tensorflow gpu_error ai_generated true

tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize

ID: tensorflow/failed-to-get-convolution-algorithm

Also available as: JSON · Markdown

82%Fix Rate

88%Confidence

3Evidence

2023-01-01First Seen

Version Compatibility

Version	Status	Introduced	Deprecated	Notes
2	active	—	—	—

cuDNN cannot select a convolution algorithm. Usually a cuDNN/CUDA version mismatch or GPU memory already exhausted.

generic

90% success Enable GPU memory growth to prevent cuDNN OOM during init
```
tf.config.experimental.set_memory_growth(tf.config.list_physical_devices('GPU')[0], True)
```
Sources: https://www.tensorflow.org/guide/gpu

88% success Install matching cuDNN version for your CUDA/TF combination

TF 2.15 requires CUDA 12.2 + cuDNN 8.9. Check tensorflow.org/install/source#gpu

85% success Use pip install tensorflow[and-cuda] for bundled compatible libraries
```
pip install tensorflow[and-cuda]  # auto-installs matching CUDA/cuDNN
```

Common approaches that don't work:

Downgrade cuDNN to an older version blindly 80% fail
cuDNN must match CUDA and TF versions exactly. Arbitrary downgrades cause ABI incompatibilities.
Set TF_CUDNN_USE_AUTOTUNE=0 to skip algorithm selection 75% fail
Disabling autotuning avoids the error but makes convolutions extremely slow (10-50x slower).