Align LR-schedule copy with the diffusion two-card chart layout
DiffusionCharts deliberately renders only Training Loss + Gradient Norm (the LR curve is the deterministic schedule the user picked), but the settings copy and two comments still promised a live LR chart. Reword them so the UI no longer references a chart that was intentionally dropped.
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1 changed files with 3 additions and 3 deletions
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@ -153,7 +153,7 @@ function mergeFamilies(reported?: DiffusionTrainableFamily[]): FamilyPreset[] {
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}
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// A full-page training workspace: left = configure (family, dataset, labeling, settings),
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// right = live run (progress, loss/LR charts, completion + deploy). Kept mounted with the
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// right = live run (progress, loss/grad-norm charts, completion + deploy). Kept mounted with the
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// page so a long run survives Create/Train tab switches; polling is gated on `active`.
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export function DiffusionTrainPanel({
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active,
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@ -235,7 +235,7 @@ export function DiffusionTrainPanel({
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const [batchSize, setBatchSize] = useState(1);
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const [gradAccum, setGradAccum] = useState(1);
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const [seed, setSeed] = useState(42);
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// LR schedule (PR E wired get_scheduler into the loop, so the LR chart reflects this).
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// LR schedule (PR E wired get_scheduler into the loop, so the LR follows the chosen curve).
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// Warmup only applies to the non-constant schedules; plain "constant" ignores it.
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const [lrScheduler, setLrScheduler] = useState<
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"constant" | "constant_with_warmup" | "cosine" | "linear"
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@ -842,7 +842,7 @@ export function DiffusionTrainPanel({
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<option value="linear">Linear decay</option>
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</select>
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<p className="text-[11px] leading-snug text-muted-foreground">
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How the learning rate evolves over the run (shown live in the LR chart).
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How the learning rate evolves over the run.
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</p>
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</div>
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{lrScheduler !== "constant" &&
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