Checks / performance
Very large Linear layer
Check R30. Runs in the editor as you build, in CI through the
GitHub Action, and over the wire at
POST /api/v1/check. Milliseconds, before any GPU is billed.
warn
performance
R30
| Trigger | A single Linear exceeds ~1B parameters (inFeatures × outFeatures). |
|---|---|
| Why | A dense layer that large (~4 GB float32) almost always means a feature map was flattened without pooling first. Add a Global Average Pool / more downsampling, or factorize the layer. Embedding and vocab-projection heads are the expected exception. |
| Source | Parameter-budget hygiene; a single matrix this size dominates model memory. |
Why it is not a lint you can ignore
A structural mistake does not fail at review time and it does not fail at import
time. It fails when the module is constructed on the training node, after the job was queued and
the dataset was downloaded. That is why this runs before the spend and not after it.
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Every check
41 structural checks: 6 guardrail gates and 35 architecture advisor rules. See the full catalogue.
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