[Mlir-commits] [mlir] a53cd03 - [mlir][Vector] Extend xfer drop unit dim patterns
Diego Caballero
llvmlistbot at llvm.org
Tue May 23 13:58:58 PDT 2023
Author: Diego Caballero
Date: 2023-05-23T20:58:51Z
New Revision: a53cd03deac5e6272e9dae88a90cd51410d312d5
URL: https://github.com/llvm/llvm-project/commit/a53cd03deac5e6272e9dae88a90cd51410d312d5
DIFF: https://github.com/llvm/llvm-project/commit/a53cd03deac5e6272e9dae88a90cd51410d312d5.diff
LOG: [mlir][Vector] Extend xfer drop unit dim patterns
This patch extends the transfer drop unit dim patterns to support cases where the vector shape should also be reduced
(e.g., transfer_read(memref<1x4x1xf32>, vector<1x4x1xf32>) -> transfer_read(memref<4xf32>, vector<4xf32>).
Reviewed By: hanchung, pzread
Differential Revision: https://reviews.llvm.org/D151007
Added:
Modified:
mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
mlir/test/Dialect/Vector/vector-transfer-drop-unit-dims-patterns.mlir
Removed:
################################################################################
diff --git a/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp b/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
index af0fcd097028d..0e9dcf27c5585 100644
--- a/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
+++ b/mlir/lib/Dialect/Vector/Transforms/VectorTransferOpTransforms.cpp
@@ -63,6 +63,7 @@ class TransferOptimization {
std::vector<Operation *> opToErase;
};
+} // namespace
/// Return true if there is a path from start operation to dest operation,
/// otherwise return false. The operations have to be in the same region.
bool TransferOptimization::isReachable(Operation *start, Operation *dest) {
@@ -288,14 +289,25 @@ static int getReducedRank(ArrayRef<int64_t> shape) {
return llvm::count_if(shape, [](int64_t dimSize) { return dimSize != 1; });
}
+/// Returns a copy of `shape` without unit dims.
+static SmallVector<int64_t> getReducedShape(ArrayRef<int64_t> shape) {
+ SmallVector<int64_t> reducedShape;
+ llvm::copy_if(shape, std::back_inserter(reducedShape),
+ [](int64_t dimSize) { return dimSize != 1; });
+ return reducedShape;
+}
+
/// Returns true if all values are `arith.constant 0 : index`
static bool isZero(Value v) {
auto cst = v.getDefiningOp<arith::ConstantIndexOp>();
return cst && cst.value() == 0;
}
-/// Rewrites vector.transfer_read ops where the source has unit dims, by
-/// inserting a memref.subview dropping those unit dims.
+namespace {
+
+/// Rewrites `vector.transfer_read` ops where the source has unit dims, by
+/// inserting a memref.subview dropping those unit dims. The vector shapes are
+/// also reduced accordingly.
class TransferReadDropUnitDimsPattern
: public OpRewritePattern<vector::TransferReadOp> {
using OpRewritePattern::OpRewritePattern;
@@ -317,12 +329,15 @@ class TransferReadDropUnitDimsPattern
return failure();
if (!transferReadOp.getPermutationMap().isMinorIdentity())
return failure();
+ // Check if the source shape can be further reduced.
int reducedRank = getReducedRank(sourceType.getShape());
if (reducedRank == sourceType.getRank())
- return failure(); // The source shape can't be further reduced.
- if (reducedRank != vectorType.getRank())
- return failure(); // This pattern requires the vector shape to match the
- // reduced source shape.
+ return failure();
+ // Check if the reduced vector shape matches the reduced source shape.
+ // Otherwise, this case is not supported yet.
