- [`KT-57889`](https://youtrack.jetbrains.com/issue/KT-57889) K2: false-positive lack of information for inline function's type parameter in case of builder-style inference from caller function's return expression
- [`KT-57961`](https://youtrack.jetbrains.com/issue/KT-57961) K2: Unresolved reference using dynamic lambda parameter

        "//tensorflow:windows": """
              $(location @local_config_def_file_filter//:def_file_filter) \\
              --input $(location :tensorflow_def_file) \\
              --output $@
          """,
        "//conditions:default": "touch $@",  # Just a placeholder for Unix platforms
    }),
    tools = ["@local_config_def_file_filter//:def_file_filter"],
    visibility = ["//visibility:public"],
)

                    """
                    @file:Incubating
                    package com.example

                    import org.gradle.api.Incubating

                    ${annotatedKotlinMembers.lineSequence().filter { !it.contains("Incubating") }.joinToString("\n")}

                    /** @since 2.0 */
                    const val cathedral = "cathedral"
                    """
                )
            }

                    localName += current.name.asString()
                } else {
                    className += current.name.asString()
                }
            }
            is PropertyAccessorDescriptor -> {} // Filter out property accessors
            is CallableDescriptor -> {
                if (!allowLocal) {
                    return null
                }

                localName += current.name.asString()

  then kube-proxy will send the traffic to the Terminating pod rather than dropping it. This
  patches up a race condition between when a pod is killed and when the external load
  balancer notices that it has been killed. ([#97238](https://github.com/kubernetes/kubernetes/pull/97238), [@andrewsykim](https://github.com/andrewsykim))

- Implement `post-filter` extension point for scheduling framework ([#78097](https://github.com/kubernetes/kubernetes/pull/78097), [@draveness](https://github.com/draveness))
- Add Bind extension point of the scheduling framework ([#78513](https://github.com/kubernetes/kubernetes/pull/78513), [@chenchun](https://github.com/chenchun))

    *   Added a new field, `filter_parallelization`, to `tf.data.experimental.OptimizationOptions`. If it is set to `True`, tf.data will run `Filter` transformation with multiple threads. Its default value is `False` if not specified.

*   `tf.keras`:

  // Example: when this is set to 30%, the new ReplicaSet can be scaled up immediately when
  // the rolling update starts, such that the total number of old and new pods do not exceed
  // 130% of desired pods. Once old pods have been killed,
  // new ReplicaSet can be scaled up further, ensuring that total number of pods running
  // at any time during the update is at most 130% of desired pods.
  // +optional

### Feature

- A new metric `apiserver_request_filter_duration_seconds` has been introduced that 
  measures request filter latency in seconds. ([#95207](https://github.com/kubernetes/kubernetes/pull/95207), [@tkashem](https://github.com/tkashem)) [SIG API Machinery and Instrumentation]

Plugins that are enabled via `multiPoint` will automatically be registered for each individual extension point that they implement.
For example, a plugin that implements Score and Filter extensions can be simultaneously enabled for both.
This means entire plugins can be enabled and disabled without having to manually edit individual extension point settings.