Commands on local system
nvidia-smi -l <n seconds>
Understanding Randomization in TF Datasets (including TFRecords) https://colab.research.google.com/github/christianmerkwirth/colabs/blob/master/Understanding_Randomization_in_TF_Datasets.ipynb
How to apply transfer learning and fine-tuning. https://www.tensorflow.org/guide/keras/transfer_learning
Newer NVIDA GPUs like the GeForce RTX 3090
require CUDA 11
.
TensorFlow provides pre-built Docker images on dockerhub - tensorflow/tensorflow. The underlying Docker files are availble in the TensorFlow GitHub repository.
Currently latest TF version is 2.7
. In table gives an overview of CUDA version used within the pre-built Docker images for the specified TF versions. Versions were retrieved from the TensorFlow GitHub repository (date 2022-01-10).
NOTICE: This guide will help you set ssh keys for GitHub and GitLab. However, this is not going to change your commit
user.name
oruser.email
. If you need to change those for specific repositories, just run the following commands while in your repository:
git config user.name "Your Name Here"
git config user.email your@email.com
For more info, see this answer. Also, keep in mind this only changes the
.git
folder inside your repository which never gets added/committed/pushed/uploaded.
I recently had to manage two ssh keys (one for Github and one for Gitlab). I did some research to find the best solution. I am justing putting the pieces together here.