keras-team/keras · error · ValueError

Repeated axis in `axis`: {canonical_axis}

Error message

Repeated axis in `axis`: {canonical_axis}

What it means

Error "Repeated axis in `axis`: {canonical_axis}" thrown in keras-team/keras.

Source

Thrown at keras/src/backend/jax/sparse.py:53

    result_dims = len(input_shape)
    if insert_dims:
        result_dims += len(axis)

    # Resolve negative values.
    canonical_axis = []
    for a in axis:
        if not -result_dims <= a < result_dims:
            raise ValueError(
                f"In `axis`, axis {a} is out of bounds for array "
                f"of dimension {result_dims}"
            )
        if a < 0:
            a = a + result_dims
        canonical_axis.append(a)

    # Check uniqueness again after resolving negative values.
    if len(set(canonical_axis)) != len(canonical_axis):
        raise ValueError(f"Repeated axis in `axis`: {canonical_axis}")
    canonical_axis = sorted(canonical_axis)

    # Compute output shape.
    output_shape = list(input_shape)
    for i in canonical_axis:
        if insert_dims:
            output_shape.insert(i, 1)
        else:
            output_shape[i] = 1
    broadcast_dims = [i for i in range(result_dims) if i not in canonical_axis]
    return canonical_axis, output_shape, broadcast_dims


def bcoo_add_indices(x1, x2, sum_duplicates):
    """Add the indices of `x2` to `x1` with zero values.

    Args:
        x1: `BCOO` tensor to add indices to.

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/backend/jax/sparse.py:53 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/b1cc634851f07033. Report an issue: GitHub.