[mlir][SCF] Use Affine ops for indexing math. #108450
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MaheshRavishankar
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For index type of induction variable, the indexing math is better represented using affine ops such as `affine.delinearize_index`. This also further demonstrates that some of these `affine` ops might need to move to a different dialect. For one these ops only support `IndexType` when they should be able to work with any integer type. Signed-off-by: MaheshRavishankar <[email protected]>
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@llvm/pr-subscribers-mlir-scf @llvm/pr-subscribers-mlir Author: None (MaheshRavishankar) ChangesFor index type of induction variable, the indexing math is better represented using affine ops such as This also further demonstrates that some of these Patch is 47.09 KiB, truncated to 20.00 KiB below, full version: https://github.com/llvm/llvm-project/pull/108450.diff 8 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Affine/Passes.td b/mlir/include/mlir/Dialect/Affine/Passes.td
index 1036e93a039240..b08e803345f76e 100644
--- a/mlir/include/mlir/Dialect/Affine/Passes.td
+++ b/mlir/include/mlir/Dialect/Affine/Passes.td
@@ -394,7 +394,7 @@ def LoopCoalescing : Pass<"affine-loop-coalescing", "func::FuncOp"> {
let summary = "Coalesce nested loops with independent bounds into a single "
"loop";
let constructor = "mlir::affine::createLoopCoalescingPass()";
- let dependentDialects = ["arith::ArithDialect"];
+ let dependentDialects = ["affine::AffineDialect","arith::ArithDialect"];
}
def SimplifyAffineStructures : Pass<"affine-simplify-structures", "func::FuncOp"> {
diff --git a/mlir/include/mlir/Dialect/SCF/Transforms/Passes.td b/mlir/include/mlir/Dialect/SCF/Transforms/Passes.td
index 9b29affb97c432..53d1ae10dc87d8 100644
--- a/mlir/include/mlir/Dialect/SCF/Transforms/Passes.td
+++ b/mlir/include/mlir/Dialect/SCF/Transforms/Passes.td
@@ -56,6 +56,7 @@ def SCFParallelLoopFusion : Pass<"scf-parallel-loop-fusion"> {
def TestSCFParallelLoopCollapsing : Pass<"test-scf-parallel-loop-collapsing"> {
let summary = "Test parallel loops collapsing transformation";
let constructor = "mlir::createTestSCFParallelLoopCollapsingPass()";
+ let dependentDialects = ["affine::AffineDialect"];
let description = [{
This pass is purely for testing the scf::collapseParallelLoops
transformation. The transformation does not have opinions on how a
diff --git a/mlir/lib/Dialect/SCF/Transforms/ParallelLoopCollapsing.cpp b/mlir/lib/Dialect/SCF/Transforms/ParallelLoopCollapsing.cpp
index 6ba7020e86fa67..358a3b38a4cd32 100644
--- a/mlir/lib/Dialect/SCF/Transforms/ParallelLoopCollapsing.cpp
+++ b/mlir/lib/Dialect/SCF/Transforms/ParallelLoopCollapsing.cpp
@@ -8,6 +8,7 @@
#include "mlir/Dialect/SCF/Transforms/Passes.h"
+#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/SCF/Utils/Utils.h"
#include "mlir/Transforms/RegionUtils.h"
diff --git a/mlir/lib/Dialect/SCF/Utils/Utils.cpp b/mlir/lib/Dialect/SCF/Utils/Utils.cpp
index a794a121d6267b..c9f0955256b9bf 100644
--- a/mlir/lib/Dialect/SCF/Utils/Utils.cpp
+++ b/mlir/lib/Dialect/SCF/Utils/Utils.cpp
@@ -12,6 +12,7 @@
#include "mlir/Dialect/SCF/Utils/Utils.h"
#include "mlir/Analysis/SliceAnalysis.h"
+#include "mlir/Dialect/Affine/IR/AffineOps.h"
#include "mlir/Dialect/Arith/IR/Arith.h"
#include "mlir/Dialect/Arith/Utils/Utils.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"
