* ⬆ Upgrade MkDocs Material and configs. PR [#4385](https://github.com/tiangolo/fastapi/pull/4385) by [@tiangolo](https://github.com/tiangolo).

## 0.70.1

There's nothing interesting in this particular FastAPI release. It is mainly to enable/unblock the release of the next version of Pydantic that comes packed with features and improvements. 🤩

### Fixes

var c uint for i := 0; i < size; i++ { _, c = bits.Sub(xLimbs[i], yLimbs[i], c) } // If there was a carry, then subtracting y underflowed, so // x is not greater than or equal to y. return not(choice(c)) } // assign sets x <- y if on == 1, and does nothing otherwise. // // Both operands must have the same announced length. // //go:norace func (x *Nat) assign(on choice, y *Nat) *Nat { // Eliminate bounds checks in the loop. size := len(x.limbs) xLimbs := x.limbs[:size] yLimbs := y.limbs[:size] mask :=...

var c uint for i := 0; i < size; i++ { _, c = bits.Sub(xLimbs[i], yLimbs[i], c) } // If there was a carry, then subtracting y underflowed, so // x is not greater than or equal to y. return not(choice(c)) } // assign sets x <- y if on == 1, and does nothing otherwise. // // Both operands must have the same announced length. // //go:norace func (x *Nat) assign(on choice, y *Nat) *Nat { // Eliminate bounds checks in the loop. size := len(x.limbs) xLimbs := x.limbs[:size] yLimbs := y.limbs[:size] mask :=...

      * Replace `LossScaleOptimizer(opt, "dynamic")` with `LossScaleOptimizer(opt)`. If you pass anything other than `"dynamic"` to the second argument, see (1) of the next section.
    * In the following rare cases, you need to make more changes when switching to the non-experimental API:
      * If you passed anything other than `"dynamic"` to the `loss_scale` argument (the second argument) of `LossScaleOptimizer`: