[mlir][tosa] Introduce arith.constant -> tosa.const normalization pass #167873
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Add a standalone pass that rewrites tensor-valued `arith.constant` ops into `tosa.const`, normalize the TOSA backend contract. Co-authored-by: Shubham <[email protected]> Signed-off-by: Vitalii Shutov <[email protected]> Change-Id: I4e71926107633007a71bd1fcc3311a5da6d38849
Lallapallooza
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@llvm/pr-subscribers-mlir-tosa Author: Vitalii Shutov (Lallapallooza) ChangesAdd a standalone pass that rewrites tensor-valued Full diff: https://github.com/llvm/llvm-project/pull/167873.diff 4 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td b/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td
index 14b00b04ccc18..34572c5c4d131 100644
--- a/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td
+++ b/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td
@@ -105,6 +105,15 @@ def TosaReduceTransposes : Pass<"tosa-reduce-transposes", "func::FuncOp"> {
}];
}
+def TosaArithConstantToTosaConstPass
+ : Pass<"tosa-arith-const-to-tosa-const", "func::FuncOp"> {
+ let summary = "Convert tensor arith.constant operations into tosa.const";
+ let description = [{
+ Normalizes tensor-valued arith.constant operations into tosa.const so that
+ subsequent TOSA passes operate on a consistent representation of constants.
+ }];
+}
+
def TosaConvertIntegerTypeToSignless : Pass<"tosa-convert-integer-type-to-signless", "func::FuncOp"> {
let summary = "Convert integer types to signless";
let description = [{
diff --git a/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt b/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt
index 41b338d6e7189..46c299834e2df 100644
--- a/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt
+++ b/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt
@@ -1,5 +1,6 @@
add_mlir_dialect_library(MLIRTosaTransforms
TosaAttachTarget.cpp
+ TosaArithConstantToConst.cpp
TosaConvertIntegerTypeToSignless.cpp
TosaDecomposeTransposeConv.cpp
TosaDecomposeDepthwise.cpp
diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaArithConstantToConst.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaArithConstantToConst.cpp
new file mode 100644
index 0000000000000..72680489b92a2
--- /dev/null
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaArithConstantToConst.cpp
@@ -0,0 +1,117 @@
+//===- TosaArithConstantToConst.cpp ---------------------------------------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+//
+// This file implements a pass that converts tensor-valued arith.constant ops
+// into tosa.const so that TOSA pipelines operate on a uniform constant form.
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Dialect/Tosa/Transforms/Passes.h"
+
+#include "mlir/Dialect/Arith/IR/Arith.h"
+#include "mlir/Dialect/Func/IR/FuncOps.h"
+#include "mlir/Dialect/Quant/IR/QuantTypes.h"
+#include "mlir/Dialect/Tosa/IR/TosaOps.h"
+#include "mlir/IR/BuiltinAttributes.h"
+#include "mlir/IR/BuiltinTypes.h"
+#include "mlir/IR/PatternMatch.h"
+#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
+
+namespace mlir {
+namespace tosa {
+#define GEN_PASS_DEF_TOSAARITHCONSTANTTOTOSACONSTPASS
+#include "mlir/Dialect/Tosa/Transforms/Passes.h.inc"
+} // namespace tosa
+} // namespace mlir
+
+using namespace mlir;
+using namespace mlir::tosa;
+
+namespace {
+
+/// Returns true when `elementType` is natively representable by tosa.const.
+static bool isSupportedElementType(Type elementType) {
+ if (isa<FloatType>(elementType))
+ return true;
+
+ if (auto intType = dyn_cast<IntegerType>(elementType))
+ return intType.isSignless() || intType.isUnsigned();
+
+ if (isa<quant::QuantizedType>(elementType))
+ return true;
+
+ return false;
+}
+
+class ArithConstantToTosaConst : public OpRewritePattern<arith::ConstantOp> {
+public:
+ using OpRewritePattern::OpRewritePattern;
+
+ LogicalResult matchAndRewrite(arith::ConstantOp constOp,
+ PatternRewriter &rewriter) const override {
+ // TOSA constant verification requires a ranked, statically shaped tensor.
