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support scalar reduction in mhlo-canonicalize-reduction pass #39

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Mar 12, 2024
Merged

support scalar reduction in mhlo-canonicalize-reduction pass #39

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12 changes: 4 additions & 8 deletions ...r/xla/mlir_hlo/mhlo/transforms/mhlo_canonicalize_reduction/mhlo_canonicalize_reduction.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -187,12 +187,10 @@ struct HloCanonicalizeReductionPass
// column reduction having following form:
// Suppose nelems = ProdutionOp(ShapeOp(I)), We convert I into
// shape `[nelems, 1]`.
// TODO(disc): this may have performance issue. Implements a reduce to
// scalar schedule if necessary.
newOperandDims.push_back(nelemToReduce);
newOperandDims.push_back(nelemToKeep);
attr = DenseIntElementsAttr::get(
RankedTensorType::get({1}, b.getIntegerType(64)), {0ll});
RankedTensorType::get({2}, b.getIntegerType(64)), {0ll, 1ll});
} else if (dimsToReduce[0] == 0) {
// case a) column reduction
newOperandDims.push_back(nelemToReduce);
Expand All @@ -219,17 +217,15 @@ struct HloCanonicalizeReductionPass
elemTy),
operand, newOperandShape));
}
auto newOp =
b.create<ReduceOp>(loc, newOperands, op.getInitValues(), attr);
auto newOp = b.create<ReduceOp>(loc, newOperands, op.getInitValues(), attr);
newOp.getBody().takeBody(op.getBody());

SmallVector<Value, 4> newResults;
if (dimsToKeep.empty()) {
// case c) reduce to scalar
// reshape rank 1 tensor with size 1 to a rank 0 tensor
for (Value result : newOp.getResults()) {
newResults.push_back(b.create<ReshapeOp>(
loc, RankedTensorType::get({}, elemTy), result));
for (Value result: newOp.getResults()) {
newResults.push_back(result);
}
} else {
SmallVector<Value, 4> resultDims;
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