[Mlir-commits] [mlir] 1a8d2a4 - [mlir][tosa] Use generic QuantizedType in Conv verifiers (#126275)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Tue Feb 11 02:58:19 PST 2025
Author: Tai Ly
Date: 2025-02-11T10:58:16Z
New Revision: 1a8d2a40167ea752366fa718a98cafdccce002a5
URL: https://github.com/llvm/llvm-project/commit/1a8d2a40167ea752366fa718a98cafdccce002a5
DIFF: https://github.com/llvm/llvm-project/commit/1a8d2a40167ea752366fa718a98cafdccce002a5.diff
LOG: [mlir][tosa] Use generic QuantizedType in Conv verifiers (#126275)
Replace UniformQuantizedType by the more generic QuantizedType in Conv verifiers.
Change-Id: Ie1961af931864f801914a62976bc988881ee075e
Signed-off-by: Tai Ly <tai.ly at arm.com>
Co-authored-by: Thibaut Goetghebuer-Planchon <thibaut.goetghebuer-planchon at arm.com>
Added:
Modified:
mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
mlir/test/Dialect/Tosa/invalid.mlir
mlir/test/Dialect/Tosa/ops.mlir
Removed:
################################################################################
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
index fd166cc1322cef9..af4a5dc96265ed5 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
@@ -240,16 +240,13 @@ static LogicalResult verifyConvOp(T op) {
bool biasIsFloat = llvm::isa<FloatType>(biasEType);
bool resultIsFloat = llvm::isa<FloatType>(resultEType);
- if (auto quantType =
- llvm::dyn_cast<mlir::quant::UniformQuantizedType>(inputEType))
+ if (auto quantType = llvm::dyn_cast<mlir::quant::QuantizedType>(inputEType))
inputEType = quantType.getStorageType();
- if (auto quantType =
- llvm::dyn_cast<mlir::quant::UniformQuantizedType>(biasEType))
+ if (auto quantType = llvm::dyn_cast<mlir::quant::QuantizedType>(biasEType))
biasEType = quantType.getStorageType();
- if (auto quantType =
- llvm::dyn_cast<mlir::quant::UniformQuantizedType>(resultEType))
+ if (auto quantType = llvm::dyn_cast<mlir::quant::QuantizedType>(resultEType))
resultEType = quantType.getStorageType();
if (biasIsFloat && resultIsFloat && (biasEType != resultEType)) {
@@ -346,8 +343,7 @@ static LogicalResult verifyConvOpModes(T op) {
auto inputEType =
llvm::cast<ShapedType>(op.getInput().getType()).getElementType();
- if (auto quantType =
- llvm::dyn_cast<mlir::quant::UniformQuantizedType>(inputEType))
+ if (auto quantType = llvm::dyn_cast<mlir::quant::QuantizedType>(inputEType))
inputEType = quantType.getStorageType();
auto accType = op.getAccType();
@@ -369,7 +365,23 @@ static LogicalResult verifyConvOpModes(T op) {
if (inputEType.isF32() && !accType.isF32())
return op.emitOpError("accumulator type for f32 tensor is not f32");
- return success();
+ auto resultEType =
+ llvm::cast<ShapedType>(op.getResult().getType()).getElementType();
+
+ if (auto quantType = llvm::dyn_cast<mlir::quant::QuantizedType>(resultEType))
+ resultEType = quantType.getStorageType();
+
+ // check allowed input/result element types combinations
+ if ((inputEType.isInteger(8) && resultEType.isInteger(32)) ||
+ (inputEType.isInteger(16) && resultEType.isInteger(48)) ||
+ (isa<Float8E5M2Type>(inputEType) && resultEType.isF16()) ||
+ (isa<Float8E4M3FNType>(inputEType) && resultEType.isF16()) ||
+ (inputEType.isF16() && resultEType.isF16()) ||
+ (inputEType.isBF16() && resultEType.isBF16()) ||
+ (inputEType.isF32() && resultEType.isF32()))
+ return success();
+
+ return op.emitOpError("input/output element types are incompatible.");
}
// verify that inType and outType have same element types
diff --git a/mlir/test/Dialect/Tosa/invalid.mlir b/mlir/test/Dialect/Tosa/invalid.mlir
index 2165e1f7ae3babb..20fc10d77d0e0c4 100644
--- a/mlir/test/Dialect/Tosa/invalid.mlir
+++ b/mlir/test/Dialect/Tosa/invalid.mlir
@@ -144,6 +144,24 @@ func.func @test_transpose_conv2d(%arg0: tensor<1x32x32x8xi8>, %arg1: tensor<16x1
