loop pseudocode: pseudopy style (← assignment, ── divider, t̂)

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
This commit is contained in:
wassname
2026-06-02 12:51:15 +08:00
parent 90b11214f8
commit b6fad64930
+10 -9
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@@ -46,19 +46,20 @@ Consult as reference, from inside this loop, never as a first move: triage tree
The same loop in pseudocode (for humans and agents to hold in one glance):
```py
# ── ML debugging loop ────────────────────────
def debug(symptom):
clues = collect(traceback, logs, static_analysis, cheap_diagnostics) # look before theorizing
H = generate(clues, lenses=5) | {likely, subtle, null} # ≥3 genuinely different
prior = anchor(H) # base rates: data .40 loss .20 train .15 arch .10 hp .05
clues collect(traceback, logs, static_analysis, cheap_diagnostics) # look before theorizing
H generate(clues, lenses=5) | {likely, subtle, null} # ≥3 genuinely different
prior anchor(H) # base rates: data .40 loss .20 train .15 arch .10 hp .05
while not localized:
# pick the test by evidence-per-cost, not by thoroughness
test = argmax(divergence(predict(h, t) for h in H) / cost(t) for t in candidates)
obs = run(test) # one log line or toy run; record obs separately from inference
prior = update(prior, obs) # a clue that points elsewhere overrides the prior outright
H = bisect_path(H, obs) # forward values + backward grads, halve the search each probe
# pick the test by evidence-per-cost, not thoroughness
t̂ argmax(divergence(predict(h, t) for h in H) / cost(t) for t in candidates)
obs run(t̂) # one log line or toy run; keep obs apart from inference
prior update(prior, obs) # a clue elsewhere overrides the prior outright
H bisect_path(H, obs) # forward values + backward grads, halve the search each probe
if cycles 2:
return read_working_code() # diff your math + graph against a trusted impl
return read_working_code() # diff your math + graph vs a trusted impl
fix(root_cause); assert reproduces(obs) # no silent fallback; crash if it doesn't
```