Does structural pruning support pre-trained model?

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#1,133 创建于 2024年6月9日 0 条评论 0 个 reaction 已指派 0 人在 GitHub 查看

还没有人认领这个 Issue。

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Issue 类型: 功能
描述清晰度: 需要澄清
活跃度: 停滞
技术栈: python, tensorflow
领域: machine-learning

调研方向

未指定源文件、测试或入口点。首先查看所引用的 TensorFlow structural-pruning 教程，并将其 from-scratch 配置与预训练模型用例进行比较；只有在请求得到澄清且可复现，并且已就 API 支持范围达成一致后，才能视为完成。

由索引模型根据 Issue 内容生成。

描述

feature request

System information

TensorFlow version (you are using):
Are you willing to contribute it (Yes/No):

Motivation

What is the use case and how does it broadly benefits users? Prioritization and whether a feature is added is based on how it
helps the community and the feature's maintenance costs.

As examples:

Instead of, "Enable the technique for my model," "Enable this technique to work better with standard object detection models, including R-CNN (link) and SSD (link)" is stronger.
Instead of, "Try something more customized with the technique," "Implement a variant of the algorithm described in equations X and Y of this paper" is clearer.

Does structural pruning support pre-trained model?

I saw Tensorflow tutorial for structural pruning, but it is used for model from scratch. It means that we need to specify pruning configuration in the model building. But it is not the case in practice.

Describe how existing APIs don't satisfy your use case (optional if obvious)

As examples:

You tried using APIs X and Y and were able to do Z. However, that was not sufficient because of ...
You achieved your use case with the code snippet W. However, this was more difficult than it should be because of ... (e.g. ran into issue X or had
to do Y).

主要语言: Python
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