Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

Tools for (approximately) visualizing the architures of existing neural networks or for visualizing the traing process (training/validation loss/accuracy, activation, etc.) are extremely helpful! TensorBoard is one of the best …

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

Data Modeling with RDF(S)

Learn OWL and RDFS

RDF: Resource Description Framework OWL: Web Ontology Language

Products

neo4j

RDFox

Unique features of RDFox include the very powerful rule language (roughly …

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

GPU Related Issues and Solutions

Input type (torch.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same

This means that the input data and the model are on different …

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

1. torchvision pretrained models

2. Model Zoo

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

Memory

1. ResNet152 inferencing requies about (a little bit less than) 2G GPU memory and training can be done with 8G GPU memory (need to set a small batch size). Deeper ResNet …

Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!

PyTorch on GPU

https://pytorch.org/docs/master/notes/cuda.html

You can use the command torch.cuda.is_available() to check whether GPU is available for PyTorch. Details of GPUs can …