@@ -671,9 +672,26 @@ LogicalResult mlir::loopUnrollJamByFactor(scf::ForOp forOp,
return success();
}
+Range emitNormalizedLoopBoundsForIndexType(RewriterBase &rewriter, Location loc,
+ OpFoldResult lb, OpFoldResult ub,
+ OpFoldResult step) {
+ Range normalizedLoopBounds;
+ normalizedLoopBounds.offset = rewriter.getIndexAttr(0);
+ normalizedLoopBounds.stride = rewriter.getIndexAttr(1);
+ AffineExpr s0, s1, s2;
+ bindSymbols(rewriter.getContext(), s0, s1, s2);
+ AffineExpr e = (s1 - s0).ceilDiv(s2);
+ normalizedLoopBounds.size =
+ affine::makeComposedFoldedAffineApply(rewriter, loc, e, {lb, ub, step});
+ return normalizedLoopBounds;
+}
+
Range mlir::emitNormalizedLoopBounds(RewriterBase &rewriter, Location loc,
OpFoldResult lb, OpFoldResult ub,
OpFoldResult step) {
+ if (getType(lb) == rewriter.getIndexType()) {
+ return emitNormalizedLoopBoundsForIndexType(rewriter, loc, lb, ub, step);
+ }
// For non-index types, generate `arith` instructions
// Check if the loop is already known to have a constant zero lower bound or
// a constant one step.
@@ -714,9 +732,38 @@ Range mlir::emitNormalizedLoopBounds(RewriterBase &rewriter, Location loc,
return {newLowerBound, newUpperBound, newStep};
}
+static void denormalizeInductionVariableForIndexType(RewriterBase &rewriter,
+ Location loc,
+ Value normalizedIv,
+ OpFoldResult origLb,
+ OpFoldResult origStep) {
+ AffineExpr d0, s0, s1;
+ bindSymbols(rewriter.getContext(), s0, s1);
+ bindDims(rewriter.getContext(), d0);
+ AffineExpr e = d0 * s1 + s0;
+ OpFoldResult denormalizedIv = affine::makeComposedFoldedAffineApply(
+ rewriter, loc, e, ArrayRef<OpFoldResult>{normalizedIv, origLb, origStep});
+ Value denormalizedIvVal =
+ getValueOrCreateConstantIndexOp(rewriter, loc, denormalizedIv);
+ SmallPtrSet<Operation *, 1> preservedUses;
+ // If an `affine.apply` operation is generated for denormalization, the use
+ // of `origLb` in those ops must not be replaced. These arent not generated
+ // when `orig_lb == 0` and `orig_step == 1`.
+ if (!isConstantIntValue(origLb, 0) || !isConstantIntValue(origStep, 1)) {
+ if (Operation *preservedUse = denormalizedIvVal.getDefiningOp()) {
+ preservedUses.insert(preservedUse);
+ }
+ }
+ rewriter.replaceAllUsesExcept(normalizedIv, denormalizedIvVal, preservedUses);
+}
+
void mlir::denormalizeInductionVariable(RewriterBase &rewriter, Location loc,
Value normalizedIv, OpFoldResult origLb,
OpFoldResult origStep) {
+ if (getType(origLb) == rewriter.getIndexType()) {
+ return denormalizeInductionVariableForIndexType(rewriter, loc, normalizedIv,
+ origLb, origStep);
+ }
Value denormalizedIv;
SmallPtrSet<Operation *, 2> preserve;
bool isStepOne = isConstantIntValue(origStep, 1);
@@ -739,10 +786,29 @@ void mlir::denormalizeInductionVariable(RewriterBase &rewriter, Location loc,
rewriter.replaceAllUsesExcept(normalizedIv, denormalizedIv, preserve);
}
+static OpFoldResult getProductOfIndexes(RewriterBase &rewriter, Location loc,
+ ArrayRef<OpFoldResult> values) {
+ assert(!values.empty() && "unexecpted empty array");
+ AffineExpr s0, s1;
+ bindSymbols(rewriter.getContext(), s0, s1);
+ AffineExpr mul = s0 * s1;
+ OpFoldResult products = rewriter.getIndexAttr(1);
+ for (auto v : values) {
+ products = affine::makeComposedFoldedAffineApply(
+ rewriter, loc, mul, ArrayRef<OpFoldResult>{products, v});
+ }
+ return products;
+}
+
/// Helper function to multiply a sequence of values.
