[Mlir-commits] [mlir] [MLIR][TOSA] Make RESCALE op input_unsigned and output_unsigned attributes required (PR #129339)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Fri Feb 28 15:51:49 PST 2025
llvmbot wrote:
<!--LLVM PR SUMMARY COMMENT-->
@llvm/pr-subscribers-mlir-tosa
Author: Peng Sun (psunn)
<details>
<summary>Changes</summary>
Previously, the input_unsigned and output_unsigned attributes on the RESCALE op were optional. This commit updates them to be required, ensuring compliance with the TOSA V1.0 Specification.
---
Full diff: https://github.com/llvm/llvm-project/pull/129339.diff
8 Files Affected:
- (modified) mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td (+2-2)
- (modified) mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-invalid.mlir (+1-1)
- (modified) mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir (+9-9)
- (modified) mlir/test/Dialect/Tosa/availability.mlir (+1-1)
- (modified) mlir/test/Dialect/Tosa/canonicalize.mlir (-2)
- (modified) mlir/test/Dialect/Tosa/ops.mlir (+2-2)
- (modified) mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir (+1-1)
- (modified) mlir/test/lib/Dialect/Tosa/TosaTestPasses.cpp (+5-1)
``````````diff
diff --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
index ddfec2c9bfcd3..a16baf7b5147d 100644
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
@@ -2289,8 +2289,8 @@ def Tosa_RescaleOp: Tosa_Op<"rescale", [Pure,
BoolAttr:$scale32,
BoolAttr:$double_round,
BoolAttr:$per_channel,
- DefaultValuedOptionalAttr<BoolAttr, "false">:$input_unsigned,
- DefaultValuedOptionalAttr<BoolAttr, "false">:$output_unsigned
+ BoolAttr: $input_unsigned,
+ BoolAttr: $output_unsigned
);
let results = (outs
diff --git a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-invalid.mlir b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-invalid.mlir
index 5db3f56cf459e..4a2dbff65852c 100644
--- a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-invalid.mlir
+++ b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-invalid.mlir
@@ -43,7 +43,7 @@ func.func @rfft2d_with_non_float_type(%arg0 : tensor<1x1x1xi32>) -> (tensor<1x1x
// CHECK-LABEL: @rescale_unsupported_type
func.func @rescale_unsupported_type(%arg0: tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>> {
// expected-error at +1 {{failed to legalize operation 'tosa.rescale'}}
- %0 = tosa.rescale %arg0 {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
+ %0 = tosa.rescale %arg0 {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>, input_unsigned = true, output_unsigned = false} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
return %0 : tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
}
diff --git a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
index 78f2e173d7cb1..4958998f88328 100644
--- a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
+++ b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
@@ -1149,7 +1149,7 @@ func.func @rescale_i8(%arg0 : tensor<2xi8>) -> () {
// CHECK-DAG: [[BOUNDED:%.+]] = arith.minsi [[CMAX]], [[LOWER]]
// CHECK-DAG: [[TRUNC:%.+]] = arith.trunci [[BOUNDED]]
// CHECK-DAG: linalg.yield [[TRUNC]]
- %0 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false} : (tensor<2xi8>) -> tensor<2xi8>
+ %0 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<2xi8>) -> tensor<2xi8>
// CHECK: return
return
@@ -1178,7 +1178,7 @@ func.func @rescale_i8_unsigned_output(%arg0 : tensor<2xi8>) -> () {
// CHECK-DAG: [[BOUNDED:%.+]] = arith.minsi [[CMAX]], [[LOWER]]
// CHECK-DAG: [[TRUNC:%.+]] = arith.trunci [[BOUNDED]]
// CHECK: linalg.yield [[TRUNC]]
- %1 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, output_unsigned = true} : (tensor<2xi8>) -> tensor<2xi8>
