*   Compared to `tf.lookup.experimental.DenseHashTable` this offers
            lower overall memory usage, and a cleaner API. It does not require
            specifying a `delete_key` and `empty_key` that cannot be inserted
            into the table.
    *   Added support for specifying number of subdivisions in all reduce host
        collective. This parallelizes work on CPU and speeds up the collective

t.Fatal(err) } else if k.IsZero() == 1 { t.Error("k is zero") } else if p.Bytes()[0] != 4 { t.Error("p is infinity") } if loopCount == 0 { t.Error("overflow was not rejected") } loopCount = 0 // A sequence of all zeroes will generate zero, which should be rejected. r = io.MultiReader(bytes.NewReader(bytes.Repeat([]byte{0}, 100)), rand.Reader) if k, p, err := randomPoint(c, func(b []byte) error { _, err := r.Read(b) return err }); err != nil { t.Fatal(err) } else if k.IsZero() == 1 { t.Error("k is zero")...

* Add support for `response_model_exclude_defaults` and `response_model_exclude_none`:
    * Deprecate the parameter `include_none` in `jsonable_encoder` and add the inverted `exclude_none`, to keep in sync with Pydantic.
    * PR [#1166](https://github.com/tiangolo/fastapi/pull/1166) by [@voegtlel](https://github.com/voegtlel).