keras/src/constraints/constraints.py/MinMaxNorm/__call__
class MinMaxNorm:    def __call__(self, w):
        w = backend.convert_to_tensor(w)
        norms = ops.sqrt(ops.sum(ops.square(w), axis=self.axis, keepdims=True))
        desired = (
            self.rate * ops.clip(norms, self.min_value, self.max_value)
            + (1 - self.rate) * norms
        )
        return w * (desired / (backend.epsilon() + norms))