ReLU vs. Softmax in Vision Transformers: Does Sequence Length Matter? Insights from a Google DeepMind Research Paper

A common machine learning architecture today is the transformer architecture. One of the main parts of the transformer, attention, has a softmax that generates a probability distribution across tokens. Parallelization is difficult with Softmax since it is expensive owing to an exponent calculation and a sum over the length of the sequence. In this study, […]

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