+ %1 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, input_unsigned = false, output_unsigned = true} : (tensor<2xi8>) -> tensor<2xi8>
// CHECK: return
return
@@ -1195,13 +1195,13 @@ func.func @rescale_i8_dyn_batch(%arg0 : tensor<?x2xi8>) -> () {
// CHECK: %[[BATCH:.+]] = tensor.dim %[[ARG0]], %[[C0]]
// CHECK: %[[INIT:.+]] = tensor.empty(%[[BATCH]]) : tensor<?x2xi8>
// CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]] : tensor<?x2xi8>) outs(%[[INIT]] : tensor<?x2xi8>)
- %0 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false} : (tensor<?x2xi8>) -> tensor<?x2xi8>
+ %0 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<?x2xi8>) -> tensor<?x2xi8>
// CHECK: %[[C0:.+]] = arith.constant 0
// CHECK: %[[BATCH:.+]] = tensor.dim %[[ARG0]], %[[C0]]
// CHECK: %[[INIT:.+]] = tensor.empty(%[[BATCH]]) : tensor<?x2xi8>
// CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]] : tensor<?x2xi8>) outs(%[[INIT]] : tensor<?x2xi8>)
- %1 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, output_unsigned = true} : (tensor<?x2xi8>) -> tensor<?x2xi8>
+ %1 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, input_unsigned = false, output_unsigned = true} : (tensor<?x2xi8>) -> tensor<?x2xi8>
return
}
@@ -1219,7 +1219,7 @@ func.func @rescale_dyn(%arg0 : tensor<1x?x?x32xi32>) -> () {
// CHECK: %[[DIM2:.+]] = tensor.dim %[[ARG0]], %[[C2]]
// CHECK: %[[INIT:.+]] = tensor.empty(%[[DIM1]], %[[DIM2]])
// CHECK: [[GENERIC:%.+]] = linalg.generic {indexing_maps = [#[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%[[ARG0]] : tensor<1x?x?x32xi32>) outs(%[[INIT]] : tensor<1x?x?x32xi8>)
- %0 = tosa.rescale %arg0 {double_round = true, input_zp = 0 : i32, multiplier = array<i32: 1376784203>, output_zp = 0 : i32, per_channel = false, scale32 = true, shift = array<i8: 38>} : (tensor<1x?x?x32xi32>) -> tensor<1x?x?x32xi8>
+ %0 = tosa.rescale %arg0 {double_round = true, input_zp = 0 : i32, multiplier = array<i32: 1376784203>, output_zp = 0 : i32, per_channel = false, scale32 = true, shift = array<i8: 38>, input_unsigned = false, output_unsigned = false} : (tensor<1x?x?x32xi32>) -> tensor<1x?x?x32xi8>
return
}
@@ -1247,7 +1247,7 @@ func.func @rescale_i8_unsigned_input(%arg0 : tensor<2xi8>) -> () {
// CHECK-DAG: [[BOUNDED:%.+]] = arith.minsi [[CMAX]], [[LOWER]]
// CHECK-DAG: [[TRUNC:%.+]] = arith.trunci [[BOUNDED]]
// CHECK: linalg.yield [[TRUNC]]
- %0 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, input_unsigned = true} : (tensor<2xi8>) -> tensor<2xi8>
+ %0 = tosa.rescale %arg0 {input_zp = 17 : i32, output_zp = 22 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = false, double_round = false, per_channel = false, input_unsigned = true, output_unsigned = false} : (tensor<2xi8>) -> tensor<2xi8>
return
}
@@ -1277,7 +1277,7 @@ func.func @rescale_per_channel(%arg0 : tensor<3xi8>) -> (tensor<3xi8>) {
// CHECK-DAG: [[BOUNDED:%.+]] = arith.minsi [[CMAX]], [[LOWER]]
// CHECK-DAG: [[TRUNC:%.+]] = arith.trunci [[BOUNDED]]
// CHECK-DAG: linalg.yield [[TRUNC]]
- %0 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 42, 43, 44>, shift = array<i8: 14, 15, 64>, scale32 = false, double_round = false, per_channel = false} : (tensor<3xi8>) -> tensor<3xi8>
+ %0 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 42, 43, 44>, shift = array<i8: 14, 15, 64>, scale32 = false, double_round = false, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<3xi8>) -> tensor<3xi8>
// CHECK: return [[GENERIC]]
return %0 : tensor<3xi8>
@@ -1290,7 +1290,7 @@ func.func @rescaleDoubleRound(%arg0 : tensor<2xi8>) -> (tensor<2xi8>) {
// CHECK: linalg.generic
