PyG or PyTorch Geometric is a deep learning framework for GNNs (graph neural networks). When dealing with graphs, to speed up the computation, we need to do the batch computation, even though the graphs are in different “shapes”. In PyG, it is possible to pack the data in batches. According to the documentation. “Adjacency matricesContinue reading “Deep Learning 20: graph batching in PyTorch Geometric”
Tag Archives: PyTorch
Deep Learning 17: text classification with BERT using PyTorch
Why BERT If you are a big fun of PyTorch and NLP, you must try to use the PyTorch based BERT implementation! If you have your own dataset and want to try the state-of-the-art model, BERT is a good choice. Please check the code from https://github.com/huggingface/pytorch-pretrained-BERT to get a close look. However, in this post,Continue reading “Deep Learning 17: text classification with BERT using PyTorch”
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