Typeflag: TypeSymlink,
		},
		fm: 0777 | fs.ModeSymlink,
	}, {
		// character device node.
		h: &Header{
			Name:     "dev/null",
			Mode:     0666,
			Size:     0,
			ModTime:  time.Unix(1360578951, 0),
			Typeflag: TypeChar,
		},
		fm: 0666 | fs.ModeDevice | fs.ModeCharDevice,
	}, {
		// block device node.
		h: &Header{
			Name:     "dev/sda",
			Mode:     0660,
			Size:     0,

	MLGR	R1, R2                // b9860021
	DIVD	R1, R2                // b90400b2b90d00a1b904002b
	DIVD	R1, R2, R3            // b90400b2b90d00a1b904003b
	DIVW	R4, R5                // b90400b5b91d00a4b904005b
	DIVW	R4, R5, R6            // b90400b5b91d00a4b904006b
	DIVDU	R7, R8                // a7a90000b90400b8b98700a7b904008b
	DIVDU	R7, R8, R9            // a7a90000b90400b8b98700a7b904009b

 * class to read a response that is larger than the entire memory allocated to the current process.
 * It can even stream a response larger than the total storage on the current device, which is a
 * common requirement for video streaming applications.
 *
 * Because this class does not buffer the full response in memory, the application may not

[CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and
Windows)*:

```
$ pip install tensorflow
```

Other devices (DirectX and MacOS-metal) are supported using
[Device Plugins](https://www.tensorflow.org/install/gpu_plugins#available_devices).

A smaller CPU-only package is also available:

```
$ pip install tensorflow-cpu
```

# Handling Errors { #handling-errors }

There are many situations in which you need to notify an error to a client that is using your API.

This client could be a browser with a frontend, a code from someone else, an IoT device, etc.

You could need to tell the client that:

* The client doesn't have enough privileges for that operation.
* The client doesn't have access to that resource.
* The item the client was trying to access doesn't exist.
* etc.

    ask_cuda_compute_capabilities = (
        'Please specify a list of comma-separated CUDA compute capabilities '
        'you want to build with.\nYou can find the compute capability of your '
        'device at: https://developer.nvidia.com/cuda-gpus. Each capability '
        'can be specified as "x.y" or "compute_xy" to include both virtual and'
        ' binary GPU code, or as "sm_xy" to only include the binary '

package main

import (
	"fmt"
	"go/build"
	"log"
	"os"
	"os/exec"
	"path/filepath"
	"runtime"
	"strings"
	"syscall"
)

const debug = false

var tmpdir string

var (
	devID    string
	appID    string
	teamID   string
	bundleID string
	deviceID string
)

// lock is a file lock to serialize iOS runs. It is global to avoid the

- Added driver-owned fields in `ResourceClaim.Status` to report device status data for each allocated device. ([#128240](https://github.com/kubernetes/kubernetes/pull/128240), [@LionelJouin](https://github.com/LionelJouin)) [SIG API Machinery, Network, 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))

## Add Labels to PRs

The same GitHub Action <a href="https://github.com/tiangolo/latest-changes" class="external-link" target="_blank">latest-changes</a> uses one label in the PR to decide the section in the release notes to put this PR in.

Make sure you use a supported label from the <a href="https://github.com/tiangolo/latest-changes#using-labels" class="external-link" target="_blank">latest-changes list of labels</a>: