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Implement a KV Cache for Transformer Inference is a medium coding interview question covering deep learning, design, arrays — the kind asked at FAANG (Facebook/Meta, Apple, Amazon, Netflix, Google) and AI-first companies like Anthropic, OpenAI, and Nvidia.
Implement the key-value cache used in autoregressive transformer inference: store attention keys and values for past tokens per layer, append the newest token's K/V each step, and compute attention for the new token against the cached history. Explain the complexity win.
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