How should I practice Incremental Hard Attention with a KV Cache?

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Incremental Hard Attention with a KV Cache

OpenAI● MediumFULLTIMEPHONE SCREEN

Problem statement

Implement a deterministic incremental attention adapter. The input contains n token embeddings and n position embeddings, each of dimension d, plus square key and value weight matrices.

At step t:

The problem statement continues

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Examples

Example 1

tokenEmbeddings = [[1,0],[1,1]]positionEmbeddings = [[0,0],[0,0]]keyWeights = [[1,0],[0,1]]valueWeights = [[0,1],[1,0]]return = [[0,1],[1,1]]

At each step, the newest key has the unique highest score. Values come from the separate value projection, not from the attention output.

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