 1.13.1. You can check for updates in the NVIDIA Control Panel or by running the command `nvcc --version` in your terminal.
  2. Step 2: Step 2: Reinstall TensorFlow GPU using pip: `pip uninstall tensorflow-gpu` followed by `pip install tensorflow-gpu --force-reinstall`. This will ensure that you have the latest version of cuDNN included with the installation.
  3. Step 3: Step 3: Verify that CUDA version 10 is installed and compatible with TensorFlow 1.13.1 by running the command `nvcc --version` in your terminal.

Update cuDNN Version

  1. Step 1: Step 1: Update the cuDNN version on your system to the latest version compatible with TensorFlow 1.13.1. You can check for updates using the official NVIDIA website or by running the command `nvcc --version` in your terminal.
  2. Step 2: Step 2: Download and install the updated cuDNN library from the official NVIDIA website or through pip: `pip install tensorflow-gpu cudnn7`.

💡 Conclusion

To resolve the 'Failed to get convolution algorithm. This is probably because cuDNN failed to initialize' error in TensorFlow GPU, update your CUDA version and reinstall TensorFlow, or update cuDNN version. By following these steps, you should be able to resolve the issue and get your TensorFlow GPU working again.

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