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14 changes: 9 additions & 5 deletions mlir/lib/Dialect/XeGPU/Transforms/XeGPUWgToSgDistribute.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -376,10 +376,12 @@ struct WgToSgElementwiseOp : public ConversionPattern {
// Copy all attributes, but update "layout_result_0" to drop
// sgLayout/sgData
for (auto attr : op->getAttrs()) {
if (auto layout = dyn_cast<xegpu::LayoutAttr>(attr.getValue()))
state.addAttribute(attr.getName(), layout.dropSgLayoutAndData());
else
if (auto layout = dyn_cast<xegpu::LayoutAttr>(attr.getValue())) {
if (auto newLayout = layout.dropSgLayoutAndData())

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Is "else" required here?

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@chencha3 chencha3 Jun 27, 2025

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I don't think so. if the newLayout is null, we don't need to keep it in the op

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Yeah, you're right, sorry for the noise

state.addAttribute(attr.getName(), newLayout);
} else {
state.addAttribute(attr.getName(), attr.getValue());
}
}
Operation *newOp = rewriter.create(state);
newResults.push_back(newOp->getResult(0));
Expand Down Expand Up @@ -629,8 +631,10 @@ void XeGPUWgToSgDistributePass::runOnOperation() {
std::string name = xegpu::getLayoutName(result);
if (auto layout = op->getAttrOfType<xegpu::LayoutAttr>(name)) {
op->removeAttr(name);
if (!isa<scf::IfOp, scf::ForOp, scf::WhileOp, scf::ConditionOp>(op))
op->setAttr(name, layout.dropSgLayoutAndData());
if (!isa<scf::IfOp, scf::ForOp, scf::WhileOp, scf::ConditionOp>(op)) {
if (auto newLayout = layout.dropSgLayoutAndData())
op->setAttr(name, newLayout);
}
}
}
});
Expand Down
19 changes: 19 additions & 0 deletions mlir/test/Dialect/XeGPU/xegpu-wg-to-sg-elemwise.mlir
Original file line number Diff line number Diff line change
@@ -1,6 +1,25 @@
// RUN: mlir-opt --xegpu-wg-to-sg-distribute -split-input-file %s | FileCheck %s

gpu.module @test_elementwise_ops {

// CHECK-LABEL: unary_ops_sg_layout_only
gpu.func @unary_ops_sg_layout_only(%a: memref<24x32xf32>) {
%tdesc_a = xegpu.create_nd_tdesc %a[0, 0] : memref<24x32xf32>
-> !xegpu.tensor_desc<24x32xf32, #xegpu.layout<sg_layout = [2, 4], sg_data = [12, 8]>>
%load_a = xegpu.load_nd %tdesc_a
: !xegpu.tensor_desc<24x32xf32, #xegpu.layout<sg_layout = [2, 4], sg_data = [12, 8]>>
-> vector<24x32xf32>
// CHECK: math.exp {{.*}} : vector<12x8xf32>
%exp = math.exp %load_a
{layout_result_0 = #xegpu.layout<sg_layout = [2, 4], sg_data = [12, 8]>}
: vector<24x32xf32>
// CHECK: arith.negf {{.*}} : vector<12x8xf32>
%negf = arith.negf %load_a
{layout_result_0 = #xegpu.layout<sg_layout = [2, 4], sg_data = [12, 8]>}
: vector<24x32xf32>
gpu.return
}

// CHECK-LABEL: unary_ops
gpu.func @unary_ops(%a: memref<24x32xf32>) {
%tdesc_a = xegpu.create_nd_tdesc %a[0, 0] : memref<24x32xf32>
Expand Down
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