January 2023
Intermediate to advanced
288 pages
6h 6m
Chinese
Content preview from 移动端AI与ML应用开发：基于iOS和Android
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258
|
第
14
章
然后在 Android 上使用它。Firebase 身份验证（
https://oreil.ly/WTSaa
）就是其中之一。
14.4
从
iOS
访问服务器模型
之前你创建了一个模型并将其托管在 TensorFlow Serving 上，该模型可从
http://<server>:
8501/v1/models/helloworld:predict
获得。对于本示例，我的服务器位于
192.168.86.26
，因此
我要创建一个简单的 iOS 应用程序，该应用程序可以访问服务器、向其传递数据并返回
推理。要执行此操作并推理单个值，你需要将 JSON 有效负载发布到服务器，如下所示：
{"signature_name": "serving_default", "instances": [[10.0]]}
如果这成功了，你会得到一个包含推理的有效负载：
{
"predictions": [[18.9806728]]
}
因此，我们首先需要一个应用程序将有效负载传递到服务器，并解析返回的内容。让我
们探索一下如何在 Swift 中做到这一点。你可以在本书的存储库（
https://oreil.ly/wPL4V
）
中找到一个完整的应用程序。在本节中，我将只探讨此应用程序如何进行远程推理：
首先，在 Swift 中，如果你设置了等效的结构，则很容易解码 JSON 值。因此要解码预
测，你可以创建如下结构：
struct Results: Decodable {
let predictions: [[Double]] ...
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