// CHECK: tosa.apply_scale
// CHECK-SAME: {double_round = true}
- %0 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 19689>, shift = array<i8: 33>, scale32 = true, double_round = true, per_channel = false} : (tensor<2xi8>) -> tensor<2xi8>
+ %0 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 19689>, shift = array<i8: 33>, scale32 = true, double_round = true, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<2xi8>) -> tensor<2xi8>
return %0 : tensor<2xi8>
}
@@ -1299,7 +1299,7 @@ func.func @rescaleUnnecessaryDoubleRound(%arg0 : tensor<2xi8>) -> (tensor<2xi8>)
// CHECK: linalg.generic
// CHECK: tosa.apply_scale
// CHECK-SAME: {double_round = false}
- %0 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = true, double_round = true, per_channel = false} : (tensor<2xi8>) -> tensor<2xi8>
+ %0 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 19689>, shift = array<i8: 15>, scale32 = true, double_round = true, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<2xi8>) -> tensor<2xi8>
return %0 : tensor<2xi8>
}
diff --git a/mlir/test/Dialect/Tosa/availability.mlir b/mlir/test/Dialect/Tosa/availability.mlir
index 7324b0ea52e89..98290c7b9eedd 100644
--- a/mlir/test/Dialect/Tosa/availability.mlir
+++ b/mlir/test/Dialect/Tosa/availability.mlir
@@ -611,7 +611,7 @@ func.func @test_cast1(%arg0: tensor<13x21x3xi32>) -> tensor<13x21x3xf32> {
func.func @test_rescale(%arg0: tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>, %multiplier : tensor<1xi32>, %shift : tensor<1xi8>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>> {
// CHECK: profiles: [ [pro_int] ]
// CHECK: extensions: [ [int16] ]
- %0 = tosa.rescale %arg0 {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
+ %0 = tosa.rescale %arg0 {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>, input_unsigned = true, output_unsigned = false} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
return %0 : tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
}
diff --git a/mlir/test/Dialect/Tosa/canonicalize.mlir b/mlir/test/Dialect/Tosa/canonicalize.mlir
index 66de6b23eae01..30f557a338fb5 100644
--- a/mlir/test/Dialect/Tosa/canonicalize.mlir
+++ b/mlir/test/Dialect/Tosa/canonicalize.mlir
@@ -897,8 +897,6 @@ func.func @reshape_quant_nofold() -> tensor<1x1x1x1xi32> {
%0 = "tosa.const"() {value = dense<127> : tensor<i8>} : () -> tensor<!quant.uniform<i8:f32, 3.0757404601899907E-5:-128>>
%cst0 = "tosa.const_shape"() {value = dense<[1, 1, 1, 1]> : tensor<4xindex>} : () -> !tosa.shape<4>
%1 = tosa.reshape %0, %cst0 : (tensor<!quant.uniform<i8:f32, 3.0757404601899907E-5:-128>>, !tosa.shape<4>) -> tensor<1x1x1x1x!quant.uniform<i8:f32, 3.0757404601899907E-5:-128>>
- %multiplier = "tosa.const"() {value = dense<1073741824> : tensor<1xi32> } : () -> tensor<1xi32>
- %shift = "tosa.const"() {value = dense<30> : tensor<1xi8> } : () -> tensor<1xi8>
%2 = tosa.rescale %1 {double_round = true, input_zp = -128 : i32, multiplier = array<i32: 1073741824>, output_zp = 0 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>, input_unsigned = false, output_unsigned = false} : (tensor<1x1x1x1x!quant.uniform<i8:f32, 3.0757404601899907E-5:-128>>) -> tensor<1x1x1x1xi32>
return %2 : tensor<1x1x1x1xi32>
}
diff --git a/mlir/test/Dialect/Tosa/ops.mlir b/mlir/test/Dialect/Tosa/ops.mlir
index bea73ab92f2e3..c96accdcfd596 100644
--- a/mlir/test/Dialect/Tosa/ops.mlir
+++ b/mlir/test/Dialect/Tosa/ops.mlir
@@ -82,7 +82,7 @@ func.func @test_conv2d_q8xi4(%arg0: tensor<1x11x11x3xi8>) -> tensor<1x1x1x3xi8>
%izp = "tosa.const"() {value = dense<0> : tensor<1xi8>} : () -> tensor<1xi8>
%wzp = "tosa.const"() {value = dense<0> : tensor<1xi4>} : () -> tensor<1xi4>
