optimizations. Setting the variable to 0 or unsetting it will
            disable the optimizations.
        *   These optimizations can yield slightly different numerical results
            from when they are off due to floating-point round-off errors from
            different computation approaches and orders.
        *   To verify that the optimizations are on, look for a message with

* ♻ Remove `media_type` from `ORJSONResponse` as it's inherited from the parent class. PR [#5805](https://github.com/tiangolo/fastapi/pull/5805) by [@Kludex](https://github.com/Kludex).
* ♻ Instantiate `HTTPException` only when needed, optimization refactor. PR [#5356](https://github.com/tiangolo/fastapi/pull/5356) by [@pawamoy](https://github.com/pawamoy).

### Docs

:= 1; i < len(table); i++ { table[i].montgomeryMul(table[i-1], table[0], m) } out.resetFor(m) out.limbs[0] = 1 out.montgomeryRepresenta(m) tmp := NewNat().ExpandFor(m) for _, b := range e { for _, j := range []int{4, 0} { // Square four times. Optimization note: this can be implemented // more efficiently than with generic Montgomery multiplication. out.montgomeryMul(out, out, m) out.montgomeryMul(out, out, m) out.montgomeryMul(out, out, m) out.montgomeryMul(out, out, m) // Select x^k in constant...

:= 1; i < len(table); i++ { table[i].montgomeryMul(table[i-1], table[0], m) } out.resetFor(m) out.limbs[0] = 1 out.montgomeryRepresenta(m) tmp := NewNat().ExpandFor(m) for _, b := range e { for _, j := range []int{4, 0} { // Square four times. Optimization note: this can be implemented // more efficiently than with generic Montgomery multiplication. out.montgomeryMul(out, out, m) out.montgomeryMul(out, out, m) out.montgomeryMul(out, out, m) out.montgomeryMul(out, out, m) // Select x^k in constant...