giant/configs/default.toml at feat/router-learnable-width - giant - Gitea: Git with a cup of tea

lars/giant

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lars 9277d79dff Implement Phase 1: full data pipeline, model, training, and config support

- Data pipeline: loader (parquet→numpy), transforms (log, local-frame
  Rodrigues rotation, Normalizer), StepsDataset with event-ID-based split
- Model: SinusoidalEmbedding, ConditionEncoder, ResBlock, DenoisingMLP
- Schedule: cosine DDPM and conditional flow matching loss (Lipman 2022)
- Samplers: flow (Euler ODE), DDPM ancestral, DDIM deterministic
- Training loop: AdamW + cosine LR, grad clipping, best-val checkpoint
- Validation: per-dimension marginal summary (normalised space)
- CLI: TOML config support with CLI-overrides; hyperparam-encoded output
  directory; config.toml with git hash saved into each run's checkpoint dir
- 21 unit tests covering transforms, network, flow/DDPM losses, dataset splits

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-06-17 10:48:03 +02:00

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 # git: c3bf3abebfe29a10fe42b9cbafbb3460ab78d243
 [train]
 mode         = "flow"
 epochs       = 100
 batch_size   = 4096
 lr           = 3e-4
 val_fraction = 0.1
 num_workers  = 4
 [model]
 hidden_dim = 256
 n_blocks   = 6
 emb_dim    = 16