fix: add a separate check for pad_dot_general

Author: avik-pal

src/enzyme_ad/jax/Passes/EnzymeHLOOpt.cpp

@@ -9667,12 +9667,15 @@ struct PadDotGeneral
       nextOtherArg = slice.getResult();
     }
 
+    auto lhs = otherIsLHS ? nextOtherArg : pad.getOperand();
+    auto rhs = otherIsLHS ? pad.getOperand() : nextOtherArg;
+    if (!areValidDotGeneralInputs(lhs, rhs, op.getDotDimensionNumbersAttr()))
+      return failure();
+
     Value res = rewriter.create<stablehlo::DotGeneralOp>(
         op.getLoc(),
-        RankedTensorType::get(resultShape, op.getType().getElementType()),
-        otherIsLHS ? nextOtherArg : pad.getOperand(),
-        otherIsLHS ? pad.getOperand() : nextOtherArg,
-        op.getDotDimensionNumbersAttr(), op.getPrecisionConfigAttr(),
+        RankedTensorType::get(resultShape, op.getType().getElementType()), lhs,
+        rhs, op.getDotDimensionNumbersAttr(), op.getPrecisionConfigAttr(),
         op.getAlgorithmAttr());
 
     if (!resultDimsToPad.empty()) {

src/enzyme_ad/jax/Utils.cpp

@@ -1248,6 +1248,28 @@ bool reshapeIsTranspose(stablehlo::ReshapeOp reshapeOp) {
   return true;
 }
 
+bool areValidDotGeneralInputs(Value lhs, Value rhs,
+                              stablehlo::DotDimensionNumbersAttr dotDimNumbers) {
+  auto lhsShape = cast<ShapedType>(lhs.getType()).getShape();
+  auto rhsShape = cast<ShapedType>(rhs.getType()).getShape();
+
+  for (auto [lhsBatchDim, rhsBatchDim] :
+       llvm::zip(dotDimNumbers.getLhsBatchingDimensions(),
+                 dotDimNumbers.getRhsBatchingDimensions())) {
+    if (lhsShape[lhsBatchDim] != rhsShape[rhsBatchDim])
+      return false;
+  }
+
+  for (auto [lhsContractingDim, rhsContractingDim] :
+       llvm::zip(dotDimNumbers.getLhsContractingDimensions(),
+                 dotDimNumbers.getRhsContractingDimensions())) {
+    if (lhsShape[lhsContractingDim] != rhsShape[rhsContractingDim])
+      return false;
+  }
+
+  return true;
+}
+
 } // namespace stablehlo
 
 } // namespace mlir

src/enzyme_ad/jax/Utils.h

@@ -716,6 +716,9 @@ negatedComparisonDirection(stablehlo::ComparisonDirection direction);
 
 bool reshapeIsTranspose(stablehlo::ReshapeOp reshapeOp);
 
+bool areValidDotGeneralInputs(Value lhs, Value rhs,
+                              stablehlo::DotDimensionNumbersAttr dotDimNumbers);
+
 } // namespace stablehlo
 
 } // namespace mlir

test/lit_tests/paddotgeneral2.mlir

@@ -0,0 +1,17 @@
+// RUN: enzymexlamlir-opt --pass-pipeline="any(enzyme-hlo-generate-td{patterns=pad_dot_general<1>(1)},transform-interpreter,enzyme-hlo-remove-transform)" %s | FileCheck %s
+
+func.func @fn(%arg0: tensor<f32>) -> (tensor<32x32xf32>, tensor<f32>) {
+    %c = stablehlo.constant dense<3> : tensor<32x32xi64>
+    %c_0 = stablehlo.constant dense<2> : tensor<32x32xi64>
+    %cst = stablehlo.constant dense<0.000000e+00> : tensor<f32>
+    %0 = stablehlo.reshape %arg0 : (tensor<f32>) -> tensor<1x1xf32>
+    %1 = stablehlo.pad %0, %cst, low = [2, 3], high = [29, 28], interior = [0, 0] : (tensor<1x1xf32>, tensor<f32>) -> tensor<32x32xf32>
+    %2 = stablehlo.convert %c_0 : (tensor<32x32xi64>) -> tensor<32x32xf32>
+    %3 = stablehlo.multiply %2, %1 : tensor<32x32xf32>
+    %4 = stablehlo.convert %c : (tensor<32x32xi64>) -> tensor<32x32xf32>
+    %5 = stablehlo.subtract %3, %4 : tensor<32x32xf32>
+    %6 = stablehlo.pad %0, %cst, low = [3, 2], high = [28, 29], interior = [0, 0] : (tensor<1x1xf32>, tensor<f32>) -> tensor<32x32xf32>
+    %7 = stablehlo.dot_general %6, %5, contracting_dims = [0] x [1], precision = [DEFAULT, DEFAULT] : (tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
+    // CHECK: %7 = stablehlo.dot_general %6, %5, contracting_dims = [0] x [1], precision = [DEFAULT, DEFAULT] : (tensor<32x32xf32>, tensor<32x32xf32>) -> tensor<32x32xf32>
+    return %7, %arg0 : tensor<32x32xf32>, tensor<f32>
+}