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See how it worksAttention Is All You Need
Vaswani, Shazeer, Parmar et al. · 2017 · p. 4
An attention function can be described as mapping a query and a set of key-value pairs to an output, where the query, keys, values, and output are all vectors. The output is computed as a weighted sum of the values, where the weight assigned to each value is computed by a compatibility function of the query with the corresponding key.
We call our particular attention “Scaled Dot-Product Attention”. The input consists of queries and keys of dimension dk, and values of dimension dv. We compute the dot products of the query with all keys, divide each by √dk, and apply a softmax function to obtain the weights on the values.
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How is the attention output computed?
The attention output is a weighted sum of the value vectors; each weight comes from a compatibility function between the query and the matching key Vaswani 2017 · p. 4, and in the scaled dot-product form that function is a softmax over the dot products divided by √dk p. 4.
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Attention Is All You Need
Vaswani et al. · 2017 · p. 4 of 15
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Big Bird: Transformers for Longer SequencesZaheer et al. · 2020 · Missing PDF
Efficient Transformers: A SurveyTay et al. · 2022 · Slides · 126 pages
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