static Value getProductOfIntsOrIndexes(RewriterBase &rewriter, Location loc,
ArrayRef<Value> values) {
assert(!values.empty() && "unexpected empty list");
+ if (getType(values.front()) == rewriter.getIndexType()) {
+ SmallVector<OpFoldResult> ofrs = getAsOpFoldResult(values);
+ OpFoldResult product = getProductOfIndexes(rewriter, loc, ofrs);
+ return getValueOrCreateConstantIndexOp(rewriter, loc, product);
+ }
std::optional<Value> productOf;
for (auto v : values) {
auto vOne = getConstantIntValue(v);
@@ -757,7 +823,7 @@ static Value getProductOfIntsOrIndexes(RewriterBase &rewriter, Location loc,
if (!productOf) {
productOf = rewriter
.create<arith::ConstantOp>(
- loc, rewriter.getOneAttr(values.front().getType()))
+ loc, rewriter.getOneAttr(getType(values.front())))
.getResult();
}
return productOf.value();
@@ -774,6 +840,16 @@ static Value getProductOfIntsOrIndexes(RewriterBase &rewriter, Location loc,
static std::pair<SmallVector<Value>, SmallPtrSet<Operation *, 2>>
delinearizeInductionVariable(RewriterBase &rewriter, Location loc,
Value linearizedIv, ArrayRef<Value> ubs) {
+
+ if (linearizedIv.getType() == rewriter.getIndexType()) {
+ Operation *delinearizedOp =
+ rewriter.create<affine::AffineDelinearizeIndexOp>(loc, linearizedIv,
+ ubs);
+ auto resultVals = llvm::map_to_vector(
+ delinearizedOp->getResults(), [](OpResult r) -> Value { return r; });
+ return {resultVals, SmallPtrSet<Operation *, 2>{delinearizedOp}};
+ }
+
SmallVector<Value> delinearizedIvs(ubs.size());
SmallPtrSet<Operation *, 2> preservedUsers;
diff --git a/mlir/test/Dialect/Affine/loop-coalescing.mlir b/mlir/test/Dialect/Affine/loop-coalescing.mlir
index 45dd299295f640..f6e7b21bc66aba 100644
--- a/mlir/test/Dialect/Affine/loop-coalescing.mlir
+++ b/mlir/test/Dialect/Affine/loop-coalescing.mlir
@@ -1,14 +1,15 @@
-// RUN: mlir-opt -split-input-file -allow-unregistered-dialect -affine-loop-coalescing --cse %s | FileCheck %s
+// RUN: mlir-opt -split-input-file -allow-unregistered-dialect -affine-loop-coalescing --cse --mlir-print-local-scope %s | FileCheck %s
// CHECK-LABEL: @one_3d_nest
func.func @one_3d_nest() {
// Capture original bounds. Note that for zero-based step-one loops, the
// upper bound is also the number of iterations.
- // CHECK: %[[orig_lb:.*]] = arith.constant 0
- // CHECK: %[[orig_step:.*]] = arith.constant 1
- // CHECK: %[[orig_ub_k:.*]] = arith.constant 3
- // CHECK: %[[orig_ub_i:.*]] = arith.constant 42
- // CHECK: %[[orig_ub_j:.*]] = arith.constant 56
+ // CHECK-DAG: %[[orig_lb:.*]] = arith.constant 0
+ // CHECK-DAG: %[[orig_step:.*]] = arith.constant 1
+ // CHECK-DAG: %[[orig_ub_k:.*]] = arith.constant 3
+ // CHECK-DAG: %[[orig_ub_i:.*]] = arith.constant 42
+ // CHECK-DAG: %[[orig_ub_j:.*]] = arith.constant 56
+ // CHECK-DAG: %[[range:.*]] = arith.constant 7056
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%c2 = arith.constant 2 : index
@@ -16,9 +17,6 @@ func.func @one_3d_nest() {
%c42 = arith.constant 42 : index
%c56 = arith.constant 56 : index
// The range of the new scf.
