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fix(hlo): GroupNorm emits real stablehlo.reduce (IREE-compilable) #754

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Merged
michalharakal merged 1 commit into from
Jun 23, 2026
Merged

fix(hlo): GroupNorm emits real stablehlo.reduce (IREE-compilable) #754

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28 changes: 22 additions & 6 deletions ...hlo/src/commonMain/kotlin/sk/ainet/compile/hlo/converters/NeuralNetOperationsConverter.kt
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Original file line number Diff line number Diff line change
Expand Up @@ -509,9 +509,16 @@ public class NeuralNetOperationsConverter : StableHloOperationConverter {
val offsetOperand: String? = if (operands.size > 2) operands[2] else null

val grouped = context.nextTempValue()
val zeroInit = context.nextTempValue()
val countConst = context.nextTempValue()
val sumX = context.nextTempValue()
val meanValue = context.nextTempValue()
val meanBroadcast = context.nextTempValue()
val centered = context.nextTempValue()
val squared = context.nextTempValue()
val sumSq = context.nextTempValue()
val meanSq = context.nextTempValue()
val meanSquared = context.nextTempValue()
val varValue = context.nextTempValue()
val epsConst = context.nextTempValue()
val epsBroadcast = context.nextTempValue()
Expand All @@ -527,16 +534,25 @@ public class NeuralNetOperationsConverter : StableHloOperationConverter {
// spatial into one trailing axis so a single-axis reduction is per-group.
operations += "$grouped = stablehlo.reshape $xInput : ($outputType) -> $groupedType"

// mean(xg) over the trailing axis, broadcast back, mean-center.
operations += "$meanValue = stablehlo.custom_call @reduce_mean($grouped) " +
"{dimensions = [2], keepdim = false} : $reducedType"
// Reductions use real `stablehlo.reduce` (not @reduce_* custom_calls) so the module
// compiles on stock IREE. mean(xg) = sum(xg) / M over the trailing axis; broadcast
// back and mean-center.
operations += "$zeroInit = stablehlo.constant dense<0.0> : tensor<$elementType>"
operations += "$countConst = stablehlo.constant dense<${perGroup}.0> : $reducedType"
operations += "$sumX = stablehlo.reduce($grouped init: $zeroInit) " +
"applies stablehlo.add across dimensions = [2] : ($groupedType, tensor<$elementType>) -> $reducedType"
operations += "$meanValue = stablehlo.divide $sumX, $countConst : $reducedType"
operations += "$meanBroadcast = stablehlo.broadcast_in_dim $meanValue, " +
"dims = [0, 1] : ($reducedType) -> $groupedType"
operations += "$centered = stablehlo.subtract $grouped, $meanBroadcast : $groupedType"

// var(xg) over the trailing axis; std = sqrt(var + eps).
operations += "$varValue = stablehlo.custom_call @reduce_variance($grouped) " +
"{dimensions = [2], keepdim = false} : $reducedType"
// var(xg) = E[xg^2] - E[xg]^2 (population, ddof=0); std = sqrt(var + eps).
operations += "$squared = stablehlo.multiply $grouped, $grouped : $groupedType"
operations += "$sumSq = stablehlo.reduce($squared init: $zeroInit) " +
"applies stablehlo.add across dimensions = [2] : ($groupedType, tensor<$elementType>) -> $reducedType"
operations += "$meanSq = stablehlo.divide $sumSq, $countConst : $reducedType"
operations += "$meanSquared = stablehlo.multiply $meanValue, $meanValue : $reducedType"
operations += "$varValue = stablehlo.subtract $meanSq, $meanSquared : $reducedType"
operations += "$epsConst = stablehlo.constant dense<$epsilon> : tensor<$elementType>"
operations += "$epsBroadcast = stablehlo.broadcast_in_dim $epsConst, " +
"dims = [] : (tensor<$elementType>) -> $reducedType"
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13 changes: 8 additions & 5 deletions .../skainet-compile-hlo/src/commonTest/kotlin/sk/ainet/compile/hlo/GroupNormConverterTest.kt
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Expand Up @@ -51,9 +51,12 @@ class GroupNormConverterTest {
val mlir = module.content

assertTrue(mlir.contains("stablehlo.reshape"), "groupNorm must reshape to group the channels and back")
assertTrue(mlir.contains("@reduce_mean"), "groupNorm must lower mean(x) to a real reduction")
assertTrue(mlir.contains("@reduce_variance"), "groupNorm must lower var(x) to a real reduction")
assertTrue(mlir.contains("stablehlo.subtract"), "groupNorm must mean-center")
assertTrue(mlir.contains("stablehlo.reduce("), "groupNorm must lower mean/var to real stablehlo.reduce")
assertFalse(
mlir.contains("custom_call"),
"groupNorm must use real stablehlo.reduce, not @reduce_* custom_calls (those don't compile on IREE)"
)
assertTrue(mlir.contains("stablehlo.subtract"), "groupNorm must mean-center and form E[x^2]-E[x]^2")
assertTrue(mlir.contains("stablehlo.sqrt"), "groupNorm must take sqrt(var + eps)")
assertTrue(mlir.contains("stablehlo.divide"), "groupNorm must divide by the std")
assertTrue(mlir.contains("stablehlo.broadcast_in_dim"), "groupNorm must broadcast reduced stats back")
Expand All @@ -68,9 +71,9 @@ class GroupNormConverterTest {
val mlir = module.content

assertFalse(mlir.contains("@group_norm"))
assertFalse(mlir.contains("custom_call"))
assertTrue(mlir.contains("stablehlo.reshape"))
assertTrue(mlir.contains("@reduce_mean"))
assertTrue(mlir.contains("@reduce_variance"))
assertTrue(mlir.contains("stablehlo.reduce("))
assertTrue(mlir.contains("stablehlo.sqrt"))
assertTrue(mlir.contains("stablehlo.divide"))
}
Expand Down
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