huggingface/pytorch-image-models · error · ValueError

Coefficient list cannot be empty

Error message

Coefficient list cannot be empty

What it means

Thrown by resolve_ns_coefficients in timm's Muon optimizer when the coefficients argument is a sequence of triples but contains zero items. At least one coefficient triple is required.

Source

Thrown at timm/optim/muon.py:1055

    if not is_seq(value):
        raise TypeError(
            "Coefficients must be a preset name (str), a 3-sequence (a,b,c), "
            "or a sequence of 3-sequences."
        )

    # Decide single triple vs list-of-triples by structure
    if len(value) == 3 and all(is_real(v) for v in value):  # type: ignore[index]
        return [as_coeff(value)]  # single triple -> wrap

    # Otherwise treat as list/tuple of triples
    out = []
    for i, item in enumerate(value):  # type: ignore[assignment]
        if not is_seq(item):
            raise TypeError(f"Item {i} is not a sequence: {item!r}")
        out.append(as_coeff(item))
    if not out:
        raise ValueError("Coefficient list cannot be empty")
    return out

View on GitHub (pinned to 9a5261e31b)

Solutions

1. Ensure the coefficient list has at least one (a,b,c) triple
2. If dynamically generated, add a fallback default triple when the list would be empty

Example fix

# before
coeffs = []  # built dynamically, ended empty
Muon(params, ns_coefficients=coeffs)

# after
coeffs = coeffs or [(0.9, 0.95, 0.5)]
Muon(params, ns_coefficients=coeffs)

assert len(ns_coefficients) > 0, 'coefficient list must not be empty'

When it happens

Trigger: Passing ns_coefficients=[] to timm.optim.Muon/AdamMuon.

Common situations: Programmatically building a per-layer coefficient list that ends up empty (e.g. no layers matched a filter).

Related errors

• Preset '{value}' is empty or invalid
• Coefficients must be a preset name (str), a 3-sequence (a,b,
• Item {i} is not a sequence: {item!r}
• Invalid learning rate: {}
• Invalid learning rate: {lr}

AI-assisted analysis of huggingface/pytorch-image-models@9a5261e31b (2026-08-27). Data as JSON: /api/errors/394c8d289da7d9af. Report an issue: GitHub.