【SCU】【Paddle TensorRT No.48】Add pd_op.pad converter
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你的PR提交成功，感谢你对开源项目的贡献! |
PolaKuma
changed the title
pd_op.pad converterpd_op.pad converter
lizexu123
reviewed
Nov 27, 2024
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| // Check for the existence of the attributes pad_value and paddings | ||
| if (!op->HasAttribute("pad_value") || !op->HasAttribute("paddings")) { |
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paddings是属性，pad_value是输入
| return false; | ||
| } | ||
| for (int i = 0; i < pad_size - 4; ++i) { | ||
| if (paddings[i].dyn_cast<pir::Int64Attribute>().data() != 0) { |
| def setUp(self): | ||
| self.python_api = paddle.nn.functional.pad | ||
| self.api_args = { | ||
| "x": np.random.randn(1, 3, 32, 32).astype("float32"), |
YuanRisheng
reviewed
Dec 11, 2024
| } | ||
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| // Check for the existence of the attributes pad_value and paddings | ||
| if (!op->HasAttribute("pad_value") || !op->HasAttribute("paddings")) { |
There was a problem hiding this comment.
可以参考pd_op.h文件里PadOp定义的代码，这里构建算子的时候，pad_value可以传入value（对应旧IR的输入）或者float（对应原来旧IR下的attribute），这种场景下不管是value还是float，进入到PIR内都会变成输入operands，所以你需要判断pad_value是否是float传入的，这才能对应起来原来旧IR下那部分attribute判断逻辑，可以使用这个pir::GetDefiningOpForInput(op, 1)->isa<paddle::dialect::FullOp>()来判断是否是属性pad_value，详情使用可以进一步参考trt_op_marker_pass.cc里的其他代码
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Sorry to inform you that 9a82b0e's CIs have passed for more than 7 days. To prevent PR conflicts, you need to re-run all CIs manually. |
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PR Category
User Experience
PR Types
New features
Description
新增了
pd_op.padMarker和Converter