- // CHECK: %[[partial_range:.*]] = arith.muli %[[orig_ub_i]], %[[orig_ub_j]]
- // CHECK-NEXT:%[[range:.*]] = arith.muli %[[partial_range]], %[[orig_ub_k]]
-
// Updated loop bounds.
// CHECK: scf.for %[[i:.*]] = %[[orig_lb]] to %[[range]] step %[[orig_step]]
scf.for %i = %c0 to %c42 step %c1 {
@@ -26,13 +24,11 @@ func.func @one_3d_nest() {
// CHECK-NOT: scf.for
// Reconstruct original IVs from the linearized one.
- // CHECK: %[[orig_k:.*]] = arith.remsi %[[i]], %[[orig_ub_k]]
- // CHECK: %[[div:.*]] = arith.divsi %[[i]], %[[orig_ub_k]]
- // CHECK: %[[orig_j:.*]] = arith.remsi %[[div]], %[[orig_ub_j]]
- // CHECK: %[[orig_i:.*]] = arith.divsi %[[div]], %[[orig_ub_j]]
+ // CHECK: %[[delinearize:.+]]:3 = affine.delinearize_index %[[i]]
+ // CHECK-SAME: into (%[[orig_ub_i]], %[[orig_ub_j]], %[[orig_ub_k]])
scf.for %j = %c0 to %c56 step %c1 {
scf.for %k = %c0 to %c3 step %c1 {
- // CHECK: "use"(%[[orig_i]], %[[orig_j]], %[[orig_k]])
+ // CHECK: "use"(%[[delinearize]]#0, %[[delinearize]]#1, %[[delinearize]]#2)
"use"(%i, %j, %k) : (index, index, index) -> ()
}
}
@@ -40,6 +36,8 @@ func.func @one_3d_nest() {
return
}
+// -----
+
// Check that there is no chasing the replacement of value uses by ensuring
// multiple uses of loop induction variables get rewritten to the same values.
@@ -52,13 +50,10 @@ func.func @multi_use() {
scf.for %i = %c1 to %c10 step %c1 {
scf.for %j = %c1 to %c10 step %c1 {
scf.for %k = %c1 to %c10 step %c1 {
- // CHECK: %[[k_unshifted:.*]] = arith.remsi %[[iv]], %[[k_extent:.*]]
- // CHECK: %[[ij:.*]] = arith.divsi %[[iv]], %[[k_extent]]
- // CHECK: %[[j_unshifted:.*]] = arith.remsi %[[ij]], %[[j_extent:.*]]
- // CHECK: %[[i_unshifted:.*]] = arith.divsi %[[ij]], %[[j_extent]]
- // CHECK: %[[k:.*]] = arith.addi %[[k_unshifted]]
- // CHECK: %[[j:.*]] = arith.addi %[[j_unshifted]]
- // CHECK: %[[i:.*]] = arith.addi %[[i_unshifted]]
+ // CHECK: %[[delinearize:.+]]:3 = affine.delinearize_index %[[iv]]
+ // CHECK: %[[k:.*]] = affine.apply affine_map<(d0) -> (d0 + 1)>(%[[delinearize]]#2)
+ // CHECK: %[[j:.*]] = affine.apply affine_map<(d0) -> (d0 + 1)>(%[[delinearize]]#1)
+ // CHECK: %[[i:.*]] = affine.apply affine_map<(d0) -> (d0 + 1)>(%[[delinearize]]#0)
// CHECK: "use1"(%[[i]], %[[j]], %[[k]])
"use1"(%i,%j,%k) : (index,index,index) -> ()
@@ -72,12 +67,20 @@ func.func @multi_use() {
return
}
+// -----
+
func.func @unnormalized_loops() {
- // CHECK: %[[orig_step_i:.*]] = arith.constant 2
+ // Normalized lower bound and step for the outer scf.