%2 = "tosa.conv2d"(%arg0, %0, %1, %izp, %wzp) {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>} : (tensor<1x11x11x3xi8>, tensor<3x11x11x3xi4>, tensor<3xi32>, tensor<1xi8>, tensor<1xi4>) -> tensor<1x1x1x3xi32>
- %3 = "tosa.rescale"(%2) {double_round = true, input_zp = 0 : i32, multiplier = array<i32: 2026291432, 1079222024, 1693132724>, output_zp = 27 : i32, per_channel = true, scale32 = true, shift = array<i8: 37, 36, 37>} : (tensor<1x1x1x3xi32>) -> tensor<1x1x1x3xi8>
+ %3 = "tosa.rescale"(%2) {double_round = true, input_zp = 0 : i32, multiplier = array<i32: 2026291432, 1079222024, 1693132724>, output_zp = 27 : i32, per_channel = true, scale32 = true, shift = array<i8: 37, 36, 37>, input_unsigned = false, output_unsigned = false} : (tensor<1x1x1x3xi32>) -> tensor<1x1x1x3xi8>
return %3 : tensor<1x1x1x3xi8>
}
@@ -707,7 +707,7 @@ func.func @test_cast3(%arg0: tensor<13x21x3xi32>) -> tensor<13x21x3x!quant.unifo
// -----
// CHECK-LABEL: rescale
func.func @test_rescale(%arg0: tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>> {
- %0 = tosa.rescale %arg0 {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
+ %0 = tosa.rescale %arg0 {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>, input_unsigned = false, output_unsigned = false} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
return %0 : tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
}
diff --git a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
index b87e9a78bf144..d18a6833daaf0 100644
--- a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
@@ -94,7 +94,7 @@ func.func @test_unary_i32(%arg0 : tensor<4xi32>) -> () {
%5 = tosa.reverse %arg0 { axis = 0 : i32 } : (tensor<4xi32>) -> tensor<?xi32>
// CHECK: tosa.rescale %arg0 {{.+}} : (tensor<4xi32>) -> tensor<4xi16>
- %6 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 42, 43>, shift = array<i8: 14, 15>, scale32 = false, double_round = false, per_channel = false} : (tensor<4xi32>) -> tensor<*xi16>
+ %6 = tosa.rescale %arg0 {input_zp = 243 : i32, output_zp = 252 : i32, multiplier = array<i32: 42, 43>, shift = array<i8: 14, 15>, scale32 = false, double_round = false, per_channel = false, input_unsigned = false, output_unsigned = false} : (tensor<4xi32>) -> tensor<*xi16>
// CHECK: tosa.identity %arg0 : (tensor<4xi32>) -> tensor<4xi32>
%7 = tosa.identity %arg0 : (tensor<4xi32>) -> tensor<?xi32>
diff --git a/mlir/test/lib/Dialect/Tosa/TosaTestPasses.cpp b/mlir/test/lib/Dialect/Tosa/TosaTestPasses.cpp
index 83db1188861ab..93ad9d124d9cf 100644
--- a/mlir/test/lib/Dialect/Tosa/TosaTestPasses.cpp
+++ b/mlir/test/lib/Dialect/Tosa/TosaTestPasses.cpp
@@ -165,13 +165,17 @@ ConvertTosaConv2DOp::matchAndRewrite(Operation *op,
// Obtain the quantized scale = multiplier and shift.
computeMultiplierAndShift(opTensorScale, multiplier, shift, 32);
+ bool input_unsigned = newTosaConv2DOp.getResult().getType().isUnsignedInteger();
+ bool output_unsigned = outputType.isUnsignedInteger();
+
auto newTosaRescaleOp = rewriter.create<tosa::RescaleOp>(
op->getLoc(), outputType, newTosaConv2DOp.getResult(),
rewriter.getI32IntegerAttr(0), rewriter.getI32IntegerAttr(outputZp),
rewriter.getDenseI32ArrayAttr({multiplier}),
rewriter.getDenseI8ArrayAttr({static_cast<int8_t>(shift)}),
rewriter.getBoolAttr(true), rewriter.getBoolAttr(true),
- rewriter.getBoolAttr(false));
+ rewriter.getBoolAttr(false), rewriter.getBoolAttr(input_unsigned),
+ rewriter.getBoolAttr(output_unsigned));
rewriter.replaceOp(op, {newTosaRescaleOp.getResult()});
return success();
``````````
</details>
https://github.com/llvm/llvm-project/pull/129339
More information about the Mlir-commits
mailing list