+ int vectorReducedRank = getReducedRank(vectorType.getShape());
+ if (reducedRank != vectorReducedRank)
+ return failure();
if (llvm::any_of(transferReadOp.getIndices(),
[](Value v) { return !isZero(v); }))
return failure();
@@ -331,14 +346,22 @@ class TransferReadDropUnitDimsPattern
Value c0 = rewriter.create<arith::ConstantIndexOp>(loc, 0);
SmallVector<Value> zeros(reducedRank, c0);
auto identityMap = rewriter.getMultiDimIdentityMap(reducedRank);
- rewriter.replaceOpWithNewOp<vector::TransferReadOp>(
- transferReadOp, vectorType, reducedShapeSource, zeros, identityMap);
+ auto reducedVectorType = VectorType::get(
+ getReducedShape(vectorType.getShape()), vectorType.getElementType());
+
+ auto newTransferReadOp = rewriter.create<vector::TransferReadOp>(
+ loc, reducedVectorType, reducedShapeSource, zeros, identityMap);
+ auto shapeCast = rewriter.createOrFold<vector::ShapeCastOp>(
+ loc, vectorType, newTransferReadOp);
+ rewriter.replaceOp(transferReadOp, shapeCast);
+
return success();
}
};
-/// Rewrites vector.transfer_write ops where the "source" (i.e. destination) has
-/// unit dims, by inserting a memref.subview dropping those unit dims.
+/// Rewrites `vector.transfer_write` ops where the "source" (i.e. destination)
+/// has unit dims, by inserting a `memref.subview` dropping those unit dims. The
+/// vector shapes are also reduced accordingly.
class TransferWriteDropUnitDimsPattern
: public OpRewritePattern<vector::TransferWriteOp> {
using OpRewritePattern::OpRewritePattern;
@@ -360,12 +383,15 @@ class TransferWriteDropUnitDimsPattern
return failure();
if (!transferWriteOp.getPermutationMap().isMinorIdentity())
return failure();
+ // Check if the destination shape can be further reduced.
int reducedRank = getReducedRank(sourceType.getShape());
if (reducedRank == sourceType.getRank())
- return failure(); // The source shape can't be further reduced.
- if (reducedRank != vectorType.getRank())
- return failure(); // This pattern requires the vector shape to match the
- // reduced source shape.
+ return failure();
+ // Check if the reduced vector shape matches the reduced destination shape.
+ // Otherwise, this case is not supported yet.
+ int vectorReducedRank = getReducedRank(vectorType.getShape());
+ if (reducedRank != vectorReducedRank)
+ return failure();
if (llvm::any_of(transferWriteOp.getIndices(),
[](Value v) { return !isZero(v); }))
return failure();
@@ -374,12 +400,20 @@ class TransferWriteDropUnitDimsPattern
Value c0 = rewriter.create<arith::ConstantIndexOp>(loc, 0);
SmallVector<Value> zeros(reducedRank, c0);
auto identityMap = rewriter.getMultiDimIdentityMap(reducedRank);
+ VectorType reducedVectorType = VectorType::get(
+ getReducedShape(vectorType.getShape()), vectorType.getElementType());
+
+ auto shapeCast = rewriter.createOrFold<vector::ShapeCastOp>(
+ loc, reducedVectorType, vector);
rewriter.replaceOpWithNewOp<vector::TransferWriteOp>(
- transferWriteOp, vector, reducedShapeSource, zeros, identityMap);
+ transferWriteOp, shapeCast, reducedShapeSource, zeros, identityMap);
+
return success();
}
};
+} // namespace
+
/// Return true if the memref type has its inner dimension matching the given
/// shape. Otherwise return false.
