*   `Model.fit_generator`, `Model.evaluate_generator`,
        `Model.predict_generator`, `Model.train_on_batch`,
        `Model.test_on_batch`, and `Model.predict_on_batch` methods now respect
        the `run_eagerly` property, and will correctly run using `tf.function`
        by default. Note that `Model.fit_generator`, `Model.evaluate_generator`,

@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
    return filter_query
```

Read the new docs: [Query Parameter Models](https://fastapi.tiangolo.com/tutorial/query-param-models/).

#### `Header` Parameter Models

Use Pydantic models for `Header` parameters:

```python
from typing import Annotated

from fastapi import FastAPI, Header
from pydantic import BaseModel

x.limbs[i] i-- } // We shift in the remaining limbs, reducing modulo m each time. for i >= 0 { out.shiftIn(x.limbs[i], m) i-- } return out } // ExpandFor ensures x has the right size to work with operations modulo m. // // The announced size of x must be smaller than or equal to that of m. func (x *Nat) ExpandFor(m *Modulus) *Nat { return x.expand(len(m.nat.limbs)) } // resetFor ensures out has the right size to work with operations modulo m. // // out is zeroed and may start at any size. func (out...

- Avoid unnecessary scheduling churn when annotations are updated while Pods are being scheduled. ([#90373](https://github.com/kubernetes/kubernetes/pull/90373), [@fabiokung](https://github.com/fabiokung)) [SIG Scheduling]
- Azure auth module for kubectl now requests login after refresh token expires. ([#86481](https://github.com/kubernetes/kubernetes/pull/86481), [@tdihp](https://github.com/tdihp)) [SIG API Machinery and Auth]

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