- DRA: ResourceClaim and PodSchedulingContext status updates no longer allow changing object meta data. ([#123730](https://github.com/kubernetes/kubernetes/pull/123730), [@pohly](https://github.com/pohly))

- Expose a `NewUnstructuredExtractor` from apply configurations `meta/v1` package that enables extracting objects into unstructured apply configurations. ([#103564](https://github.com/kubernetes/kubernetes/pull/103564), [@kevindelgado](https://github.com/kevindelgado))

- Fix k8s.io/apimachinery/pkg/api/meta.SetStatusCondition to update ObservedGeneration ([#95961](https://github.com/kubernetes/kubernetes/pull/95961), [@KnicKnic](https://github.com/KnicKnic)) [SIG API Machinery]

- The errors in `k8s.io/apimachinery/pkg/api/meta` now support for the `stdlibs` `errors.Is` matching, including when wrapped. ([#111808](https://github.com/kubernetes/kubernetes/pull/111808), [@alvaroaleman](https://github.com/alvaroaleman))

the metadata (the `metadata` sub-section) from resources on the cluster in an efficient manner for use cases that deal with objects generically, like the garbage collector, quota, or the namespace controller. The client asks the server to return a `meta.k8s.io/v1 PartialObjectMetadata` object for list, get, delete, watch, and patch operations on both normal APIs and custom resources which can be encoded in protobuf for additional work. If the server does not yet support this API the client will gracefully...

[S interface{ ~[]byte|string }]
[S ~[]E, E any]
[P Constraint[int]]
[_ any]
</pre>

<p>
Just as each ordinary function parameter has a parameter type, each type parameter
has a corresponding (meta-)type which is called its
<a href="#Type_constraints"><i>type constraint</i></a>.
</p>

<p>
A parsing ambiguity arises when the type parameter list for a generic type

    *   During tensor-filter operations, allow exclusion of nodes by regular
        expressions.
    *   Fix spurious background colors in some text terminals.
*   `tf.contrib`:
    *   Add meta-distribution BatchReshape which reshapes batch dimensions.
    *   `tf.contrib.layers.recompute_grad` works for explicit gradient
        checkpointing on TPU.
    *   Add `tf.contrib.framework.argsort`.

can be found in the LICENSE file. // Code generated by {{ .Meta.Name }}. DO NOT EDIT. package fiat // Invert sets e = 1/x, and returns e. // // If x == 0, Invert returns e = 0. func (e *Element) Invert(x *Element) *Element { // Inversion is implemented as exponentiation with exponent p − 2. // The sequence of {{ .Ops.Adds }} multiplications and {{ .Ops.Doubles }} squarings is derived from the // following addition chain generated with {{ .Meta.Module }} {{ .Meta.ReleaseTag }}. // {{- range lines (format...