static int64_t hasMatchingInnerContigousShape(MemRefType memrefType,
@@ -439,6 +473,8 @@ checkAndCollapseInnerZeroIndices(ValueRange indices, int64_t firstDimToCollapse,
return success();
}
+namespace {
+
/// Rewrites contiguous row-major vector.transfer_read ops by inserting
/// memref.collapse_shape on the source so that the resulting
/// vector.transfer_read has a 1D source. Requires the source shape to be
@@ -732,6 +768,7 @@ class RewriteScalarWrite : public OpRewritePattern<vector::TransferWriteOp> {
return success();
}
};
+
} // namespace
void mlir::vector::transferOpflowOpt(RewriterBase &rewriter,
diff --git a/mlir/test/Dialect/Vector/vector-transfer-drop-unit-dims-patterns.mlir b/mlir/test/Dialect/Vector/vector-transfer-drop-unit-dims-patterns.mlir
index e4e2e3b69c67b..3efa06948f546 100644
--- a/mlir/test/Dialect/Vector/vector-transfer-drop-unit-dims-patterns.mlir
+++ b/mlir/test/Dialect/Vector/vector-transfer-drop-unit-dims-patterns.mlir
@@ -15,6 +15,14 @@ func.func @transfer_read_rank_reducing(
// CHECK-SAME: memref<1x1x3x2xi8, {{.*}}> to memref<3x2xi8, {{.*}}>
// CHECK: vector.transfer_read %[[SUBVIEW]]
+transform.sequence failures(propagate) {
+^bb1(%module_op: !pdl.operation):
+ transform.vector.apply_rank_reducing_subview_patterns %module_op
+ : (!pdl.operation) -> !pdl.operation
+}
+
+// -----
+
func.func @transfer_write_rank_reducing(%arg : memref<1x1x3x2xi8, strided<[6, 6, 2, 1], offset: ?>>, %vec : vector<3x2xi8>) {
%c0 = arith.constant 0 : index
vector.transfer_write %vec, %arg [%c0, %c0, %c0, %c0] :
@@ -28,6 +36,97 @@ func.func @transfer_write_rank_reducing(%arg : memref<1x1x3x2xi8, strided<[6, 6,
// CHECK-SAME: memref<1x1x3x2xi8, {{.*}}> to memref<3x2xi8, {{.*}}>
// CHECK: vector.transfer_write %{{.*}}, %[[SUBVIEW]]
+transform.sequence failures(propagate) {
+^bb1(%module_op: !pdl.operation):
+ transform.vector.apply_rank_reducing_subview_patterns %module_op
+ : (!pdl.operation) -> !pdl.operation
+}
+
+// -----
+
+func.func @transfer_read_and_vector_rank_reducing(
+ %arg : memref<1x1x3x2x1xf32>) -> vector<3x2x1xf32> {
+ %c0 = arith.constant 0 : index
+ %cst = arith.constant 0.0 : f32
+ %v = vector.transfer_read %arg[%c0, %c0, %c0, %c0, %c0], %cst :
+ memref<1x1x3x2x1xf32>, vector<3x2x1xf32>
+ return %v : vector<3x2x1xf32>
+}
+
+// CHECK-LABEL: func @transfer_read_and_vector_rank_reducing
+// CHECK-SAME: %[[ARG:.+]]: memref<1x1x3x2x1xf32>
+// CHECK: %[[SUBVIEW:.+]] = memref.subview %[[ARG]][0, 0, 0, 0, 0] [1, 1, 3, 2, 1] [1, 1, 1, 1, 1]
+// CHECK-SAME: memref<1x1x3x2x1xf32> to memref<3x2xf32>
+// CHECK: vector.transfer_read %[[SUBVIEW]]{{.*}} {in_bounds = [true, true]} : memref<3x2xf32>, vector<3x2xf32>
+
+transform.sequence failures(propagate) {
+^bb1(%module_op: !pdl.operation):
+ transform.vector.apply_rank_reducing_subview_patterns %module_op
