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FA-99116 / Learning rate schedules / Open access

Linear decay ignores the configured minimum rate · case 01

Linear decay ignores the configured minimum rate.

Verified by executionVariant 1 · 6 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The decay formula is hard-coded to approach zero instead of the configured floor.

THE FAILURE

The decay formula is hard-coded to approach zero instead of the configured floor.

Unsuccessful approach: Applying the floor only before the endpoint still returns zero at the endpoint.

Case contract

Linearly decay from base to floor across total steps and clamp at both endpoints.

Why this case matters

A deterministic scalar schedule makes step-to-rate mapping explicit for a small training loop.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(step, base, floor, total):
    return base*max(0,1-step/total)
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('start',solve(0,10,2,4),10); check('quarter',solve(1,10,2,4),7.5); check('mid',solve(2,10,2,4),5); check('floor',solve(4,10,2,4),2); check('after',solve(6,10,2,4),2); check('equal floor',solve(0,3,3,4),3)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
start10.010Passed
quarter7.57.5Passed
mid5.05Passed
floor02Failed
after02Failed
equal floor3.03Passed

SHA-256 / 7d6ead06558665dc1087be7b98c2774e9cd266099759d41ee431ec2815fdf35a

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(step, base, floor, total):
    return max(floor,base*(1-step/total)) if step<total else 0
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('start',solve(0,10,2,4),10); check('quarter',solve(1,10,2,4),7.5); check('mid',solve(2,10,2,4),5); check('floor',solve(4,10,2,4),2); check('after',solve(6,10,2,4),2); check('equal floor',solve(0,3,3,4),3)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
start10.010Passed
quarter7.57.5Passed
mid5.05Passed
floor02Failed
after02Failed
equal floor33Passed

SHA-256 / 5d3a82374d5c7b1fea7e07a912ca57fcf8fcf412ae7aa81df2281d312afc2acd

HELD IN THE MEMBER ARCHIVE

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This mechanism has 6 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

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Verification & scope

These are toy scalar contracts with integer steps and finite parameters; they do not model framework defaults or optimizer state. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.

Observations recorded using Python 3.12.14 at 2026-09-30T16:48:20.350830+00:00.

Case digest / 67c45ee72902799bfc72dd565944965a33ee338350f260a5ff6615ad17d40daa