keras-team/keras · error · ValueError

Array inputs to associative_scan must have the same first di

Error message

Array inputs to associative_scan must have the same first dimension. (saw: {})

What it means

Error "Array inputs to associative_scan must have the same first dimension. (saw: {})" thrown in keras-team/keras.

Source

Thrown at keras/src/backend/openvino/core.py:1233

    def _unsqueeze(x, axis):
        x_ov = get_ov_output(x)
        const_axis = ov_opset.constant(axis, Type.i32).output(0)
        return OpenVINOKerasTensor(
            ov_opset.unsqueeze(x_ov, const_axis).output(0)
        )

    if reverse:
        elems_flat = [_flip(elem, axis) for elem in elems_flat]

    def _combine(a_flat, b_flat):
        a = tree.pack_sequence_as(elems, a_flat)
        b = tree.pack_sequence_as(elems, b_flat)
        c = f(a, b)
        return tree.flatten(c)

    num_elems = int(elems_flat[0].shape[axis])
    if not all(int(elem.shape[axis]) == num_elems for elem in elems_flat[1:]):
        raise ValueError(
            "Array inputs to associative_scan must have the same "
            "first dimension. (saw: {})".format(
                [elem.shape for elem in elems_flat]
            )
        )

    def _interleave(a, b, axis):
        n_a = a.shape[axis]
        n_b = b.shape[axis]

        a_common = slice_along_axis(a, 0, n_b, axis=axis)
        a_exp = _unsqueeze(a_common, axis + 1)
        b_exp = _unsqueeze(b, axis + 1)
        interleaved = _concat([a_exp, b_exp], axis + 1)

        interleaved_ov = get_ov_output(interleaved)
        orig_shape = ov_opset.shape_of(interleaved_ov, Type.i32).output(0)
        ndim = len(interleaved_ov.get_partial_shape())

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/backend/openvino/core.py:1233 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/67ab9f2b1f51ffec. Report an issue: GitHub.