+ auto resultType = dyn_cast<RankedTensorType>(constOp.getResult().getType());
+ if (!resultType || !resultType.hasStaticShape())
+ return failure();
+
+ if (!isSupportedElementType(resultType.getElementType()))
+ return failure();
+
+ Attribute attr = constOp.getValueAttr();
+ auto elementsAttr = dyn_cast<ElementsAttr>(attr);
+ if (!elementsAttr)
+ return failure();
+
+ auto attrType = dyn_cast<RankedTensorType>(elementsAttr.getType());
+ if (!attrType || !attrType.hasStaticShape())
+ return failure();
+
+ if (attrType != resultType) {
+ // Allow reshape when the payload can be reinterpreted without altering
+ // the number of elements or element type. Dense resource attributes
+ // cannot be reshaped losslessly, so bail out in that case.
+ if (!isa<DenseElementsAttr>(elementsAttr))
+ return failure();
+
+ if (attrType.getElementType() != resultType.getElementType())
+ return failure();
+
+ auto denseAttr = cast<DenseElementsAttr>(elementsAttr);
+ if (denseAttr.getNumElements() != resultType.getNumElements())
+ return failure();
+
+ elementsAttr = denseAttr.reshape(resultType);
+ }
+
+ auto newConst = tosa::ConstOp::create(rewriter, constOp.getLoc(),
+ resultType, elementsAttr);
+ rewriter.replaceOp(constOp, newConst.getResult());
+ return success();
+ }
+};
+
+struct TosaArithConstantToTosaConstPass
+ : public tosa::impl::TosaArithConstantToTosaConstPassBase<
+ TosaArithConstantToTosaConstPass> {
+ using Base::Base;
+
+ void getDependentDialects(DialectRegistry ®istry) const override {
+ registry.insert<tosa::TosaDialect>();
+ }
+
+ void runOnOperation() override {
+ auto *ctx = &getContext();
+ RewritePatternSet patterns(ctx);
+ patterns.add<ArithConstantToTosaConst>(ctx);
+
+ if (failed(applyPatternsGreedily(getOperation(), std::move(patterns))))
+ signalPassFailure();
+ }
+};
+
+} // namespace
diff --git a/mlir/test/Dialect/Tosa/arith-const-to-tosa-const.mlir b/mlir/test/Dialect/Tosa/arith-const-to-tosa-const.mlir
new file mode 100644
index 0000000000000..38dbcf7e45b3c
--- /dev/null
+++ b/mlir/test/Dialect/Tosa/arith-const-to-tosa-const.mlir
@@ -0,0 +1,84 @@
+// RUN: mlir-opt %s --tosa-arith-const-to-tosa-const --split-input-file | FileCheck %s
+
+// CHECK-LABEL: func.func @rewrite_f32_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[1.000000e+00, 2.000000e+00]> : tensor<2xf32>}> : () -> tensor<2xf32>
+// CHECK: return %[[CST]]
+func.func @rewrite_f32_tensor() -> tensor<2xf32> {
+ %c = arith.constant dense<[1.000000e+00, 2.000000e+00]> : tensor<2xf32>
+ return %c : tensor<2xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_i32_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[1, 0, -1]> : tensor<3xi32>}> : () -> tensor<3xi32>
+// CHECK: return %[[CST]]
+func.func @rewrite_i32_tensor() -> tensor<3xi32> {
+ %c = arith.constant dense<[1, 0, -1]> : tensor<3xi32>
+ return %c : tensor<3xi32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_i1_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[true, false]> : tensor<2xi1>}> : () -> tensor<2xi1>
+func.func @rewrite_i1_tensor() -> tensor<2xi1> {
+ %c = arith.constant dense<[true, false]> : tensor<2xi1>
+ return %c : tensor<2xi1>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_rank0_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<1.234500e+00> : tensor<f32>}> : () -> tensor<f32>
+func.func @rewrite_rank0_tensor() -> tensor<f32> {
+ %c = arith.constant dense<1.234500e+00> : tensor<f32>
+ return %c : tensor<f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @preserve_scalar_i32
+// CHECK: %[[CST:.*]] = arith.constant 42 : i32
+func.func @preserve_scalar_i32() -> i32 {
+ %c = arith.constant 42 : i32
+ return %c : i32
+}
+
+// -----
+
+// CHECK-LABEL: func.func @preserve_index_tensor
+// CHECK: %[[CST:.*]] = arith.constant dense<[0, 1]> : tensor<2xindex>
+func.func @preserve_index_tensor() -> tensor<2xindex> {
+ %c = arith.constant dense<[0, 1]> : tensor<2xindex>
+ return %c : tensor<2xindex>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_resource_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense_resource<blob1> : tensor<4xf32>}> : () -> tensor<4xf32>
