def softplus(x):
    """Softplus activation function.

    It is defined as `f(x) = log(exp(x) + 1)`, where `log` is the natural
    logarithm and `exp` is the exponential function.

    Args:
        x: Input tensor.

    Returns:
        A tensor with the same shape as `x`.

    Example:

    >>> x = keras.ops.convert_to_tensor([-0.555, 0.0, 0.555])
    >>> keras.ops.softplus(x)
    array([0.45366603, 0.6931472, 1.008666], dtype=float32)

    """
    if any_symbolic_tensors((x,)):
        return Softplus().symbolic_call(x)
    return backend.nn.softplus(x)
Softplus activation function.

    It is defined as `f(x) = log(exp(x) + 1)`, where `log` is the natural
    logarithm and `exp` is the exponential function.

    Args:
        x: Input tensor.

    Returns:
        A tensor with the same shape as `x`.

    Example:

    >>> x = keras.ops.convert_to_tensor([-0.555, 0.0, 0.555])
    >>> keras.ops.softplus(x)
    array([0.45366603, 0.6931472, 1.008666], dtype=float32)

    
keras/src/ops/nn.py