+ : (!pdl.operation) -> !pdl.operation
+}
+
+// -----
+
+func.func @transfer_write_and_vector_rank_reducing(
+ %arg : memref<1x1x3x2x1xf32>,
+ %vec : vector<3x2x1xf32>) {
+ %c0 = arith.constant 0 : index
+ vector.transfer_write %vec, %arg [%c0, %c0, %c0, %c0, %c0] :
+ vector<3x2x1xf32>, memref<1x1x3x2x1xf32>
+ return
+}
+
+// CHECK-LABEL: func @transfer_write_and_vector_rank_reducing
+// CHECK-SAME: %[[ARG:.+]]: memref<1x1x3x2x1xf32>
+// CHECK: %[[SUBVIEW:.+]] = memref.subview %[[ARG]][0, 0, 0, 0, 0] [1, 1, 3, 2, 1] [1, 1, 1, 1, 1]
+// CHECK-SAME: memref<1x1x3x2x1xf32> to memref<3x2xf32>
+// CHECK: vector.transfer_write %{{.*}}, %[[SUBVIEW]]{{.*}} {in_bounds = [true, true]} : vector<3x2xf32>, memref<3x2xf32>
+
+transform.sequence failures(propagate) {
+^bb1(%module_op: !transform.any_op):
+ transform.vector.apply_rank_reducing_subview_patterns %module_op
+ : (!transform.any_op) -> !transform.any_op
+}
+
+// -----
+
+func.func @transfer_read_and_vector_rank_reducing_to_0d(
+ %arg : memref<1x1x1x1x1xf32>) -> vector<1x1x1xf32> {
+ %c0 = arith.constant 0 : index
+ %cst = arith.constant 0.0 : f32
+ %v = vector.transfer_read %arg[%c0, %c0, %c0, %c0, %c0], %cst :
+ memref<1x1x1x1x1xf32>, vector<1x1x1xf32>
+ return %v : vector<1x1x1xf32>
+}
+
+// CHECK-LABEL: func @transfer_read_and_vector_rank_reducing_to_0d
+// CHECK-SAME: %[[MEMREF:.+]]: memref<1x1x1x1x1xf32>
+// CHECK: %[[SUBVIEW:.+]] = memref.subview %[[MEMREF]][0, 0, 0, 0, 0] [1, 1, 1, 1, 1] [1, 1, 1, 1, 1] : memref<1x1x1x1x1xf32> to memref<f32>
+// CHECK: %[[READ:.+]] = vector.transfer_read %[[SUBVIEW]]{{.*}} : memref<f32>, vector<f32>
+// CHECK: vector.shape_cast %[[READ]] : vector<f32> to vector<1x1x1xf32>
+
+transform.sequence failures(propagate) {
+^bb1(%module_op: !pdl.operation):
+ transform.vector.apply_rank_reducing_subview_patterns %module_op
+ : (!pdl.operation) -> !pdl.operation
+}
+
+// -----
+
+func.func @transfer_write_and_vector_rank_reducing_to_0d(
+ %arg : memref<1x1x1x1x1xf32>,
+ %vec : vector<1x1x1xf32>) {
+ %c0 = arith.constant 0 : index
+ vector.transfer_write %vec, %arg [%c0, %c0, %c0, %c0, %c0] :
+ vector<1x1x1xf32>, memref<1x1x1x1x1xf32>
+ return
+}
+
+// CHECK-LABEL: func @transfer_write_and_vector_rank_reducing_to_0d
+// CHECK-SAME: %[[MEMREF:.+]]: memref<1x1x1x1x1xf32>, %[[VECTOR:.+]]: vector<1x1x1xf32>
+// CHECK: %[[SUBVIEW:.+]] = memref.subview %[[MEMREF]][0, 0, 0, 0, 0] [1, 1, 1, 1, 1] [1, 1, 1, 1, 1] : memref<1x1x1x1x1xf32> to memref<f32>
+// CHECK: %[[SHCAST:.+]] = vector.shape_cast %[[VECTOR]] : vector<1x1x1xf32> to vector<f32>
+// CHECK: vector.transfer_write %[[SHCAST]], %[[SUBVIEW]]{{.*}} : vector<f32>, memref<f32>
transform.sequence failures(propagate) {
^bb1(%module_op: !transform.any_op):
More information about the Mlir-commits
mailing list