[mlir][vector] Support complete folding in single pass for vector.insert/vector.extract (#142124)
### Description This patch improves the folding efficiency of `vector.insert` and `vector.extract` operations by not returning early after successfully converting dynamic indices to static indices. This PR also renames the test pass `TestConstantFold` to `TestSingleFold` and adds comprehensive documentation explaining the single-pass folding behavior. ### Motivation Since the `OpBuilder::createOrFold` function only calls `fold` **once**, the current `fold` methods of `vector.insert` and `vector.extract` may leave the op in a state that can be folded further. For example, consider the following un-folded IR: ``` %v1 = vector.insert %e1, %v0 [0] : f32 into vector<128xf32> %c0 = arith.constant 0 : index %e2 = vector.extract %v1[%c0] : f32 from vector<128xf32> ``` If we use `createOrFold` to create the `vector.extract` op, then the result will be: ``` %v1 = vector.insert %e1, %v0 [127] : f32 into vector<128xf32> %e2 = vector.extract %v1[0] : f32 from vector<128xf32> ``` But this is not the optimal result. `createOrFold` should have returned `%e1`. The reason is that the execution of fold returns immediately after `extractInsertFoldConstantOp`, causing subsequent folding logics to be skipped. --------- Co-authored-by: Yang Bai <yangb@nvidia.com>
This commit is contained in:
@@ -2063,6 +2063,7 @@ static Value extractInsertFoldConstantOp(OpType op, AdaptorType adaptor,
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if (opChange) {
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op.setStaticPosition(staticPosition);
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op.getOperation()->setOperands(operands);
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// Return the original result to indicate an in-place folding happened.
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return op.getResult();
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}
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return {};
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@@ -2146,11 +2147,12 @@ OpFoldResult ExtractOp::fold(FoldAdaptor adaptor) {
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return getVector();
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if (auto res = foldPoisonSrcExtractOp(adaptor.getVector()))
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return res;
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// Fold `arith.constant` indices into the `vector.extract` operation. Make
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// sure that patterns requiring constant indices are added after this fold.
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// Fold `arith.constant` indices into the `vector.extract` operation.
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// Do not stop here as this fold may enable subsequent folds that require
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// constant indices.
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SmallVector<Value> operands = {getVector()};
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if (auto val = extractInsertFoldConstantOp(*this, adaptor, operands))
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return val;
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auto inplaceFolded = extractInsertFoldConstantOp(*this, adaptor, operands);
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if (auto res = foldPoisonIndexInsertExtractOp(
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getContext(), adaptor.getStaticPosition(), kPoisonIndex))
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return res;
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@@ -2172,7 +2174,8 @@ OpFoldResult ExtractOp::fold(FoldAdaptor adaptor) {
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return val;
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if (auto val = foldScalarExtractFromFromElements(*this))
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return val;
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return OpFoldResult();
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return inplaceFolded;
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}
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namespace {
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@@ -3272,11 +3275,12 @@ OpFoldResult vector::InsertOp::fold(FoldAdaptor adaptor) {
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// (type mismatch).
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if (getNumIndices() == 0 && getValueToStoreType() == getType())
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return getValueToStore();
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// Fold `arith.constant` indices into the `vector.insert` operation. Make
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// sure that patterns requiring constant indices are added after this fold.
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// Fold `arith.constant` indices into the `vector.insert` operation.
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// Do not stop here as this fold may enable subsequent folds that require
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// constant indices.
