</div>
    <div class="item">
      <a title="Scalar: Beautiful Open-Source API References from Swagger/OpenAPI files" style="display: block; position: relative;" href="https://github.com/scalar/scalar/?utm_source=fastapi&utm_medium=website&utm_campaign=top-banner" target="_blank">
        <span class="sponsor-badge">sponsor</span>
        <img class="sponsor-image" src="/img/sponsors/scalar-banner.svg" />
      </a>
    </div>

    img: https://fastapi.tiangolo.com/img/sponsors/blockbee.png
  - url: https://github.com/scalar/scalar/?utm_source=fastapi&utm_medium=website&utm_campaign=main-badge
    title: "Scalar: Beautiful Open-Source API References from Swagger/OpenAPI files"
    img: https://fastapi.tiangolo.com/img/sponsors/scalar.svg
  - url: https://www.propelauth.com/?utm_source=fastapi&utm_campaign=1223&utm_medium=mainbadge

<a href="https://github.com/scalar/scalar/?utm_source=fastapi&utm_medium=website&utm_campaign=main-badge" target="_blank" title="Scalar: Beautiful Open-Source API References from Swagger/OpenAPI files"><img src="https://fastapi.tiangolo.com/img/sponsors/scalar.svg"></a>

  - login: railwayapp
    avatarUrl: https://avatars.githubusercontent.com/u/66716858?v=4
    url: https://github.com/railwayapp
  - login: scalar
    avatarUrl: https://avatars.githubusercontent.com/u/301879?v=4
    url: https://github.com/scalar
- - login: dribia
    avatarUrl: https://avatars.githubusercontent.com/u/41189616?v=4
    url: https://github.com/dribia
  - login: svix

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

{* ../../docs_src/response_model/tutorial001_01_py310.py hl[16,21] *}

FastAPI will use this return type to:

* **Validate** the returned data.

        Keras training loops like `fit`/`evaluate`, the unreduced vector loss is
        passed to the optimizer but the reported loss will be a scalar value.
    *   `SUM`: Scalar sum of weighted losses. 4. `SUM_OVER_BATCH_SIZE`: Scalar
        `SUM` divided by number of elements in losses. This reduction type is
        not supported when used with `tf.distribute.Strategy` outside of

	XVMOVQ		X0, X31.B32     // 1f000777
	XVMOVQ		X1, X30.H16     // 3e800777
	XVMOVQ		X2, X29.W8      // 5dc00777
	XVMOVQ		X3, X28.V4      // 7ce00777
	XVMOVQ		X3, X27.Q2      // 7bf00777

	// Move vector element to scalar.
	XVMOVQ		X0, X31.W[7]    // 1fdcff76
	XVMOVQ		X1, X29.W[0]    // 3dc0ff76
	XVMOVQ		X3, X28.V[3]    // 7cecff76
	XVMOVQ		X4, X27.V[0]    // 9be0ff76
	XVMOVQ		X31.W[7], X0    // e0df0377

* 📝 Tweak default suggested configs for generating clients. PR [#10736](https://github.com/tiangolo/fastapi/pull/10736) by [@tiangolo](https://github.com/tiangolo).

### Internal

* 🔧 Update sponsors, add Scalar. PR [#10728](https://github.com/tiangolo/fastapi/pull/10728) by [@tiangolo](https://github.com/tiangolo).