+ // CHECK-DAG: %[[lb_i:.*]] = arith.constant 0
+ // CHECK-DAG: %[[step_i:.*]] = arith.constant 1
+ // CHECK-DAG: %[[orig_step_j_and_numiter_i:.*]] = arith.constant 3
+
+ // Number of iterations in the inner loop, the pattern is the same as above,
+ // only capture the final result.
+ // CHECK-DAG: %[[numiter_j:.*]] = arith.constant 4
+
+ // CHECK-DAG: %[[range:.*]] = arith.constant 12
- // CHECK: %[[orig_step_j_and_numiter_i:.*]] = arith.constant 3
- // CHECK: %[[orig_lb_i:.*]] = arith.constant 5
- // CHECK: %[[orig_lb_j:.*]] = arith.constant 7
%c2 = arith.constant 2 : index
%c3 = arith.constant 3 : index
%c5 = arith.constant 5 : index
@@ -85,28 +88,18 @@ func.func @unnormalized_loops() {
%c10 = arith.constant 10 : index
%c17 = arith.constant 17 : index
- // Normalized lower bound and step for the outer scf.
- // CHECK: %[[lb_i:.*]] = arith.constant 0
- // CHECK: %[[step_i:.*]] = arith.constant 1
-
- // Number of iterations in the inner loop, the pattern is the same as above,
- // only capture the final result.
- // CHECK: %[[numiter_j:.*]] = arith.constant 4
// New bounds of the outer scf.
- // CHECK: %[[range:.*]] = arith.muli %[[orig_step_j_and_numiter_i:.*]], %[[numiter_j]]
// CHECK: scf.for %[[i:.*]] = %[[lb_i]] to %[[range]] step %[[step_i]]
scf.for %i = %c5 to %c10 step %c2 {
// The inner loop has been removed.
// CHECK-NOT: scf.for
scf.for %j = %c7 to %c17 step %c3 {
// The IVs are rewritten.
- // CHECK: %[[normalized_j:.*]] = arith.remsi %[[i]], %[[numiter_j]]
- // CHECK: %[[normalized_i:.*]] = arith.divsi %[[i]], %[[numiter_j]]
- // CHECK: %[[scaled_j:.*]] = arith.muli %[[normalized_j]], %[[orig_step_j_and_numiter_i]]
- // CHECK: %[[orig_j:.*]] = arith.addi %[[scaled_j]], %[[orig_lb_j]]
- // CHECK: %[[scaled_i:.*]] = arith.muli %[[normalized_i]], %[[orig_step_i]]
- // CHECK: %[[orig_i:.*]] = arith.addi %[[scaled_i]], %[[orig_lb_i]]
+ // CHECK: %[[delinearize:.+]]:2 = affine.delinearize_index %[[i]]
+ // CHECK-SAME: into (%[[orig_step_j_and_numiter_i]], %[[numiter_j]])
+ // CHECK: %[[orig_j:.*]] = affine.apply affine_map<(d0) -> (d0 * 3 + 7)>(%[[delinearize]]#1)
+ // CHECK: %[[orig_i:.*]] = affine.apply affine_map<(d0) -> (d0 * 2 + 5)>(%[[delinearize]]#0)
// CHECK: "use"(%[[orig_i]], %[[orig_j]])
"use"(%i, %j) : (index, index) -> ()
}
@@ -114,20 +107,21 @@ func.func @unnormalized_loops() {
return
}
+// -----
+
func.func @noramalized_loops_with_yielded_iter_args() {
- // CHECK: %[[orig_lb:.*]] = arith.constant 0
- // CHECK: %[[orig_step:.*]] = arith.constant 1
- // CHECK: %[[orig_ub_k:.*]] = arith.constant 3
- // CHECK: %[[orig_ub_i:.*]] = arith.constant 42
- // CHECK: %[[orig_ub_j:.*]] = arith.constant 56
+ // CHECK-DAG: %[[orig_lb:.*]] = arith.constant 0
+ // CHECK-DAG: %[[orig_ub_i:.*]] = arith.constant 42
+ // CHECK-DAG: %[[orig_step:.*]] = arith.constant 1
+ // CHECK-DAG: %[[orig_ub_j:.*]] = arith.constant 56
+ // CHECK-DAG: %[[orig_ub_k:.*]] = arith.constant 3
+ // CHECK-DAG: %[[range:.*]] = arith.constant 7056
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
%c42 = arith.constant 42 : index
%c56 = arith.constant 56 : index
// The range of the new scf.
