replace grader-folk words with the precise term

knob -> hyperparameter, gate -> threshold, rung -> defined level, clean log ->
error-free log, ship the rubric -> put the rubric. Quoted source text (Irpan's
canary, Domingos' knobs) and wassname's own lines are untouched.

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
This commit is contained in:
wassname
2026-09-01 05:46:15 +08:00
co-authored by Claudypoo
parent e4ae445108
commit 6106575e9c
4 changed files with 18 additions and 18 deletions
+1 -1
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@@ -51,7 +51,7 @@ For RL, add reward scale/sign as a top-3 issue, and episode-boundary handling (d
A catalog of small, well-worn checks, in rough dependency order (each assumes the one before). Pull from it; don't run it end-to-end as a ritual.
**Step 1: Verify components in isolation.**[^goodfellow][^cs229] Most bugs are "doing the wrong calculation." Test each piece independently.
- Forward pass: feed known inputs, check output shapes and ranges. `assert` shapes everywhere, since `(None,)` vs `(None, 1)` silently broadcasts into `(None, None)`. (Or make the shapes runtime-checked contracts with jaxtyping[^jaxtyping] + beartype, which turns the #1 silent bug loud.)
- Forward pass: feed known inputs, check output shapes and ranges. `assert` shapes everywhere, since `(None,)` vs `(None, 1)` silently broadcasts into `(None, None)`. (Or make the shapes runtime-checked annotations with jaxtyping[^jaxtyping] + beartype, which turns the #1 silent bug loud.)
- Loss: hand-compute a few targets and compare to code output.
- Data pipeline: sample a batch, print it, eyeball it. Are labels aligned with inputs? Transforms applied correctly?
- Preprocessing: look at processed inputs as a human. Can *you* solve the task from them?