Denken Sie einfach daran, wenn Sie „Server“ im Allgemeinen lesen, dass es sich auf eines dieser beiden Dinge beziehen kann.

- Restore --verify-only function in code generation wrappers. ([#123261](https://github.com/kubernetes/kubernetes/pull/123261), [@skitt](https://github.com/skitt)) [SIG API Machinery]

more releases are expected in 2019.

## Major Features and Improvements

*   The `tensorflow` pip package now includes GPU support by default (same as
    `tensorflow-gpu`) for both Linux and Windows. This runs on machines with and
    without NVIDIA GPUs. `tensorflow-gpu` is still available, and CPU-only
    packages can be downloaded at `tensorflow-cpu` for users who are concerned
    about package size.

[ ] Extensions and Telemetry
[ ] Security
[ ] Test and Release
[ ] User Experience
[ ] Developer Infrastructure

**Affected features (please put an X in all that apply)**

[ ] Multi Cluster
[ ] Virtual Machine
[ ] Multi Control Plane

## TensorFlow models are programs

TensorFlow
[**models**](https://developers.google.com/machine-learning/glossary/#model) (to
use a term commonly used by machine learning practitioners) are expressed as
programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted

- Restore --verify-only function in code generation wrappers. ([#123261](https://github.com/kubernetes/kubernetes/pull/123261), [@skitt](https://github.com/skitt)) [SIG API Machinery]

		Can be repeated to define multiple symbols.
	-I dir1 -I dir2
		Search for #include files in dir1, dir2, etc,
		after consulting $GOROOT/pkg/$GOOS_$GOARCH.
	-S
		Print assembly and machine code.
	-V
		Print assembler version and exit.
	-debug
		Dump instructions as they are parsed.
	-dynlink
		Support references to Go symbols defined in other shared libraries.
	-e

{
    "description": "TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.",
    "license": "Apache-2.0",
    "title": "TensorFlow",
    "upload_type": "software",
    "creators": [
        {
            "name": "TensorFlow Developers"
        }

## Caso de uso

Vamos iniciar com um exemplo de **caso de uso** e então ver como resolvê-lo com isso.

Vamos imaginar que você tem alguns **modelos de _machine learning_** que deseja usar para lidar com as requisições. 🤖

 * Windows command prompt you can see
 * what names a host registers with the nbtstat command.
 * <p>
 * <blockquote>
 * 
 * <pre>
 * C:\&gt;nbtstat -a 192.168.1.15
 * 
 *        NetBIOS Remote Machine Name Table
 * 
 *    Name               Type         Status
 * ---------------------------------------------
 * JMORRIS2        &lt;00&gt;  UNIQUE      Registered
 * BILLING-NY      &lt;00&gt;  GROUP       Registered