[Mlir-commits] [mlir] 6daa021 - [mlir][tosa] Check same input/output types in pooling ops verifier (#203565)

[llvmlistbot at llvm.org]

Author: Luke Hutton
Date: 2026-06-22T09:52:41+01:00
New Revision: 6daa02101815f4b2a6851fba8d8bedbfffd1e72c

URL: https://github.com/llvm/llvm-project/commit/6daa02101815f4b2a6851fba8d8bedbfffd1e72c
DIFF: https://github.com/llvm/llvm-project/commit/6daa02101815f4b2a6851fba8d8bedbfffd1e72c.diff

LOG: [mlir][tosa] Check same input/output types in pooling ops verifier (#203565)

Adds a missing check to make sure the input and output types of pooling
ops have the same element type.

Added: 
    

Modified: 
    mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
    mlir/test/Dialect/Tosa/verifier.mlir

Removed: 
    


################################################################################
diff  --git a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
index c2407729d3bd7..3c54d7448d021 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
@@ -1073,18 +1073,18 @@ static LogicalResult verifyVariableOpErrorIf(T op, Type type, StringRef name) {
 }
 
 // verify that inType and outType have same element types
-template <typename T>
-static LogicalResult verifySameElementTypes(T op, Type aType, Type bType,
+static LogicalResult verifySameElementTypes(Operation *op, Type aType,
+                                            Type bType,
                                             StringRef aName = "input",
                                             StringRef bName = "output") {
   auto aTType = llvm::dyn_cast<TensorType>(aType);
   auto bTType = llvm::dyn_cast<TensorType>(bType);
   if (!aTType) {
-    op.emitOpError("expect shaped tensor for") << aName << ", got " << aType;
+    op->emitOpError("expect shaped tensor for") << aName << ", got " << aType;
     return failure();
   }
   if (!bTType) {
-    op.emitOpError("expect shaped tensor for") << bName << ", got" << bType;
+    op->emitOpError("expect shaped tensor for") << bName << ", got" << bType;
     return failure();
   }
   auto aElementType = aTType.getElementType();
@@ -1100,7 +1100,7 @@ static LogicalResult verifySameElementTypes(T op, Type aType, Type bType,
     // eg, not sure how to check quant::QuantizedType
     // this happens in test_conv2d_q_grouped_convolution in
     // tfl-to-tosa-pipeline.mlir
-    op.emitOpError("expect ")
+    op->emitOpError("expect ")
         << aName << " and " << bName << " to have same element type, got "
         << aElementType << " and " << bElementType;
     return failure();
@@ -1144,6 +1144,9 @@ static LogicalResult verifyPoolingOpImpl(Operation *op,
                                          ArrayRef<int64_t> strides,
                                          ArrayRef<int64_t> padding, Value input,
                                          Value output) {
+  if (failed(verifySameElementTypes(op, input.getType(), output.getType())))
+    return failure();
+
   const bool hasKernel = kernel.size() > 0;
   const bool hasStrides = strides.size() > 0;
   const bool hasPad = padding.size() > 0;

diff  --git a/mlir/test/Dialect/Tosa/verifier.mlir b/mlir/test/Dialect/Tosa/verifier.mlir
index 00fd07304cf6f..9d97df2f43c6d 100644
--- a/mlir/test/Dialect/Tosa/verifier.mlir
+++ b/mlir/test/Dialect/Tosa/verifier.mlir
@@ -2123,6 +2123,28 @@ func.func @test_maxpool2d_adaptive_unexpected_output_width(%arg0: tensor<1x32x32
 
 // -----
 
+func.func @test_avg_pool2d_same_input_output_type(%arg0: tensor<1x7x7x9xf32>) -> tensor<1x7x7x9xf16> {
+  %input_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf32>}> : () -> tensor<1xf32>
+  %output_zp = "tosa.const"() <{values = dense<0.0> : tensor<1xf32>}> : () -> tensor<1xf32>
+  // expected-error at +1 {{'tosa.avg_pool2d' op expect input and output to have same element type, got 'f32' and 'f16'}}
+  %0 = tosa.avg_pool2d %arg0, %input_zp, %output_zp {acc_type = f32, kernel = array<i64: 2, 2>, pad = array<i64: 0, 1, 0, 1>, stride = array<i64: 1, 1>} : (tensor<1x7x7x9xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x7x7x9xf16>
+  return %0 : tensor<1x7x7x9xf16>
+}
+
+// -----
+
+func.func @test_maxpool2d_adaptive_unexpected_output_width(%arg0: tensor<1x32x32x8xf32>) -> tensor<1x32x32x8xf16> {
+  %kernel = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
+  %stride = tosa.const_shape {values = dense<[1, 1]> : tensor<2xindex>} : () -> !tosa.shape<2>
+  %pad = tosa.const_shape {values = dense<[0, 0, 0, 0]> : tensor<4xindex>} : () -> !tosa.shape<4>
+  // expected-error at +1 {{'tosa.max_pool2d_adaptive' op expect input and output to have same element type, got 'f32' and 'f16'}}
+  %0 = tosa.max_pool2d_adaptive %arg0, %kernel, %stride, %pad :
+         (tensor<1x32x32x8xf32>, !tosa.shape<2>, !tosa.shape<2>, !tosa.shape<4>) -> tensor<1x32x32x8xf16>
+  return %0 : tensor<1x32x32x8xf16>
+}
+
+// -----
+
 func.func @test_const_mxint8_uint8(%arg0 : index) -> tensor<2x!tosa.mxint8> {
   // expected-error at +1 {{incompatible attribute for element type}}
   %0 = "tosa.const"() {values = dense<tensor<2x!tosa.mxint8> : [127: ui8, 245: ui8]>} : () -> tensor<2x!tosa.mxint8>