tensorflow gpu tests pass--but I don't have cuDNN installed

Question

Windows10-pro, single RTX 2080 Ti. I am new to Tensorflow.

I just installed tensorflow-gpu, version 2.1.0, python 3.7.7. Cuda compilation tools, release 10.1, V10.1.105. Nothing self-compiled. And I have not installed cuDNN, nor have I registered. All installation is standard, nothing self-compiled.

The tensorflow.org documentation states that cuDNN is needed to use the GPU. But my tests for GPU-usage seem to pass. For example, tf.config.experimental.list_physical_devices('GPU') returns [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')].

It may appear that I should just install cuDNN and not lose any more sleep. But I would still want to know if I were using the GPU so I would prefer a test that is capable of failing.

Is there a true test to see if an installation will use the GPU?

Answer 1

In NVIDIA GPU computing toolkit, one can verify the cuDNN installation, On windows system, Go to

C:\Programming Files\NVIDIA GPU computing Toolkit/CUDA\v10.0\include\

open cudnn.h 

To utilize the Tensorflow-GPU successfully, CUDA and cuDNN are required. Some of the Tensorflow library such as tf.keras.layers.GRU(Keras GRU layers) employs the capability of cuDNN.

Check these examples provided in Tensorflow site for GPU utilization.