32 lines
1.5 KiB
JSON
32 lines
1.5 KiB
JSON
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{
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"$schema": "https://json-schema.org/draft/2020-12/schema",
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"$id": "https://memlnaut/schemas/ml_defaults.schema.json",
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"title": "MEMLNaut ML Training Defaults",
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"description": "Single, global declaration of the MLP training-hyperparameter defaults (learning rate, max iterations, min-error/convergence threshold) — ONE value per field, shared by every mode on every platform (firmware, WASM/manifold, VCV). This is only the DEFAULT: codegen/generate.ts emits it to nisps/modes/generated/ml_defaults.hpp (C++) and manifold/src/modes/generated/ml_defaults.ts (TS), and nisps::ml::MLPCore::set_train_config()/train_config() (nisps/ml/mlp.hpp) makes it overridable at runtime on every target. Per-mode ml.default_spread stays separate — it is genuinely per-mode-tuned, unlike these.",
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"type": "object",
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"required": ["learning_rate", "max_iterations", "min_error"],
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"additionalProperties": false,
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"properties": {
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"$schema": { "type": "string" },
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"_note": {
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"type": "string",
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"description": "Free-text provenance note from the schema author."
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},
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"learning_rate": {
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"type": "number",
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"exclusiveMinimum": 0.0,
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"description": "SGD learning rate the no-arg train() falls back to."
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},
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"max_iterations": {
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"type": "integer",
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"minimum": 1,
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"description": "Epoch cap for the no-arg train() fallback."
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},
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"min_error": {
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"type": "number",
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"minimum": 0.0,
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"description": "Early-stop threshold: training stops once epoch loss drops below this value."
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}
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}
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}
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