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Revamp StableHLO folder patterns to use MLIR folding infra, to not ex… #2813

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Revamp StableHLO folder patterns to use MLIR folding infra, to not ex…
GleasonK Jun 11, 2025
6221bba
clang-format
GleasonK Jun 11, 2025
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37 changes: 36 additions & 1 deletion stablehlo/tests/transforms/stablehlo_aggressive_folder.mlir
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
// RUN: stablehlo-opt --stablehlo-aggressive-folder --split-input-file --verify-diagnostics %s | FileCheck %s
// RUN: stablehlo-opt --stablehlo-aggressive-folder=fold-op-element-limit=100 --split-input-file --verify-diagnostics %s | FileCheck %s

////////
// AddOp
Expand Down Expand Up @@ -41,6 +41,21 @@ func.func @broadcast_in_dim_fold_splat(%arg0: tensor<3x3xi32>)

// -----

////////
// ClampOp

// CHECK-LABEL: func.func @clamp_fold
func.func @clamp_fold(%arg0: tensor<3xi32>) -> tensor<3xi32> {
%min = stablehlo.constant dense<[1, 5, 10]> : tensor<3xi32>
%max = stablehlo.constant dense<[10, 25, 12]> : tensor<3xi32>
%operand = stablehlo.constant dense<[0, 30, 11]> : tensor<3xi32>
// CHECK: stablehlo.constant dense<[1, 25, 11]> : tensor<3xi32>
%0 = "stablehlo.clamp"(%min, %operand, %max) : (tensor<3xi32>, tensor<3xi32>, tensor<3xi32>) -> tensor<3xi32>
func.return %0: tensor<3xi32>
}

// -----

////////
// CompareOp

Expand Down Expand Up @@ -102,6 +117,26 @@ func.func @concatenate_fold() -> (tensor<6xi32>, tensor<3xi32>, tensor<3x3xi32>,

// -----

////////
// DivOp

// CHECK-LABEL: @div_fold_cst
func.func @div_fold_cst() -> (tensor<i32>, tensor<ui32>, tensor<f32>) {
%cst = stablehlo.constant dense<2> : tensor<i32>
%cst_1 = stablehlo.constant dense<2> : tensor<ui32>
%cst_2 = stablehlo.constant dense<2.0> : tensor<f32>
// CHECK: stablehlo.constant dense<1> : tensor<i32>
// CHECK: stablehlo.constant dense<1> : tensor<ui32>
// CHECK: stablehlo.divide{{.*}} : tensor<f32>
// DISABLED-CHECK: stablehlo.constant dense<1.0{{.*}}> : tensor<f32>
%0 = stablehlo.divide %cst, %cst : tensor<i32>
%1 = stablehlo.divide %cst_1, %cst_1 : tensor<ui32>
%2 = stablehlo.divide %cst_2, %cst_2 : tensor<f32>
return %0, %1, %2 : tensor<i32>, tensor<ui32>, tensor<f32>
}

// -----

////////
// MulOp

Expand Down
2 changes: 1 addition & 1 deletion stablehlo/tests/transforms/stablehlo_aggressive_simplification.mlir
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
// RUN: stablehlo-opt --stablehlo-aggressive-simplification --allow-unregistered-dialect --split-input-file %s | FileCheck %s
// RUN: stablehlo-opt --stablehlo-aggressive-simplification=fold-op-element-limit=100 --allow-unregistered-dialect --split-input-file %s | FileCheck %s

/////////
// AddOp
Expand Down
10 changes: 5 additions & 5 deletions stablehlo/tests/transforms/stablehlo_refine_shapes.mlir
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Expand Up @@ -521,16 +521,16 @@ func.func @eval_slice_zerodim() -> tensor<0x2x1xi64> {
// -----

// CHECK-LABEL: func @eval_slice_zerorank
func.func @eval_slice_zerorank() -> tensor<f32> {
// CHECK: [[RESULT:%.*]] = stablehlo.constant dense<3.300000e+01> : tensor<f32>
func.func @eval_slice_zerorank() -> tensor<i32> {
// CHECK: [[RESULT:%.*]] = stablehlo.constant dense<33> : tensor<i32>
// CHECK: return [[RESULT]]
%0 = stablehlo.constant dense<33.0> : tensor<f32>
%0 = stablehlo.constant dense<33> : tensor<i32>
%1 = "stablehlo.slice"(%0) {
start_indices = array<i64>,
limit_indices = array<i64>,
strides = array<i64>
} : (tensor<f32>) -> tensor<f32>
func.return %1 : tensor<f32>
} : (tensor<i32>) -> tensor<i32>
func.return %1 : tensor<i32>
}

// -----
Expand Down
4 changes: 4 additions & 0 deletions stablehlo/transforms/StablehloRefineShapes.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@ limitations under the License.

#include <cstddef>
#include <cstdint>
#include <limits>
#include <tuple>
#include <utility>

Expand Down Expand Up @@ -1038,8 +1039,11 @@ LogicalResult applyShapeRefinementPatterns(func::FuncOp func,
// Populate additional patterns for StableHLO extensions.
state.addAdditionalPatterns(patterns);

// No float folding and fold as much as possible. Shape refinement will fail
// if int shape computations are unable to be folded.
StablehloAggressiveFolderPassOptions folderOptions;
folderOptions.optimizeFloat = false;
folderOptions.foldOpElementLimit = std::numeric_limits<int64_t>::max();

// The folding patterns implement partial evaluation of shape computations
// which is a critical part of implementing type refinement for ops like
Expand Down
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