[Mlir-commits] [mlir] Revert "[MLIR][Vector] Generalize DropUnitDimFromElementwiseOps to non leading / trailing dimensions." (PR #97652)
Han-Chung Wang
llvmlistbot at llvm.org
Wed Jul 3 16:03:28 PDT 2024
https://github.com/hanhanW created https://github.com/llvm/llvm-project/pull/97652
Reverts llvm/llvm-project#92934 because it breaks some lowering. To repro: `mlir-opt -test-vector-transfer-flatten-patterns ~/repro.mlir`
```mlir
func.func @unit_dim_folding(%arg0: vector<1x1xf32>) -> vector<1x1xf32> {
%cst = arith.constant dense<0.000000e+00> : vector<1x1xf32>
%0 = arith.mulf %arg0, %cst : vector<1x1xf32>
return %0 : vector<1x1xf32>
}
```
>From 68b8f5f684395f5057731f1dc67d27493d7660fa Mon Sep 17 00:00:00 2001
From: Han-Chung Wang <hanhan0912 at gmail.com>
Date: Wed, 3 Jul 2024 16:02:17 -0700
Subject: [PATCH] =?UTF-8?q?Revert=20"[MLIR][Vector]=20Generalize=20DropUni?=
=?UTF-8?q?tDimFromElementwiseOps=20to=20non=20leadin=E2=80=A6"?=
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This reverts commit 2c06fb899966b49ff0fe4adf55fceb7d1941fbca.
---
.../Vector/Transforms/VectorTransforms.cpp | 55 +++++++++----------
.../Vector/vector-transfer-flatten.mlir | 36 ------------
2 files changed, 26 insertions(+), 65 deletions(-)
diff --git a/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp b/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp
index c7d3022eff4d3..da5954b70a2ec 100644
--- a/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp
+++ b/mlir/lib/Dialect/Vector/Transforms/VectorTransforms.cpp
@@ -1622,27 +1622,7 @@ struct ChainedReduction final : OpRewritePattern<vector::ReductionOp> {
}
};
-// Scalable unit dimensions are not supported. Folding such dimensions would
-// require "shifting" the scalable flag onto some other fixed-width dim (e.g.
-// vector<[1]x4xf32> -> vector<[4]xf32>). This could be implemented in the
-// future.
-static VectorType dropNonScalableUnitDimFromType(VectorType inVecTy) {
- auto inVecShape = inVecTy.getShape();
- SmallVector<int64_t> newShape;
- SmallVector<bool> newScalableDims;
- for (auto [dim, isScalable] :
- llvm::zip_equal(inVecShape, inVecTy.getScalableDims())) {
- if (dim == 1 && !isScalable)
- continue;
-
- newShape.push_back(dim);
- newScalableDims.push_back(isScalable);
- }
-
- return VectorType::get(newShape, inVecTy.getElementType(), newScalableDims);
-}
-
-/// For vectors with at least an unit dim, replaces:
+/// For vectors with either leading or trailing unit dim, replaces:
/// elementwise(a, b)
/// with:
/// sc_a = shape_cast(a)
@@ -1654,16 +1634,20 @@ static VectorType dropNonScalableUnitDimFromType(VectorType inVecTy) {
/// required to be rank > 1.
///
/// Ex:
+/// ```
/// %mul = arith.mulf %B_row, %A_row : vector<1x[4]xf32>
/// %cast = vector.shape_cast %mul : vector<1x[4]xf32> to vector<[4]xf32>
+/// ```
///
/// gets converted to:
///
+/// ```
/// %B_row_sc = vector.shape_cast %B_row : vector<1x[4]xf32> to vector<[4]xf32>
/// %A_row_sc = vector.shape_cast %A_row : vector<1x[4]xf32> to vector<[4]xf32>
/// %mul = arith.mulf %B_row_sc, %A_row_sc : vector<[4]xf32>
/// %cast_new = vector.shape_cast %mul : vector<[4]xf32> to vector<1x[4]xf32>
/// %cast = vector.shape_cast %cast_new : vector<1x[4]xf32> to vector<[4]xf32>
+/// ```
///
/// Patterns for folding shape_casts should instantly eliminate `%cast_new` and
/// `%cast`.