+func.func @rewrite_resource_tensor() -> tensor<4xf32> {
+ %c = arith.constant dense_resource<"blob1"> : tensor<4xf32>
+ return %c : tensor<4xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_quant_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[10, 20]> : tensor<2xui8>}> : () -> tensor<2xui8>
+func.func @rewrite_quant_tensor() -> tensor<2xui8> {
+ %c = arith.constant dense<[10, 20]> : tensor<2xui8>
+ return %c : tensor<2xui8>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_quant_uniform_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<["10", "20"]> : tensor<2x!quant.uniform<i8:f32, 5.000000e-01>>}> : () -> tensor<2x!quant.uniform<i8:f32, 5.000000e-01>>
+func.func @rewrite_quant_uniform_tensor() -> tensor<2x!quant.uniform<i8:f32, 0.5:0>> {
+ %c = arith.constant dense<["10", "20"]> : tensor<2x!quant.uniform<i8:f32, 0.5:0>>
+ return %c : tensor<2x!quant.uniform<i8:f32, 0.5:0>>
+}
+
+// -----
|
Member
|
@llvm/pr-subscribers-mlir Author: Vitalii Shutov (Lallapallooza) ChangesAdd a standalone pass that rewrites tensor-valued Full diff: https://github.com/llvm/llvm-project/pull/167873.diff 4 Files Affected:
diff --git a/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td b/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td
index 14b00b04ccc18..34572c5c4d131 100644
--- a/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td
+++ b/mlir/include/mlir/Dialect/Tosa/Transforms/Passes.td
@@ -105,6 +105,15 @@ def TosaReduceTransposes : Pass<"tosa-reduce-transposes", "func::FuncOp"> {
}];
}
+def TosaArithConstantToTosaConstPass
+ : Pass<"tosa-arith-const-to-tosa-const", "func::FuncOp"> {
+ let summary = "Convert tensor arith.constant operations into tosa.const";
+ let description = [{
+ Normalizes tensor-valued arith.constant operations into tosa.const so that
+ subsequent TOSA passes operate on a consistent representation of constants.
+ }];
+}
+
def TosaConvertIntegerTypeToSignless : Pass<"tosa-convert-integer-type-to-signless", "func::FuncOp"> {
let summary = "Convert integer types to signless";
let description = [{
diff --git a/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt b/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt
index 41b338d6e7189..46c299834e2df 100644
--- a/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt
+++ b/mlir/lib/Dialect/Tosa/Transforms/CMakeLists.txt
@@ -1,5 +1,6 @@
add_mlir_dialect_library(MLIRTosaTransforms
TosaAttachTarget.cpp
+ TosaArithConstantToConst.cpp
TosaConvertIntegerTypeToSignless.cpp
TosaDecomposeTransposeConv.cpp
TosaDecomposeDepthwise.cpp
diff --git a/mlir/lib/Dialect/Tosa/Transforms/TosaArithConstantToConst.cpp b/mlir/lib/Dialect/Tosa/Transforms/TosaArithConstantToConst.cpp
new file mode 100644
index 0000000000000..72680489b92a2
--- /dev/null
+++ b/mlir/lib/Dialect/Tosa/Transforms/TosaArithConstantToConst.cpp
@@ -0,0 +1,117 @@
+//===- TosaArithConstantToConst.cpp ---------------------------------------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+//
+// This file implements a pass that converts tensor-valued arith.constant ops
+// into tosa.const so that TOSA pipelines operate on a uniform constant form.
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Dialect/Tosa/Transforms/Passes.h"
+
+#include "mlir/Dialect/Arith/IR/Arith.h"
+#include "mlir/Dialect/Func/IR/FuncOps.h"
+#include "mlir/Dialect/Quant/IR/QuantTypes.h"
+#include "mlir/Dialect/Tosa/IR/TosaOps.h"
+#include "mlir/IR/BuiltinAttributes.h"
+#include "mlir/IR/BuiltinTypes.h"
+#include "mlir/IR/PatternMatch.h"
+#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
+
+namespace mlir {
+namespace tosa {
+#define GEN_PASS_DEF_TOSAARITHCONSTANTTOTOSACONSTPASS
+#include "mlir/Dialect/Tosa/Transforms/Passes.h.inc"
+} // namespace tosa
+} // namespace mlir
+
+using namespace mlir;
+using namespace mlir::tosa;
+
+namespace {
+
+/// Returns true when `elementType` is natively representable by tosa.const.
