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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第
8
章
8.2.1
保存模型
TensorFlow 使用多种不同的模型保存方法，但 TensorFlow 生态系统中最标准化的是
SavedModel 格式。这会将模型保存为
.pb
（用 于 protobuf）文件格式，作为固定模型的
表示，以及包含其他模型资产或变量的关联目录。这具有将架构与状态分离的决定性优
势，以便以后可以根据需要添加其他状态，或者可以发送模型更新，而无须发送递交任
何模型资产，这些资产本身可能非常大。
要使用这种格式保存，你只需指定输出目录，然后像这样调用
tf.saved_model.save()
：
export_dir = 'saved_model/1'
tf.saved_model.save(model, export_dir)
你可以在图 8-2 中看到保存的目录结构。
图
8-2
：保存模型后的目录结构
由于这是一个非常简单的模型，变量文件只有一个分片。较大的模型将拆分为多个，因
此命名为
variables.data-00000-of-00001
。此模型不使用任何资产，因此该文件夹为空。
8.2.2
转换模型
转换模型就像从保存的模型中创建转换器的实例并调用其转换方法一样简单。这将为你
提供 TFLite 格式的模型，然后你可以通过将其字节写入文件流来保存该模型。
这是代码：
converter = tf.lite.TFLiteConverter.from_saved_model(export_dir)
tflite_model = converter.convert() ...
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