[docs] Format fix (#38414)
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fix table
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Steven Liu 2025-06-03 09:53:23 -07:00 committed by GitHub
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@ -56,10 +56,10 @@ Attention is calculated independently in each layer of the model, and caching is
Refer to the table below to compare how caching improves efficiency.
| without caching | with caching | | | |
|---|---|---|---|---|
| for each step, recompute all previous `K` and `V` | for each step, only compute current `K` and `V` | | | |
| attention cost per step is **quadratic** with sequence length | attention cost per step is **linear** with sequence length (memory grows linearly, but compute/token remains low) | | | |
| without caching | with caching |
|---|---|
| for each step, recompute all previous `K` and `V` | for each step, only compute current `K` and `V`
| attention cost per step is **quadratic** with sequence length | attention cost per step is **linear** with sequence length (memory grows linearly, but compute/token remains low) |