Tensorflow not running on GPU

To check which devices are available to TensorFlow you can use this and see if the GPU cards are available: from tensorflow.python.client import device_lib print(device_lib.list_local_devices()) Edit Also, you should see this kind of logs if you use TensorFlow Cuda version : I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so.*.* locally I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library … Read more

could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR

In Tensorflow 2.0, my issue was resolved by setting the memory growth. ConfigProto is deprecated in TF 2.0, I used tf.config.experimental. My computer specs are: OS: Ubuntu 18.04 GPU: GeForce RTX 2070 Nvidia Driver: 430.26 Tensorflow: 2.0 Cudnn: 7.6.2 Cuda: 10.0 The code I used was: physical_devices = tf.config.experimental.list_physical_devices(‘GPU’) assert len(physical_devices) > 0, “Not enough … Read more

Which TensorFlow and CUDA version combinations are compatible?

TL;DR) See this table: https://www.tensorflow.org/install/source#gpu Generally: Check the CUDA version: cat /usr/local/cuda/version.txt and cuDNN version: grep CUDNN_MAJOR -A 2 /usr/local/cuda/include/cudnn.h and install a combination as given below in the images or here. The following images and the link provide an overview of the officially supported/tested combinations of CUDA and TensorFlow on Linux, macOS and Windows: … Read more

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