keras-team/keras · error · NotImplementedError

Argument synchronized=True is not supported with JAX.

Error message

Argument synchronized=True is not supported with JAX.

What it means

Error "Argument synchronized=True is not supported with JAX." thrown in keras-team/keras.

Source

Thrown at keras/src/backend/jax/nn.py:1043

            "Arguments `target` and `output` must have the same shape. "
            "Received: "
            f"target.shape={target.shape}, output.shape={output.shape}"
        )

    if from_logits:
        log_logits = jax.nn.log_sigmoid(output)
        log_neg_logits = jax.nn.log_sigmoid(-output)
        return -1.0 * target * log_logits - (1.0 - target) * log_neg_logits

    output = jnp.clip(output, backend.epsilon(), 1.0 - backend.epsilon())
    bce = target * jnp.log(output)
    bce += (1.0 - target) * jnp.log(1.0 - output)
    return -bce


def moments(x, axes, keepdims=False, synchronized=False):
    if synchronized:
        raise NotImplementedError(
            "Argument synchronized=True is not supported with JAX."
        )
    # The dynamic range of float16 is too limited for statistics. As a
    # workaround, we simply perform the operations on float32 and convert back
    # to float16
    need_cast = False
    ori_dtype = backend.standardize_dtype(x.dtype)
    if ori_dtype in ("float16", "bfloat16"):
        need_cast = True
        x = cast(x, "float32")

    mean = jnp.mean(x, axes, keepdims=True)
    variance = jnp.var(x, axis=axes, keepdims=True)

    if not keepdims:
        mean = jnp.squeeze(mean, axes)
        variance = jnp.squeeze(variance, axes)
    if need_cast:

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/backend/jax/nn.py:1043 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/ca4143d17c23e331. Report an issue: GitHub.