keras-team/keras · error · ValueError

Unsupported value `sparse=True` with numpy backend

Error message

Unsupported value `sparse=True` with numpy backend

What it means

Error "Unsupported value `sparse=True` with numpy backend" thrown in keras-team/keras.

Source

Thrown at keras/src/backend/numpy/numpy.py:365

    x2 = convert_to_tensor(x2)

    dtype = dtypes.result_type(x1.dtype, x2.dtype)
    if dtype in ["int8", "int16", "int32", "uint8", "uint16", "uint32"]:
        dtype = config.floatx()
    elif dtype in ["int64"]:
        dtype = "float64"

    return np.heaviside(x1, x2).astype(dtype)


def kaiser(x, beta):
    x = convert_to_tensor(x)
    return np.kaiser(x, beta).astype(config.floatx())


def bincount(x, weights=None, minlength=0, sparse=False):
    if sparse:
        raise ValueError("Unsupported value `sparse=True` with numpy backend")
    x = convert_to_tensor(x)
    dtypes_to_resolve = [x.dtype]
    if weights is not None:
        weights = convert_to_tensor(weights)
        dtypes_to_resolve.append(weights.dtype)
        dtype = dtypes.result_type(*dtypes_to_resolve)
    else:
        dtype = "int32"
    if len(x.shape) == 2:
        if weights is None:

            def bincount_fn(arr):
                return np.bincount(arr, minlength=minlength)

            bincounts = list(map(bincount_fn, x))
        else:

            def bincount_fn(arr_w):

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/backend/numpy/numpy.py:365 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/db8ac1daf8bbf8c4. Report an issue: GitHub.