* Fix issue where on re-registration of device plugin, `allocatable` was not getting updated. This issue makes devices invisible to the Kubelet if device plugin restarts. Only work-around, if this fix is not there, is to restart the kubelet and then start device plugin. ([#63118](https://github.com/kubernetes/kubernetes/pull/63118), [@vikaschoudhary16](https://github.com/vikaschoudhary16))

        decisions.
*   PluggableDevice
    *   Third-party devices can now connect to TensorFlow as plug-ins through
        [StreamExecutor C API](https://github.com/tensorflow/community/blob/master/rfcs/20200612-stream-executor-c-api.md).
        and
        [PluggableDevice](https://github.com/tensorflow/community/blob/master/rfcs/20200624-pluggable-device-for-tensorflow.md)
        interface.

- Services implement a field selector for the ClusterIP and Type fields.
  Kubelet uses the fieldselector on Services to avoid watching for Headless Services and reduce the memory consumption. ([#123905](https://github.com/kubernetes/kubernetes/pull/123905), [@aojea](https://github.com/aojea)) [SIG Apps, Node and Testing]

* Fix issue where on re-registration of device plugin, `allocatable` was not getting updated. This issue makes devices invisible to the Kubelet if device plugin restarts. Only work-around, if this fix is not there, is to restart the kubelet and then start device plugin. ([#63118](https://github.com/kubernetes/kubernetes/pull/63118), [@vikaschoudhary16](https://github.com/vikaschoudhary16))

- Fixed cleanup of raw block devices after kubelet restart. ([#83451](https://github.com/kubernetes/kubernetes/pull/83451), [@jsafrane](https://github.com/jsafrane))
- Add data cache flushing during unmount device for GCE-PD driver in Windows Server. ([#83591](https://github.com/kubernetes/kubernetes/pull/83591), [@jingxu97](https://github.com/jingxu97))

  * **alpha**: NVIDIA GPU support ([#24836](https://github.com/kubernetes/kubernetes/pull/24836), [@therc](https://github.com/therc))
  * Adding loadBalancer services and nodeports services to quota system

## Known Issues and Important Steps before Upgrading

  csession.CloseAndDelete(s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteGraph(graph);
  TF_DeleteStatus(s);
}

// If `device` is non-empty, run Min op on that device.
// Otherwise run it on the default device (CPU).
void RunMinTest(const string& device, bool use_XLA) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Make a placeholder operation.

servep2p.com
servepics.com
servequake.com
server-on.net
servername.us
servers.run
servesarcasm.com
service.gov.scot
service.gov.uk
service.one
servicebus.windows.net
services
services.aero
setagaya.tokyo.jp
seto.aichi.jp
setouchi.okayama.jp
settsu.osaka.jp
sevastopol.ua
seven
sew
sex
sex.hu
sex.pl
sexy
sf.no
sfr
sg

name: TensorFlow Lite in Play Services issue
about: Use this template for issues with TensorFlow Lite in Google Play Services
labels: 'comp:lite-in-play-services'

---

**System information**
- Android Device information (use `adb shell getprop ro.build.fingerprint`
  if possible):
- TensorFlow Lite in Play Services SDK version (found in `build.gradle`):
- Google Play Services version
  (`Settings` > `Apps` > `Google Play Services` > `App details`):

- During device plugin allocation, resources requested by the pod can only be allocated if the device plugin has registered itself to kubelet AND healthy devices are present on the node to be allocated. If these conditions are not sattsfied, the pod would fail with `UnexpectedAdmissionError` error. ([#117719](https://github.com/kuber...