INNER CODE UNIT · Python

cmd_train

initial-d/ml-quant-trading · src/mlquant/cli/main.py:255

def cmd_train(config_path: str) -> None:
    cfg = load_config(config_path)
    seed_everything(cfg.get("seed", 42))
    art = _artifacts_dir(cfg)
    panel = _load_panel(art)
    feat_blob  = torch.load(art / "features.pt", weights_only=False)
    fwd_ret, _ = target_01(panel)

    # Train only on dates before the out-of-sample window. Slicing to
    # ``oos + 1`` keeps the label of the last training day (close at ``oos``),
    # which is already known when the first out-of-sample signal is formed.
    T = fwd_ret.shape[0]
    oos = _oos_start(cfg, T)
    ds = FactorDataset(
        factors=feat_blob["factors"][: oos + 1],
        mask=feat_blob["mask"][: oos + 1],
        forward_returns=fwd_ret[: oos + 1],
    )

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