code: def softplus(x, scale=1.0, name=None):
    
    if scale == 1:
      return tf.nn.softplus(x)
    else:
      with tf.name_scope(name, 'softplus', [x]):
        scale = tf.convert_to_tensor(scale, dtype=x.dtype.base_dtype)
        return tf.nn.softplus(x * scale) / scale
docs: Computes softplus with a scale factor to sharpen of the hinge.
  
    This is an alternate non-linearity to relu. It has a similar shape, but
    it has a smooth transition from the linear part to 0.
  
    Args:
      x: A tensor.
      scale: A float that sharpens the curve.
      name: Optional name.
    Returns:
      y = log(1 + exp(scale * x)) / scale