+static bool isSupportedElementType(Type elementType) {
+ if (isa<FloatType>(elementType))
+ return true;
+
+ if (auto intType = dyn_cast<IntegerType>(elementType))
+ return intType.isSignless() || intType.isUnsigned();
+
+ if (isa<quant::QuantizedType>(elementType))
+ return true;
+
+ return false;
+}
+
+class ArithConstantToTosaConst : public OpRewritePattern<arith::ConstantOp> {
+public:
+ using OpRewritePattern::OpRewritePattern;
+
+ LogicalResult matchAndRewrite(arith::ConstantOp constOp,
+ PatternRewriter &rewriter) const override {
+ // TOSA constant verification requires a ranked, statically shaped tensor.
+ auto resultType = dyn_cast<RankedTensorType>(constOp.getResult().getType());
+ if (!resultType || !resultType.hasStaticShape())
+ return failure();
+
+ if (!isSupportedElementType(resultType.getElementType()))
+ return failure();
+
+ Attribute attr = constOp.getValueAttr();
+ auto elementsAttr = dyn_cast<ElementsAttr>(attr);
+ if (!elementsAttr)
+ return failure();
+
+ auto attrType = dyn_cast<RankedTensorType>(elementsAttr.getType());
+ if (!attrType || !attrType.hasStaticShape())
+ return failure();
+
+ if (attrType != resultType) {
+ // Allow reshape when the payload can be reinterpreted without altering
+ // the number of elements or element type. Dense resource attributes
+ // cannot be reshaped losslessly, so bail out in that case.
+ if (!isa<DenseElementsAttr>(elementsAttr))
+ return failure();
+
+ if (attrType.getElementType() != resultType.getElementType())
+ return failure();
+
+ auto denseAttr = cast<DenseElementsAttr>(elementsAttr);
+ if (denseAttr.getNumElements() != resultType.getNumElements())
+ return failure();
+
+ elementsAttr = denseAttr.reshape(resultType);
+ }
+
+ auto newConst = tosa::ConstOp::create(rewriter, constOp.getLoc(),
+ resultType, elementsAttr);
+ rewriter.replaceOp(constOp, newConst.getResult());
+ return success();
+ }
+};
+
+struct TosaArithConstantToTosaConstPass
+ : public tosa::impl::TosaArithConstantToTosaConstPassBase<
+ TosaArithConstantToTosaConstPass> {
+ using Base::Base;
+
+ void getDependentDialects(DialectRegistry ®istry) const override {
+ registry.insert<tosa::TosaDialect>();
+ }
+
+ void runOnOperation() override {
+ auto *ctx = &getContext();
+ RewritePatternSet patterns(ctx);
+ patterns.add<ArithConstantToTosaConst>(ctx);
+
+ if (failed(applyPatternsGreedily(getOperation(), std::move(patterns))))
+ signalPassFailure();
+ }
+};
+
+} // namespace
diff --git a/mlir/test/Dialect/Tosa/arith-const-to-tosa-const.mlir b/mlir/test/Dialect/Tosa/arith-const-to-tosa-const.mlir
new file mode 100644
index 0000000000000..38dbcf7e45b3c
--- /dev/null
+++ b/mlir/test/Dialect/Tosa/arith-const-to-tosa-const.mlir
@@ -0,0 +1,84 @@
+// RUN: mlir-opt %s --tosa-arith-const-to-tosa-const --split-input-file | FileCheck %s
+
+// CHECK-LABEL: func.func @rewrite_f32_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[1.000000e+00, 2.000000e+00]> : tensor<2xf32>}> : () -> tensor<2xf32>
+// CHECK: return %[[CST]]
+func.func @rewrite_f32_tensor() -> tensor<2xf32> {
+ %c = arith.constant dense<[1.000000e+00, 2.000000e+00]> : tensor<2xf32>
+ return %c : tensor<2xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_i32_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[1, 0, -1]> : tensor<3xi32>}> : () -> tensor<3xi32>
+// CHECK: return %[[CST]]
+func.func @rewrite_i32_tensor() -> tensor<3xi32> {
+ %c = arith.constant dense<[1, 0, -1]> : tensor<3xi32>
+ return %c : tensor<3xi32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_i1_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[true, false]> : tensor<2xi1>}> : () -> tensor<2xi1>
+func.func @rewrite_i1_tensor() -> tensor<2xi1> {
