[Mlir-commits] [mlir] [MLIR][Vector]Generalize DropUnitDimFromElementwiseOps (PR #92934)
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llvmlistbot at llvm.org
Tue May 21 10:04:06 PDT 2024
llvmbot wrote:
<!--LLVM PR SUMMARY COMMENT-->
@llvm/pr-subscribers-mlir
Author: Hugo Trachino (nujaa)
<details>
<summary>Changes</summary>
Generalizes `DropUnitDimFromElementwiseOps` to support inner unit dimensions.
discussed [here](https://discourse.llvm.org/t/mlir-for-arm-sme-vectorizing-matmul-like-ops-as-part-of-a-broader-program/78603).
---
Full diff: https://github.com/llvm/llvm-project/pull/92934.diff
2 Files Affected:
- (modified) mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp (+27-23)
- (modified) mlir/test/Dialect/Vector/vector-transfer-flatten.mlir (+20)
``````````diff
diff --git a/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp b/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp
index f29eba90c3ceb..e772d4bbea311 100644
--- a/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp
+++ b/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp
@@ -1607,7 +1607,23 @@ struct ChainedReduction final : OpRewritePattern<vector::ReductionOp> {
}
};
-/// For vectors with either leading or trailing unit dim, replaces:
+FailureOr<VectorType> dropNonScalableUnitDimType(VectorType VT) {
+ VectorType newVT = VT;
+ int removed = 0;
+ auto shape = VT.getShape();
+ for (unsigned i = 0; i < shape.size(); i++) {
+ if (shape[i] == 1 && !VT.getScalableDims()[i]) {
+ newVT = VectorType::Builder(newVT).dropDim(i - removed);
+ removed++;
+ }
+ }
+
+ if (removed == 0)
+ return failure();
+ return newVT;
+}
+
+/// For vectors with at least an unit dim, replaces:
/// elementwise(a, b)
/// with:
/// sc_a = shape_cast(a)
@@ -1652,42 +1668,30 @@ struct DropUnitDimFromElementwiseOps final
// guaranteed to have identical shapes (with some exceptions such as
// `arith.select`) and it suffices to only check one of them.
auto sourceVectorType = dyn_cast<VectorType>(op->getOperand(0).getType());
- if (!sourceVectorType)
- return failure();
- if (sourceVectorType.getRank() < 2)
- return failure();
-
- bool hasTrailingDimUnitFixed =
- ((sourceVectorType.getShape().back() == 1) &&
- (!sourceVectorType.getScalableDims().back()));
- bool hasLeadingDimUnitFixed =
- ((sourceVectorType.getShape().front() == 1) &&
- (!sourceVectorType.getScalableDims().front()));
- if (!hasLeadingDimUnitFixed && !hasTrailingDimUnitFixed)
+ if (!sourceVectorType || sourceVectorType.getRank() < 2)
return failure();
- // Drop leading/trailing unit dim by applying vector.shape_cast to all
- // operands
- int64_t dim = hasLeadingDimUnitFixed ? 0 : sourceVectorType.getRank() - 1;
-
SmallVector<Value> newOperands;
auto loc = op->getLoc();
for (auto operand : op->getOperands()) {
auto opVectorType = cast<VectorType>(operand.getType());
- VectorType newVType = VectorType::Builder(opVectorType).dropDim(dim);
- auto opSC = rewriter.create<vector::ShapeCastOp>(loc, newVType, operand);
+ auto newVType = dropNonScalableUnitDimType(opVectorType);
+ if (failed(newVType)) {
+ return failure();
+ }
+ auto opSC =
+ rewriter.create<vector::ShapeCastOp>(loc, newVType.value(), operand);
newOperands.push_back(opSC);
}
VectorType newResultVectorType =
- VectorType::Builder(resultVectorType).dropDim(dim);
- // Create an updated elementwise Op without leading/trailing unit dim
+ dropNonScalableUnitDimType(resultVectorType).value();
+ // Create an updated elementwise Op without unit dim
Operation *elementwiseOp =
rewriter.create(loc, op->getName().getIdentifier(), newOperands,
newResultVectorType, op->getAttrs());
- // Restore the leading/trailing unit dim by applying vector.shape_cast
- // to the result
+ // Restore the unit dim by applying vector.shape_cast to the result
rewriter.replaceOpWithNewOp<ShapeCastOp>(op, resultVectorType,
elementwiseOp->getResult(0));
diff --git a/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir b/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
index 788ae9ac044ed..03c19742355bf 100644
--- a/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
+++ b/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
@@ -459,6 +459,26 @@ func.func @fold_unit_dims_entirely(%arg0 : vector<8xi32>,
// CHECK-128B-LABEL: func @fold_unit_dims_entirely(
// CHECK-128B-NOT: memref.collapse_shape
+// -----
+
+func.func @fold_unit_center_dim_scalable(%arg0 : vector<8x1x[1]xf128>,
+ %arg1 : vector<1x8x[1]xf128>) -> vector<8x[1]xf128> {
+ %sc_arg1 = vector.shape_cast %arg1 : vector<1x8x[1]xf128> to vector<8x1x[1]xf128>
+ %add = arith.mulf %arg0, %sc_arg1 : vector<8x1x[1]xf128>
+ %res = vector.shape_cast %add : vector<8x1x[1]xf128> to vector<8x[1]xf128>
+ return %res : vector<8x[1]xf128>
+}
+
+// CHECK-LABEL: func.func @fold_unit_center_dim_scalable(
+// CHECK-SAME: %[[VAL_0:.*]]: vector<8x1x[1]xf128>,
+// CHECK-SAME: %[[VAL_1:.*]]: vector<1x8x[1]xf128>) -> vector<8x[1]xf128> {
+// CHECK: %[[VAL_2:.*]] = vector.shape_cast %[[VAL_0]] : vector<8x1x[1]xf128> to vector<8x[1]xf128>
+// CHECK: %[[VAL_3:.*]] = vector.shape_cast %[[VAL_1]] : vector<1x8x[1]xf128> to vector<8x[1]xf128>
+// CHECK: %[[VAL_4:.*]] = arith.mulf %[[VAL_2]], %[[VAL_3]] : vector<8x[1]xf128>
+// CHECK: return %[[VAL_4]] : vector<8x[1]xf128>
+
+
+
// -----
``````````
</details>
https://github.com/llvm/llvm-project/pull/92934
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