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How to customize a loss function in pytorch? #1352

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stevenhanjun opened this issue Apr 25, 2017 · 1 comment
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How to customize a loss function in pytorch? #1352

stevenhanjun opened this issue Apr 25, 2017 · 1 comment

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@stevenhanjun
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@soumith
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soumith commented Apr 25, 2017

search discuss.pytorch.org for answer

@soumith soumith closed this as completed Apr 25, 2017
eqy pushed a commit to eqy/pytorch that referenced this issue Jan 20, 2022
@csarofeen
Collection of refactoring in nvFuser lowering (pytorch#1339)
d29fb48 
* Refactor War Sync Insertion Pass (pytorch#1339)
* Remove kir::Expr::scope_ (pytorch#1341)
* Fusion IR Refactor (pytorch#1343)
* Refactor KIR Step 1 - Remove kir::Node (pytorch#1347)
* Refactor KIR Step 2 - TMP IrUtils change (pytorch#1348)
* Refactor KIR Step 3 - Remove kir::Expr and kir::Val. (pytorch#1349)
* Refactor KIR Step 4 - Remove kir::Bool,Double,Int,NamedScalar. (pytorch#1350)
* Refactor KIR Step 5 - Remove kir::IterDomain/TensorDomain/TensorView (pytorch#1351)
* Refactor KIR Step 6 - Remove 
 kir::UnaryOp/BinaryOp/TernaryOp/ReductionOp/WelfordOp/BroadcastOp. (pytorch#1352)
* Refactor KIR Step 7 - Remove kir dispatch (pytorch#1353)
* Refactor KIR Step 8 - Clean up lower_utils (pytorch#1355)
* Refactor KIR Step 9 - lower_utils ir_utils::applyReplacements. (pytorch#1354)
* Refactor KIR Step 10 - Remove kir_printer in favor of io_stream (pytorch#1356)
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@soumith @stevenhanjun