我刚刚使用Tensorflow训练了一个模型，我想保存它并在以后恢复它。我在Tensorflow的官方文档中阅读了Saving and Restoring page，我偶然发现以下代码来保存模型
&但我无法理解import { Pipe, PipeTransform } from '@angular/core';
import {unescape} from 'lodash';
@Pipe({
name: 'unescape'
})
export class UnescapePipe implements PipeTransform {
transform(value: any, args?: any): any {
return unescape(value);
}
}列表和export_dir = ...
...
builder = tf.saved_model_builder.SavedModelBuilder(export_dir)
with tf.Session(graph=tf.Graph()) as sess:
...
builder.add_meta_graph_and_variables(sess,
[tag_constants.TRAINING],
signature_def_map=foo_signatures,
assets_collection=foo_assets)
...
# Add a second MetaGraphDef for inference.
with tf.Session(graph=tf.Graph()) as sess:
...
builder.add_meta_graph([tag_constants.SERVING])
...
builder.save()
列表是什么。
答案 0 :(得分：1)
它们似乎只是用于识别您要恢复的 For Each ctrl As Control In Controls
If TypeOf ctrl Is Button Then
If ctrl.Tag.ToString.Contains(BT) = True Then
CType(ctrl, Button).ForeColor = Color.LimeGreen
Else
CType(ctrl, Button).ForeColor = Color.White
End If
End If
Next
End Sub
。现有代码为MetaGraphDef，SERVING和TRAINING，但您可以使用GPU等内容定义自己的代码。