- // CHECK: %[[partial_range:.*]] = arith.muli %[[orig_ub_i]], %[[orig_ub_j]]
- // CHECK-NEXT:%[[range:.*]] = arith.muli %[[partial_range]], %[[orig_ub_k]]
// Updated loop bounds.
// CHECK: scf.for %[[i:.*]] = %[[orig_lb]] to %[[range]] step %[[orig_step]] iter_args(%[[VAL_1:.*]] = %[[orig_lb]]) -> (index) {
@@ -136,13 +130,10 @@ func.func @noramalized_loops_with_yielded_iter_args() {
// CHECK-NOT: scf.for
// Reconstruct original IVs from the linearized one.
- // CHECK: %[[orig_k:.*]] = arith.remsi %[[i]], %[[orig_ub_k]]
- // CHECK: %[[div:.*]] = arith.divsi %[[i]], %[[orig_ub_k]]
- // CHECK: %[[orig_j:.*]] = arith.remsi %[[div]], %[[orig_ub_j]]
- // CHECK: %[[orig_i:.*]] = arith.divsi %[[div]], %[[orig_ub_j]]
+ // CHECK: %[[delinearize:.+]]:3 = affine.delinearize_index %[[i]] into (%[[orig_ub_i]], %[[orig_ub_j]], %[[orig_ub_k]])
%1:1 = scf.for %j = %c0 to %c56 step %c1 iter_args(%arg1 = %arg0) -> (index){
%0:1 = scf.for %k = %c0 to %c3 step %c1 iter_args(%arg2 = %arg1) -> (index) {
- // CHECK: "use"(%[[orig_i]], %[[orig_j]], %[[orig_k]])
+ // CHECK: "use"(%[[delinearize]]#0, %[[delinearize]]#1, %[[delinearize]]#2)
"use"(%i, %j, %k) : (index, index, index) -> ()
// CHECK: scf.yield %[[VAL_1]] : index
scf.yield %arg2 : index
@@ -154,20 +145,21 @@ func.func @noramalized_loops_with_yielded_iter_args() {
return
}
+// -----
+
func.func @noramalized_loops_with_shuffled_yielded_iter_args() {
- // CHECK: %[[orig_lb:.*]] = arith.constant 0
- // CHECK: %[[orig_step:.*]] = arith.constant 1
- // CHECK: %[[orig_ub_k:.*]] = arith.constant 3
- // CHECK: %[[orig_ub_i:.*]] = arith.constant 42
- // CHECK: %[[orig_ub_j:.*]] = arith.constant 56
+ // CHECK-DAG: %[[orig_lb:.*]] = arith.constant 0
+ // CHECK-DAG: %[[orig_step:.*]] = arith.constant 1
+ // CHECK-DAG: %[[orig_ub_k:.*]] = arith.constant 3
+ // CHECK-DAG: %[[orig_ub_i:.*]] = arith.constant 42
+ // CHECK-DAG: %[[orig_ub_j:.*]] = arith.constant 56
%c0 = arith.constant 0 : index
%c1 = arith.constant 1 : index
%c3 = arith.constant 3 : index
%c42 = arith.constant 42 : index
%c56 = arith.constant 56 : index
// The range of the new scf.
- // CHECK: %[[partial_range:.*]] = arith.muli %[[orig_ub_i]], %[[orig_ub_j]]
- // CHECK-NEXT:%[[range:.*]] = arith.muli %[[partial_range]], %[[orig_ub_k]]
+ // CHECK-DAG:%[[range:.*]] = arith.constant 7056
// Updated loop bounds.
