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@@ -593,6 +593,8 @@ Attribute DotOperandEncodingAttr::parse(AsmParser &parser, Type type) {
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if(parent.isa<MmaEncodingAttr>() &&
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if(parent.isa<MmaEncodingAttr>() &&
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parent.cast<MmaEncodingAttr>().getVersion() == 1){
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parent.cast<MmaEncodingAttr>().getVersion() == 1){
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isMMAv1Row = attrs.get("isMMAv1Row");
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isMMAv1Row = attrs.get("isMMAv1Row");
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if(!isMMAv1Row)
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llvm::report_fatal_error("isMMAv1Row attribute is missing");
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}
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}
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return parser.getChecked<DotOperandEncodingAttr>(parser.getContext(), opIdx,
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return parser.getChecked<DotOperandEncodingAttr>(parser.getContext(), opIdx,
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parent, isMMAv1Row);
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parent, isMMAv1Row);
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@@ -879,8 +879,8 @@ module attributes {"triton_gpu.num-warps" = 4 : i32} {
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#blocked = #triton_gpu.blocked<{sizePerThread = [1, 4], threadsPerWarp = [2, 16], warpsPerCTA = [1, 4], order = [1, 0]}>
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#blocked = #triton_gpu.blocked<{sizePerThread = [1, 4], threadsPerWarp = [2, 16], warpsPerCTA = [1, 4], order = [1, 0]}>
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#shared = #triton_gpu.shared<{vec = 1, perPhase = 1, maxPhase = 1, order = [1, 0]}>
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#shared = #triton_gpu.shared<{vec = 1, perPhase = 1, maxPhase = 1, order = [1, 0]}>
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#mma = #triton_gpu.mma<{version = 1, warpsPerCTA = [2, 2]}>
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#mma = #triton_gpu.mma<{version = 1, warpsPerCTA = [2, 2]}>
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#dot_operand_a = #triton_gpu.dot_op<{opIdx=0, parent=#mma}>
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#dot_operand_a = #triton_gpu.dot_op<{opIdx=0, parent=#mma, isMMAv1Row=true}>
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#dot_operand_b = #triton_gpu.dot_op<{opIdx=1, parent=#mma}>
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#dot_operand_b = #triton_gpu.dot_op<{opIdx=1, parent=#mma, isMMAv1Row=true}>
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module attributes {"triton_gpu.num-warps" = 4 : i32} {
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module attributes {"triton_gpu.num-warps" = 4 : i32} {
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func @matmul884_kernel_dot_operand_layout(%ptr:!tt.ptr<f32> {tt.divisibility = 16 : i32},
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func @matmul884_kernel_dot_operand_layout(%ptr:!tt.ptr<f32> {tt.divisibility = 16 : i32},
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%a:tensor<128x32xf16, #shared>, %b:tensor<32x256xf16, #shared>) {
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%a:tensor<128x32xf16, #shared>, %b:tensor<32x256xf16, #shared>) {
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