[Inference] Support constant_folding_pass on PIR #58753
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yuanlehome
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| pir::Program* new_program) const { | ||
| pir::Builder builder = pir::Builder(ir_context(), new_program->block()); | ||
| std::string output_var_name = | ||
| "constant_folding@" + std::to_string((*counter_)++); |
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用counter做唯一标识输出var name感觉不是很安全
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下面还有操作，拼接了被折叠掉的name
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提醒了我，这里有个潜在问题，随着折叠的深度，name拼接后会越来越长，我修一下
zyfncg
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| // pm.EnableIRPrinting(std::make_unique<pir::PassManager::IRPrinterOption>( | ||
| // [](pir::Pass *pass, pir::Operation *op) { | ||
| // return pass->name() == "constant_folding_pass"; | ||
| // }, | ||
| // [](pir::Pass *pass, pir::Operation *op) { | ||
| // return pass->name() == "constant_folding_pass"; | ||
| // }, | ||
| // true, | ||
| // true)); |
zyfncg
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Nov 8, 2023
你说旧IR的实现吧，这比起来其实没有意义，旧模型转换到pir模型后，总op数量和被折叠的数量都不一样。算一下旧的折叠率的话，37% |
从op数量看这个数据确实意义不大，我刚才把折叠率理解成权重数量在折叠前后的对比，新旧IR的权重数量是一致的，如果折叠逻辑对齐的话折叠掉的参数数量应该是相同的，在不相同的时候这里数据或许一定的参考价值。 |
zyfncg
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Nov 8, 2023
| auto* param_var = scope_->FindVar(param_name); | ||
| PADDLE_ENFORCE_NOT_NULL( | ||
| param_var, | ||
| phi::errors::InvalidArgument("Parameter var not in scope.")); | ||
| deleted_vars_->push_back(param_name); |
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zyfncg
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Nov 9, 2023
danleifeng
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Nov 14, 2023
* fix shadow_output_op * update * rewrite constant_folding_pass * update * update * fix compile * fix dce * enhance judgement
SecretXV
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* fix shadow_output_op * update * rewrite constant_folding_pass * update * update * fix compile * fix dce * enhance judgement
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PR types
Performance optimization
PR changes
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Description
前置PR: #58732
针对PIR，实现常量折叠pass并在swintransformer模型上跑通：
TODO:
Others
Pcard-71500