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谢邀。先给结论：以我写了两三年 pytorch 代码的经验而言，比较好的顺序是先写 model，再写 dataset，最后写 train。 在讨论码组件的具体顺序前，我们先分析每一个组件背后的目的和逻. Do they mean the same? Train on meaning to aim is a completely different meaning of train, and there should be no overlap between this meaning and the meaning of teach in the original sentence.
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Model.train ()和model.eval () 我们知道，在pytorch中，模型有两种模式可以设置，一个是train模式、另一个是eval模式。 model.train ()的作用是启用 batch normalization 和 dropout。在train. 训练后的模型会非常的大，比如原本 2g 的模型，完全训练后会有 4g 多，当然这已经是删除了检查点后的大小。比如量化参数或压缩模型等手段来缩小模型。 1.2、微调模型 在预训练模型的.
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