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SmallVector<Value> operands = {getValueToStore(), getDest()};
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if (auto val = extractInsertFoldConstantOp(*this, adaptor, operands))
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return val;
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auto inplaceFolded = extractInsertFoldConstantOp(*this, adaptor, operands);
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if (auto res = foldPoisonIndexInsertExtractOp(
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getContext(), adaptor.getStaticPosition(), kPoisonIndex))
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return res;
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@@ -3286,7 +3290,7 @@ OpFoldResult vector::InsertOp::fold(FoldAdaptor adaptor) {
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return res;
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}
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return {};
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return inplaceFolded;
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}
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//===----------------------------------------------------------------------===//
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@@ -1,4 +1,4 @@
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// RUN: mlir-opt -test-constant-fold -split-input-file %s | FileCheck %s
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// RUN: mlir-opt -test-single-fold -split-input-file %s | FileCheck %s
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// CHECK-LABEL: func @affine_apply
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func.func @affine_apply(%variable : index) -> (index, index, index) {
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@@ -1,5 +1,5 @@
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// RUN: mlir-opt \
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// RUN: --pass-pipeline="builtin.module(func.func(mesh-spmdization,test-constant-fold))" \
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// RUN: --pass-pipeline="builtin.module(func.func(mesh-spmdization,test-single-fold))" \
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// RUN: --split-input-file \
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// RUN: %s | FileCheck %s
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@@ -1,5 +1,5 @@
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// RUN: mlir-opt \
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// RUN: --pass-pipeline="builtin.module(func.func(mesh-spmdization,test-constant-fold))" \
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// RUN: --pass-pipeline="builtin.module(func.func(mesh-spmdization,test-single-fold))" \
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// RUN: %s | FileCheck %s
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mesh.mesh @mesh_1d(shape = 2)
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@@ -1,5 +1,5 @@
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// RUN: mlir-opt \
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// RUN: --pass-pipeline="builtin.module(func.func(mesh-spmdization,test-constant-fold))" \
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// RUN: --pass-pipeline="builtin.module(func.func(mesh-spmdization,test-single-fold))" \
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// RUN: %s | FileCheck %s
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mesh.mesh @mesh_1d_4(shape = 4)
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@@ -1,4 +1,4 @@
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// RUN: mlir-opt --test-constant-fold %s | FileCheck %s
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// RUN: mlir-opt --test-single-fold %s | FileCheck %s
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// CHECK-LABEL: func @test_const
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func.func @test_const(%arg0 : index) -> tensor<4xi32> {
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@@ -1,4 +1,4 @@
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// RUN: mlir-opt %s -split-input-file -test-constant-fold | FileCheck %s
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// RUN: mlir-opt %s -split-input-file -test-single-fold | FileCheck %s
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// CHECK-LABEL: fold_extract_transpose_negative
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func.func @fold_extract_transpose_negative(%arg0: vector<4x4xf16>) -> vector<4x4xf16> {
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@@ -11,3 +11,5 @@ func.func @fold_extract_transpose_negative(%arg0: vector<4x4xf16>) -> vector<4x4
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%2 = vector.extract %1[0] : vector<4x4xf16> from vector<1x4x4xf16>
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return %2 : vector<4x4xf16>
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}
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38
mlir/test/Dialect/Vector/single-fold.mlir
Normal file
38
mlir/test/Dialect/Vector/single-fold.mlir
Normal file
@@ -0,0 +1,38 @@
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// RUN: mlir-opt %s -split-input-file -test-single-fold | FileCheck %s
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// The tests in this file verify that fold() methods can handle complex
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// optimization scenarios without requiring multiple folding iterations.
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// This is important because:
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//
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// 1. OpBuilder::createOrFold() only calls fold() once, so operations must
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// be fully optimized in that single call
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// 2. Multiple rounds of folding would incur higher performance costs,
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// so it's more efficient to complete all optimizations in one pass
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//
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// These tests ensure that folding implementations are robust and complete,
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// avoiding situations where operations are left in intermediate states
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// that could be further optimized.
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// CHECK-LABEL: fold_extract_in_single_pass
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// CHECK-SAME: (%{{.*}}: vector<4xf16>, %[[ARG1:.+]]: f16)
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func.func @fold_extract_in_single_pass(%arg0: vector<4xf16>, %arg1: f16) -> f16 {
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%0 = vector.insert %arg1, %arg0 [1] : f16 into vector<4xf16>
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%c1 = arith.constant 1 : index
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// Verify that the fold is finished in a single pass even if the index is dynamic.
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%1 = vector.extract %0[%c1] : f16 from vector<4xf16>
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// CHECK: return %[[ARG1]] : f16
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return %1 : f16
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}
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// -----
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// CHECK-LABEL: fold_insert_in_single_pass
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func.func @fold_insert_in_single_pass() -> vector<2xf16> {
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%cst = arith.constant dense<0.000000e+00> : vector<2xf16>
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%c1 = arith.constant 1 : index
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%c2 = arith.constant 2.5 : f16
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// Verify that the fold is finished in a single pass even if the index is dynamic.
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// CHECK: arith.constant dense<[0.000000e+00, 2.500000e+00]> : vector<2xf16>
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%0 = vector.insert %c2, %cst [%c1] : f16 into vector<2xf16>
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return %0 : vector<2xf16>
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}
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@@ -1,4 +1,4 @@
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// RUN: mlir-opt %s -split-input-file -test-constant-fold -mlir-print-debuginfo | FileCheck %s
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// RUN: mlir-opt %s -split-input-file -test-single-fold -mlir-print-debuginfo | FileCheck %s
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// CHECK-LABEL: func @fold_and_merge
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func.func @fold_and_merge() -> (i32, i32) {
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@@ -1,4 +1,4 @@
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// RUN: mlir-opt -allow-unregistered-dialect %s -split-input-file -test-constant-fold | FileCheck %s
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// RUN: mlir-opt -allow-unregistered-dialect %s -split-input-file -test-single-fold | FileCheck %s
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// -----
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@@ -26,11 +26,11 @@ endif()
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add_mlir_library(MLIRTestTransforms
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TestCommutativityUtils.cpp
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TestCompositePass.cpp
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TestConstantFold.cpp
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TestControlFlowSink.cpp
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TestInlining.cpp
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TestInliningCallback.cpp
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TestMakeIsolatedFromAbove.cpp
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TestSingleFold.cpp
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TestTransformsOps.cpp
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${MLIRTestTransformsPDLSrc}
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@@ -1,4 +1,4 @@
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//===- TestConstantFold.cpp - Pass to test constant folding ---------------===//
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//===- TestSingleFold.cpp - Pass to test single-pass folding --------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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@@ -12,14 +12,23 @@
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using namespace mlir;
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namespace {
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/// Simple constant folding pass.
