[Inference] add add_shadow_output_after_dead_parameter_pass#68476
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yuanlehome merged 4 commits intoPaddlePaddle:developfrom Sep 27, 2024
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vivienfanghuagood
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vivienfanghuagood
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一定需要新增shadow_output才能避免被DCE裁剪吗？
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目前没有想到更好的解决思路。 |
zyfncg
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| class AddShadowOutputAfterDeadParameterPattern | ||
| : public pir::OpRewritePattern<pir::ParameterOp> { | ||
| public: | ||
| using pir::OpRewritePattern<pir::ParameterOp>::OpRewritePattern; | ||
| bool MatchAndRewrite( | ||
| pir::ParameterOp op, | ||
| pir::PatternRewriter& rewriter) const override { // NOLINT | ||
| if (!op->use_empty()) { | ||
| return false; | ||
| } | ||
| rewriter.SetInsertionPointToBlockEnd(op->GetParent()); | ||
| rewriter.Build<pir::ShadowOutputOp>(op->result(0), op.param_name()); | ||
| return true; | ||
| } | ||
| }; |
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这样是不是等于所有ParameterOp都不会DCE了？
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不是，推理这边是把这个pass放在所有pass之前执行的，只会对原始模型里的ParameterOp不DCE
zyfncg
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Sep 27, 2024
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PR Category
Inference
PR Types
Others
Description
pcard-71500
为什么需要这么一个Pass？
为了适配paddle.nn.Layer.register_buffer的功能。register_buffer会在模型结构中产出一个“dead”的builtin.parameter_op，也就是说它的输出没有被使用到（这是因为动转静保存模型时并不会对这类op做裁剪PR#68442），在IR中我们认为其是dead code。如果不加以处理，在推理的IR优化过程中会被dead_code_elimination_pass给删除掉，这是不符合预期的行为。因此添加add_shadow_output_after_dead_parameter_pass，在这个dead op后添加一个shadow_output op用来标识parameter_op的输出有被使用到，因此就不会被dead_code_elimination_pass给误删除了。