### Native. ObjC Export

- [`KT-56090`](https://youtrack.jetbrains.com/issue/KT-56090) [K2/N] Emit DocString klib extensions for ObjCExport

### Native. Runtime. Memory

- [`KT-61914`](https://youtrack.jetbrains.com/issue/KT-61914) Kotlin/Native: massive increase in memory usage
- [`KT-61092`](https://youtrack.jetbrains.com/issue/KT-61092) Kotlin/Native: Adjust initial values for expected heap size

* You don't have to use `File()` in the default value of the parameter.
* It uses a "spooled" file:
    * A file stored in memory up to a maximum size limit, and after passing this limit it will be stored in disk.
* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.

models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a
[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

### Compilation

 * [Flipper](https://fbflipper.com/): A desktop debugging platform for mobile developers.
 * [Fresco](https://github.com/facebook/fresco): An Android library for managing images and the memory they use.
 * [Glide](https://github.com/bumptech/glide): An image loading and caching library for Android focused on smooth scrolling.

* Add `metrics-port` to kube-proxy cmd flags. ([#72682](https://github.com/kubernetes/kubernetes/pull/72682), [@whypro](https://github.com/whypro))
* Reduce memory utilization of admission webhook metrics by removing resource related labels. ([#69895](https://github.com/kubernetes/kubernetes/pull/69895), [@jpbetz](https://github.com/jpbetz))



# v1.11.8

    prevents connection reuse. Each connection pool holds its own set of
    connections alive so applications that have many pools also risk exhausting
    memory!

    The best practice in OkHttp 3 is to create a single OkHttpClient instance
    and share it throughout the application. Requests that needs a customized

    - [Quality of Service for memory resources](#quality-of-service-for-memory-resources)
    - [API changes and improvements for ephemeral containers](#api-changes-and-improvements-for-ephemeral-containers)
  - [Known Issues](#known-issues)

    *   Object metadata has now been deprecated and no longer saved to the
        SavedModel.

*   TF Core:

    *   Added `tf.config.experimental.reset_memory_stats` to reset the tracked
        peak memory returned by `tf.config.experimental.get_memory_info`.

*   `tf.data`:

    *   Added `target_workers` param to `data_service_ops.from_dataset_id` and

 * concurrently.
 */
class Dispatcher() {
  internal val lock: ReentrantLock = ReentrantLock()

  /**
   * The maximum number of requests to execute concurrently. Above this requests queue in memory,
   * waiting for the running calls to complete.
   *
   * If more than [maxRequests] requests are in flight when this is invoked, those requests will
   * remain in flight.
   */
  var maxRequests = 64

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