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struct TestConstantFold : public PassWrapper<TestConstantFold, OperationPass<>>,
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public RewriterBase::Listener {
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MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestConstantFold)
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/// Test pass for single-pass constant folding.
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///
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/// This pass tests the behavior of operations when folded exactly once. Unlike
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/// canonicalization passes that may apply multiple rounds of folding, this pass
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/// ensures that each operation is folded at most once, which is useful for
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/// testing scenarios where the fold implementation should handle complex cases
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/// without requiring multiple iterations.
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///
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/// The pass also removes dead constants after folding to clean up unused
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/// intermediate results.
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struct TestSingleFold : public PassWrapper<TestSingleFold, OperationPass<>>,
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public RewriterBase::Listener {
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MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestSingleFold)
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StringRef getArgument() const final { return "test-constant-fold"; }
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StringRef getArgument() const final { return "test-single-fold"; }
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StringRef getDescription() const final {
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return "Test operation constant folding";
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return "Test single-pass operation folding and dead constant elimination";
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}
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// All constants in the operation post folding.
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SmallVector<Operation *> existingConstants;
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@@ -39,18 +48,19 @@ struct TestConstantFold : public PassWrapper<TestConstantFold, OperationPass<>>,
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};
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} // namespace
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void TestConstantFold::foldOperation(Operation *op, OperationFolder &helper) {
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void TestSingleFold::foldOperation(Operation *op, OperationFolder &helper) {
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// Attempt to fold the specified operation, including handling unused or
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// duplicated constants.
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(void)helper.tryToFold(op);
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}
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void TestConstantFold::runOnOperation() {
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void TestSingleFold::runOnOperation() {
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existingConstants.clear();
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// Collect and fold the operations within the operation.
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SmallVector<Operation *, 8> ops;
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getOperation()->walk<mlir::WalkOrder::PreOrder>([&](Operation *op) { ops.push_back(op); });
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getOperation()->walk<mlir::WalkOrder::PreOrder>(
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[&](Operation *op) { ops.push_back(op); });
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// Fold the constants in reverse so that the last generated constants from
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// folding are at the beginning. This creates somewhat of a linear ordering to
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@@ -70,6 +80,6 @@ void TestConstantFold::runOnOperation() {
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namespace mlir {
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namespace test {
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void registerTestConstantFold() { PassRegistration<TestConstantFold>(); }
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void registerTestSingleFold() { PassRegistration<TestSingleFold>(); }
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} // namespace test
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} // namespace mlir
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@@ -87,7 +87,6 @@ void registerTestCfAssertPass();
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void registerTestCFGLoopInfoPass();
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void registerTestComposeSubView();
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void registerTestCompositePass();
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void registerTestConstantFold();
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void registerTestControlFlowSink();
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void registerTestConvertToSPIRVPass();
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void registerTestDataLayoutPropagation();
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@@ -145,6 +144,7 @@ void registerTestSCFUtilsPass();
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void registerTestSCFWhileOpBuilderPass();
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void registerTestSCFWrapInZeroTripCheckPasses();
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void registerTestShapeMappingPass();
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void registerTestSingleFold();
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void registerTestSliceAnalysisPass();
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void registerTestSPIRVCPURunnerPipeline();
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void registerTestSPIRVFuncSignatureConversion();
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@@ -233,7 +233,6 @@ void registerTestPasses() {
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mlir::test::registerTestCFGLoopInfoPass();
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mlir::test::registerTestComposeSubView();
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mlir::test::registerTestCompositePass();
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mlir::test::registerTestConstantFold();
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mlir::test::registerTestControlFlowSink();
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mlir::test::registerTestConvertToSPIRVPass();
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mlir::test::registerTestDataLayoutPropagation();
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@@ -291,6 +290,7 @@ void registerTestPasses() {
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mlir::test::registerTestSCFWhileOpBuilderPass();
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mlir::test::registerTestSCFWrapInZeroTripCheckPasses();
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mlir::test::registerTestShapeMappingPass();
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mlir::test::registerTestSingleFold();
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mlir::test::registerTestSliceAnalysisPass();
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mlir::test::registerTestSPIRVCPURunnerPipeline();
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mlir::test::registerTestSPIRVFuncSignatureConversion();
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