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Tensorflow 2

Performance of PyTorch vs. Keras 3 with tensorflow/torch backends for a small NN-model on a Nvidia 4060 TI – I – Torch vs. Keras3/TF2 and relevant parameters

Today’s world of Machine Learning is characterized by competing frameworks. I am used to the combination of Keras with the Tensorflow2 [TF2] backend, but have turned now to using PyTorch in addition. As a beginner with PyTorch, I wanted to get an impression about potential performance advantages in comparison with the Keras/TF2 framework combination. I had read about significant performance… Read More »Performance of PyTorch vs. Keras 3 with tensorflow/torch backends for a small NN-model on a Nvidia 4060 TI – I – Torch vs. Keras3/TF2 and relevant parameters

Two CUDA/cudnn versions with Pytorch and Tensorflow in one virtual Python environment

One of the problems I recently ran into was the coexistence of Tensorflow2 [TF2] and PyTorch in the very same virtual Python environment. I just wanted to make experiments to compare the performance of some Keras-based models with the TF2-backend on one side and, on the other side, with the PyTorch-backend. My trouble resulted from a mismatch of two CUDA/cudnn… Read More »Two CUDA/cudnn versions with Pytorch and Tensorflow in one virtual Python environment

Installation of CUDA 12.3 and CuDNN 8.9 on Opensuse Leap 15.5 for Machine Learning

Machine Learning on a Linux system is no fun without a GPU and its parallel processing capabilities. On a system with a Nvidia card you need basic Nvidia drivers and additional libraries for optimal support of Deep Neural Networks and Linear Algebra operations on the GPU sub-processors. E.g., Keras and Tensorflow 2 [TF2] use CUDA and cuDNN-libraries on your Nvidia… Read More »Installation of CUDA 12.3 and CuDNN 8.9 on Opensuse Leap 15.5 for Machine Learning