return %0 : tensor<1x32x32x16xi8>
}
+// -----
+// CHECK-LABEL: conv2d_quant_any_acc
+func.func @test_conv2d_quant_any_acc(%arg0: tensor<1x4x4x4x!quant.any<i8<-8:7>>>, %arg1: tensor<8x1x1x4x!quant.any<i8<-8:7>>>, %arg2: tensor<8x!quant.any<i8<-8:7>>>) -> tensor<1x4x4x8x!quant.any<i8<-8:7>>> {
+ %zp = "tosa.const" () { value = dense<0> : tensor<1xi8> } : () -> tensor<1xi8>
+ // expected-error at +1 {{'tosa.conv2d' op accumulator type for i8 tensor is not i32}}
+ %0 = tosa.conv2d %arg0, %arg1, %arg2, %zp, %zp {acc_type = f32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>, local_bound = true} : (tensor<1x4x4x4x!quant.any<i8<-8:7>>>, tensor<8x1x1x4x!quant.any<i8<-8:7>>>, tensor<8x!quant.any<i8<-8:7>>>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x8x!quant.any<i8<-8:7>>>
+ return %0 : tensor<1x4x4x8x!quant.any<i8<-8:7>>>
+}
+
+// -----
+// CHECK-LABEL: conv2d_quant_any_result
+func.func @test_conv2d_quant_any_result(%arg0: tensor<1x4x4x4x!quant.any<i8<-8:7>>>, %arg1: tensor<8x1x1x4x!quant.any<i8<-8:7>>>, %arg2: tensor<8x!quant.any<i8<-8:7>>>) -> tensor<1x4x4x8x!quant.any<i8<-8:7>>> {
+ %zp = "tosa.const" () { value = dense<0> : tensor<1xi8> } : () -> tensor<1xi8>
+ // expected-error at +1 {{'tosa.conv2d' op input/output element types are incompatible}}
+ %0 = tosa.conv2d %arg0, %arg1, %arg2, %zp, %zp {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>, local_bound = true} : (tensor<1x4x4x4x!quant.any<i8<-8:7>>>, tensor<8x1x1x4x!quant.any<i8<-8:7>>>, tensor<8x!quant.any<i8<-8:7>>>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x8x!quant.any<i8<-8:7>>>
+ return %0 : tensor<1x4x4x8x!quant.any<i8<-8:7>>>
+}
+
// -----
func.func @test_concat(%arg0 : tensor<2x1xf32>, %arg1 : tensor<2x2xf32>) -> tensor<?x?xf32> {
diff --git a/mlir/test/Dialect/Tosa/ops.mlir b/mlir/test/Dialect/Tosa/ops.mlir
index baf09e089aa30fb..d7e4f682c28b3cc 100644
--- a/mlir/test/Dialect/Tosa/ops.mlir
+++ b/mlir/test/Dialect/Tosa/ops.mlir
@@ -58,6 +58,22 @@ func.func @test_conv2d(%arg0: tensor<1x4x4x4xf32>, %arg1: tensor<8x1x1x4xf32>, %
return %0 : tensor<1x4x4x8xf32>
}
+// -----
+// CHECK-LABEL: conv2d_quant_uniform
+func.func @test_conv2d_quant_uniform(%arg0: tensor<1x4x4x4x!quant.uniform<i8:f32, 0.01>>, %arg1: tensor<8x1x1x4x!quant.uniform<i8:f32, 0.01>>, %arg2: tensor<8x!quant.uniform<i8:f32, 0.01>>) -> tensor<1x4x4x8x!quant.uniform<i32:f32, 0.01>> {
+ %zp = "tosa.const" () { value = dense<0> : tensor<1xi8> } : () -> tensor<1xi8>
+ %0 = tosa.conv2d %arg0, %arg1, %arg2, %zp, %zp {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>, local_bound = true} : (tensor<1x4x4x4x!quant.uniform<i8:f32, 0.01>>, tensor<8x1x1x4x!quant.uniform<i8:f32, 0.01>>, tensor<8x!quant.uniform<i8:f32, 0.01>>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x8x!quant.uniform<i32:f32, 0.01>>
+ return %0 : tensor<1x4x4x8x!quant.uniform<i32:f32, 0.01>>
+}
+
+// -----
+// CHECK-LABEL: conv2d_quant_any
+func.func @test_conv2d_quant_any(%arg0: tensor<1x4x4x4x!quant.any<i8<-8:7>>>, %arg1: tensor<8x1x1x4x!quant.any<i8<-8:7>>>, %arg2: tensor<8x!quant.any<i8<-8:7>>>) -> tensor<1x4x4x8x!quant.any<i32<-8:7>>> {
+ %zp = "tosa.const" () { value = dense<0> : tensor<1xi8> } : () -> tensor<1xi8>
+ %0 = tosa.conv2d %arg0, %arg1, %arg2, %zp, %zp {acc_type = i32, dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>, local_bound = true} : (tensor<1x4x4x4x!quant.any<i8<-8:7>>>, tensor<8x1x1x4x!quant.any<i8<-8:7>>>, tensor<8x!quant.any<i8<-8:7>>>, tensor<1xi8>, tensor<1xi8>) -> tensor<1x4x4x8x!quant.any<i32<-8:7>>>
+ return %0 : tensor<1x4x4x8x!quant.any<i32<-8:7>>>
+}
+
// -----
// CHECK-LABEL: conv2d_q8xi4
func.func @test_conv2d_q8xi4(%arg0: tensor<1x11x11x3xi8>) -> tensor<1x1x1x3xi8> {
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