+ // The training settings, shown as the run area's MAIN content before a run starts
+ // (settings are set once, up front); once training starts the run view (progress +
+ // charts) replaces them. Laid out as a wide grid for the center column.
+ const trainingSettings = (
+
+
{numberField("Steps", steps, setSteps, 1)}
{numberField("LoRA rank", rank, setRank, 1)}
{numberField("Resolution", resolution, setResolution, 512, { min: 64, step: 64 })}
@@ -664,111 +660,117 @@ export function DiffusionTrainPanel({
{numberField("Grad accumulation", gradAccum, setGradAccum, 1)}
{numberField("Seed", seed, setSeed, 42, { min: 0 })}
- {numberField("Learning rate", learningRate, setLearningRate, 0.0001, {
- min: 0,
- step: 0.00001,
- })}
-
-
-
- {lrScheduler !== "constant" &&
- numberField("Warmup steps", lrWarmupSteps, setLrWarmupSteps, 0, { min: 0 })}
-
- How the learning rate evolves over the run (shown live in the LR chart).
-
-
-
-
-
-
-
- Recomputes activations in the backward pass: a large VRAM saving for a modest
- per-step slowdown.
-
-
-
- {isDiT ? (
- <>
-
-
-
-
- How the frozen base weights are quantised. nf4 (4-bit) uses the least VRAM;
- bf16 is fastest but needs the most. Auto picks this family's recommended mode.
-
-
- {supportsCompile && (
-
-
-
-
- torch.compile the transformer. Adds a one-time warmup, then speeds up each step.
-
-
- )}
- >
- ) : (
+
+ {numberField("Learning rate", learningRate, setLearningRate, 0.0001, {
+ min: 0,
+ step: 0.00001,
+ })}
-
+
- Mixed-precision autocast for the U-Net. bf16 suits modern GPUs.
+ How the learning rate evolves over the run (shown live in the LR chart).
- )}
+ {lrScheduler !== "constant" &&
+ numberField("Warmup steps", lrWarmupSteps, setLrWarmupSteps, 0, { min: 0 })}
+
+
+
+
+
+
+
+ Recomputes activations in the backward pass: a large VRAM saving for a modest
+ per-step slowdown.
+
+
+
+ {isDiT ? (
+ <>
+
+
+
+
+ How the frozen base weights are quantised. nf4 (4-bit) uses the least VRAM;
+ bf16 is fastest but needs the most. Auto picks this family's recommended
+ mode.
+
+
+ {supportsCompile && (
+
+
+
+
+ torch.compile the transformer. Adds a one-time warmup, then speeds up each
+ step.
+
+
+ )}
+ >
+ ) : (
+
+
+
+
+ Mixed-precision autocast for the U-Net. bf16 suits modern GPUs.
+
+
+ )}
+
);
@@ -978,18 +980,6 @@ export function DiffusionTrainPanel({
/>