// CHECK: scf.for %[[i:.*]] = %[[orig_lb]] to %[[range]] step %[[orig_step]] iter_args(%[[VAL_1:.*]] = %[[orig_lb]], %[[VAL_2:.*]] = %[[orig_lb]]) -> (index, index) {
@@ -176,13 +168,11 @@ func.func @noramalized_loops_with_shuffled_yielded_iter_args() {
// CHECK-NOT: scf.for
// Reconstruct original IVs from the linearized one.
- // CHECK: %[[orig_k:.*]] = arith.remsi %[[i]], %[[orig_ub_k]]
- // CHECK: %[[div:.*]] = arith.divsi %[[i]], %[[orig_ub_k]]
- // CHECK: %[[orig_j:.*]] = arith.remsi %[[div]], %[[orig_ub_j]]
- // CHECK: %[[orig_i:.*]] = arith.divsi %[[div]], %[[orig_ub_j]]
+ // CHECK: %[[delinearize:.+]]:3 = affine.delinearize_index %[[i]]
+ // CHECK-SAME: into (%[[orig_ub_i]], %[[orig_ub_j]], %[[orig_ub_k]])
%1:2 = scf.for %j = %c0 to %c56 step %c1 iter_args(%arg2 = %arg0, %arg3 = %arg1) -> (index, index){
%0:2 = scf.for %k = %c0 to %c3 step %c1 iter_args(%arg4 = %arg2, %arg5 = %arg3) -> (index, index) {
- // CHECK: "use"(%[[orig_i]], %[[orig_j]], %[[orig_k]])
+ // CHECK: "use"(%[[delinearize]]#0, %[[delinearize]]#1, %[[delinearize]]#2)
"use"(%i, %j, %k) : (index, index, index) -> ()
// CHECK: scf.yield %[[VAL_2]], %[[VAL_1]] : index, index
scf.yield %arg5, %arg4 : index, index
@@ -194,20 +184,21 @@ func.func @noramalized_loops_with_shuffled_yielded_iter_args() {
return
}
+// -----
+
func.func @noramalized_loops_with_yielded_non_iter_args() {
- // CHECK: %[[orig_lb:.*]] = arith.constant 0
- // CHECK: %[[orig_step:.*]] = arith.constant 1
- // CHECK: %[[orig_ub_k:.*]] = arith.constant 3
- // CHECK: %[[orig_ub_i:.*]] = arith.constant 42
- // CHECK: %[[orig_ub_j:.*]] = arith.constant 56
+ // CHECK-DAG: %[[orig_lb:.*]] = arith.constant 0
+ // CHECK-DAG: %[[orig_step:.*]] = arith.constant 1
+ // CHECK-DAG: %[[orig_ub_k:.*]] = arith.constant 3
+ // CHECK-DAG: %[[orig_ub_i:.*]] = arith.constant 42
+ // CHECK-DAG: %[[orig_ub_j:.*...
[truncated]
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Signed-off-by: MaheshRavishankar <[email protected]>
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This fixes `cast`'s that were introduced in #108450. Signed-off-by: Benoit Jacob <[email protected]>
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This fixes `cast`'s that were introduced in llvm/llvm-project#108450. Signed-off-by: Benoit Jacob <[email protected]>
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llvm/llvm-project#110518 fixed assertion failures in `cast` introduced in llvm/llvm-project#108450. Signed-off-by: Benoit Jacob <[email protected]>
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llvm#110518 fixed assertion failures in `cast` introduced in llvm#108450. Signed-off-by: Benoit Jacob <[email protected]>
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For index type of induction variable, the indexing math is better represented using affine ops such as
affine.delinearize_index.This also further demonstrates that some of these
affineops might need to move to a different dialect. For one these ops only supportIndexTypewhen they should be able to work with any integer type.This change also includes some canonicalization patterns for
affine.delinearize_indexoperation tobasisvaluesdelinearize_indexop when thelinear_indexis a loop induction variable of a normalized loop and thebasisis of size 1 and is also the upper bound of the normalized loop.