keras-team/keras · error · ValueError

Internal Type Promotion error: {nodes} do not have a unique

Error message

Internal Type Promotion error: {nodes} do not have a unique least upper bound on the specified lattice; options are {LUB}. This is an unexpected error in Keras's internal logic; please report it to the maintainers.

What it means

Error "Internal Type Promotion error: {nodes} do not have a unique least upper bound on the specified lattice; options are {LUB}. This is an unexpected error in Keras's internal logic; please report it to the maintainers." thrown in keras-team/keras.

Source

Thrown at keras/src/backend/common/dtypes.py:167

    except KeyError:
        dtype = next(n for n in N if n not in UB)
        raise ValueError(
            f"{dtype=} is not a valid dtype for Keras type promotion."
        )
    CUB = set.intersection(*bounds)
    LUB = (CUB & N) or {c for c in CUB if CUB.issubset(UB[c])}
    if len(LUB) == 1:
        return LUB.pop()
    elif len(LUB) == 0:
        msg = (
            f"Input dtypes {tuple(str(n) for n in nodes)} have no available "
            "implicit dtype promotion path. Try explicitly casting inputs to "
            "the desired output type."
        )
        raise ValueError(msg)
    else:
        # If we get here, it means the lattice is ill-formed.
        raise ValueError(
            f"Internal Type Promotion error: {nodes} do not have a unique "
            f"least upper bound on the specified lattice; options are {LUB}. "
            "This is an unexpected error in Keras's internal logic; "
            "please report it to the maintainers."
        )


def _dtype_and_weaktype(value):
    """Return a (dtype, weak_type) tuple for the given input."""
    is_weak_type = False
    if value is int or value is float:
        # Note that we can't use `value in [int, float]` because the dtype
        # might be equal to python scalar types.
        # e.g, tf.float32 == float is True
        is_weak_type = True
    return standardize_dtype(value), is_weak_type

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/backend/common/dtypes.py:167 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25). Data as JSON: /api/errors/c7f09ed3b1bc1dcc. Report an issue: GitHub.