@@ -1683,29 +1667,42 @@ 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 || sourceVectorType.getRank() < 2)
+ 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)
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());
- auto newVType = dropNonScalableUnitDimFromType(opVectorType);
- if (newVType == opVectorType)
- return rewriter.notifyMatchFailure(op, "No unit dimension to remove.");
-
+ VectorType newVType = VectorType::Builder(opVectorType).dropDim(dim);
auto opSC = rewriter.create<vector::ShapeCastOp>(loc, newVType, operand);
newOperands.push_back(opSC);
}
VectorType newResultVectorType =
- dropNonScalableUnitDimFromType(resultVectorType);
- // Create an updated elementwise Op without unit dim.
+ VectorType::Builder(resultVectorType).dropDim(dim);
+ // Create an updated elementwise Op without leading/trailing unit dim
Operation *elementwiseOp =
rewriter.create(loc, op->getName().getIdentifier(), newOperands,
newResultVectorType, op->getAttrs());
- // Restore the unit dim by applying vector.shape_cast to the result.
+ // Restore the leading/trailing 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 3a5041fca53fc..5fd3cbd54aa58 100644
--- a/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
+++ b/mlir/test/Dialect/Vector/vector-transfer-flatten.mlir
@@ -604,42 +604,6 @@ func.func @fold_unit_dims_entirely(%arg0 : vector<8xi32>,
// -----
-func.func @fold_inner_unit_dim(%arg0 : vector<8x1x3xf128>,
- %arg1 : vector<1x8x3xf128>) -> vector<8x3xf128> {
- %sc_arg1 = vector.shape_cast %arg1 : vector<1x8x3xf128> to vector<8x1x3xf128>
- %mul = arith.mulf %arg0, %sc_arg1 : vector<8x1x3xf128>
- %res = vector.shape_cast %mul : vector<8x1x3xf128> to vector<8x3xf128>
- return %res : vector<8x3xf128>
-}
-
-// CHECK-LABEL: func.func @fold_inner_unit_dim(
-// CHECK-SAME: %[[VAL_0:.*]]: vector<8x1x3xf128>,
-// CHECK-SAME: %[[VAL_1:.*]]: vector<1x8x3xf128>) -> vector<8x3xf128> {
-// CHECK: %[[VAL_2:.*]] = vector.shape_cast %[[VAL_0]] : vector<8x1x3xf128> to vector<8x3xf128>
-// CHECK: %[[VAL_3:.*]] = vector.shape_cast %[[VAL_1]] : vector<1x8x3xf128> to vector<8x3xf128>
-// CHECK: %[[VAL_4:.*]] = arith.mulf %[[VAL_2]], %[[VAL_3]] : vector<8x3xf128>
-// CHECK: return %[[VAL_4]] : vector<8x3xf128>
-
-// -----
-
-func.func @fold_inner_unit_dim_scalable(%arg0 : vector<8x1x[1]x3xf128>,
- %arg1 : vector<1x8x[1]x3xf128>) -> vector<8x[1]x3xf128> {
- %sc_arg1 = vector.shape_cast %arg1 : vector<1x8x[1]x3xf128> to vector<8x1x[1]x3xf128>
- %mul = arith.mulf %arg0, %sc_arg1 : vector<8x1x[1]x3xf128>
- %res = vector.shape_cast %mul : vector<8x1x[1]x3xf128> to vector<8x[1]x3xf128>
- return %res : vector<8x[1]x3xf128>
-}
-
-// CHECK-LABEL: func.func @fold_inner_unit_dim_scalable(
-// CHECK-SAME: %[[VAL_0:.*]]: vector<8x1x[1]x3xf128>,
-// CHECK-SAME: %[[VAL_1:.*]]: vector<1x8x[1]x3xf128>) -> vector<8x[1]x3xf128> {
-// CHECK: %[[VAL_2:.*]] = vector.shape_cast %[[VAL_0]] : vector<8x1x[1]x3xf128> to vector<8x[1]x3xf128>
-// CHECK: %[[VAL_3:.*]] = vector.shape_cast %[[VAL_1]] : vector<1x8x[1]x3xf128> to vector<8x[1]x3xf128>
-// CHECK: %[[VAL_4:.*]] = arith.mulf %[[VAL_2]], %[[VAL_3]] : vector<8x[1]x3xf128>
-// CHECK: return %[[VAL_4]] : vector<8x[1]x3xf128>
-
-// -----
-
func.func @negative_out_of_bound_transfer_read(
%arg : memref<?x4x3x2xi8, strided<[24, 6, 2, 1], offset: ?>>) -> vector<5x4x3x2xi8> {
%c0 = arith.constant 0 : index
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