+ %c = arith.constant dense<[true, false]> : tensor<2xi1>
+ return %c : tensor<2xi1>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_rank0_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<1.234500e+00> : tensor<f32>}> : () -> tensor<f32>
+func.func @rewrite_rank0_tensor() -> tensor<f32> {
+ %c = arith.constant dense<1.234500e+00> : tensor<f32>
+ return %c : tensor<f32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @preserve_scalar_i32
+// CHECK: %[[CST:.*]] = arith.constant 42 : i32
+func.func @preserve_scalar_i32() -> i32 {
+ %c = arith.constant 42 : i32
+ return %c : i32
+}
+
+// -----
+
+// CHECK-LABEL: func.func @preserve_index_tensor
+// CHECK: %[[CST:.*]] = arith.constant dense<[0, 1]> : tensor<2xindex>
+func.func @preserve_index_tensor() -> tensor<2xindex> {
+ %c = arith.constant dense<[0, 1]> : tensor<2xindex>
+ return %c : tensor<2xindex>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_resource_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense_resource<blob1> : tensor<4xf32>}> : () -> tensor<4xf32>
+func.func @rewrite_resource_tensor() -> tensor<4xf32> {
+ %c = arith.constant dense_resource<"blob1"> : tensor<4xf32>
+ return %c : tensor<4xf32>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_quant_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<[10, 20]> : tensor<2xui8>}> : () -> tensor<2xui8>
+func.func @rewrite_quant_tensor() -> tensor<2xui8> {
+ %c = arith.constant dense<[10, 20]> : tensor<2xui8>
+ return %c : tensor<2xui8>
+}
+
+// -----
+
+// CHECK-LABEL: func.func @rewrite_quant_uniform_tensor
+// CHECK: %[[CST:.*]] = "tosa.const"() <{values = dense<["10", "20"]> : tensor<2x!quant.uniform<i8:f32, 5.000000e-01>>}> : () -> tensor<2x!quant.uniform<i8:f32, 5.000000e-01>>
+func.func @rewrite_quant_uniform_tensor() -> tensor<2x!quant.uniform<i8:f32, 0.5:0>> {
+ %c = arith.constant dense<["10", "20"]> : tensor<2x!quant.uniform<i8:f32, 0.5:0>>
+ return %c : tensor<2x!quant.uniform<i8:f32, 0.5:0>>
+}
+
+// -----
|
lhutton1
reviewed
Nov 13, 2025
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lhutton1
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Thanks @Lallapallooza for the PR, I had a couple of high-level questions:
- Since this is a conversion from one dialect to another, I feel a more appropriate location for this pass would be in
Conversions/as opposed toDialect/, WDYT? - Following from the first question, I'm curious to understand the use-case and how arith operations are encountered? Arith seems to be at a lower level of abstraction to Tosa which would make this a "raising" conversion. I'm wondering if there are alternatives we can consider beforehand?
lhutton1
reviewed
Nov 17, 2025
| using Base::Base; | ||
|
|
||
| void getDependentDialects(DialectRegistry ®istry) const override { | ||
| registry.insert<tosa::TosaDialect>(); |
Contributor
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Should arith also be added here?
| if (denseAttr.getNumElements() != resultType.getNumElements()) | ||
| return failure(); | ||
|
|
||
| elementsAttr = denseAttr.reshape(resultType); |
Contributor
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Is there a test for this functionality?
| @@ -0,0 +1,84 @@ | |||
| // RUN: mlir-opt %s --tosa-arith-const-to-tosa-const --split-input-file | FileCheck %s | |||
Contributor
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nit: weak preference for this file to be renames to: tosa-arith-const-to-tosa-const
Contributor
|
Updated by #168370 |
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Add a standalone pass that rewrites tensor-valued
arith.constantops intotosa.const, normalize the TOSA backend contract.