diff --git a/stablehlo/dialect/TypeInference.cpp b/stablehlo/dialect/TypeInference.cpp
index a7133ae2139..31af9fe3d68 100644
--- a/stablehlo/dialect/TypeInference.cpp
+++ b/stablehlo/dialect/TypeInference.cpp
@@ -1891,6 +1891,7 @@ LogicalResult inferDotGeneralOp(
     return emitOptionalError(location,
                              "lhs and rhs should have the same "
                              "number of batching dimensions");
+
   // dot_general_c2
   if (lhsContractingDimensions.size() != rhsContractingDimensions.size())
     return emitOptionalError(location,
@@ -1911,6 +1912,7 @@ LogicalResult inferDotGeneralOp(
     }
     return success();
   };
+
   // dot_general_c3
   if (failed(checkDimsDistinct(lhsBatchingDimensions, lhsContractingDimensions,
                                dimSet, "lhs_batching_dimensions",
@@ -1934,11 +1936,11 @@ LogicalResult inferDotGeneralOp(
                                " is out of range: ", "[0, ", rank, ")");
     return success();
   };
+
   auto lhsRankedType = lhsType.dyn_cast<RankedTensorType>();
-  auto rhsRankedType = rhsType.dyn_cast<RankedTensorType>();
-  // dot_general_c5
-  // dot_general_c6
   if (lhsRankedType) {
+    // dot_general_c5
+    // dot_general_c6
     if (failed(checkDimsInRange(lhsRankedType.getRank(), lhsBatchingDimensions,
                                 "lhs_batching_dimensions")) ||
         failed(checkDimsInRange(lhsRankedType.getRank(),
@@ -1946,9 +1948,11 @@ LogicalResult inferDotGeneralOp(
                                 "lhs_contracting_dimensions")))
       return failure();
   }
-  // dot_general_c7
-  // dot_general_c8
+
+  auto rhsRankedType = rhsType.dyn_cast<RankedTensorType>();
   if (rhsRankedType) {
+    // dot_general_c7
+    // dot_general_c8
     if (failed(checkDimsInRange(rhsRankedType.getRank(), rhsBatchingDimensions,
                                 "rhs_batching_dimensions")) ||
         failed(checkDimsInRange(rhsRankedType.getRank(),
@@ -1999,6 +2003,7 @@ LogicalResult inferDotGeneralOp(
     if (!llvm::is_contained(rhsBatchingDimensions, i) &&
         !llvm::is_contained(rhsContractingDimensions, i))
       dimensions.push_back(rhsShape[i]);
+
   // dot_general_c12
   inferredReturnShapes.emplace_back(dimensions);
   return success();
diff --git a/stablehlo/tests/ops_stablehlo.mlir b/stablehlo/tests/ops_stablehlo.mlir
index 8d743120301..a6ebfd781b7 100644
--- a/stablehlo/tests/ops_stablehlo.mlir
+++ b/stablehlo/tests/ops_stablehlo.mlir
@@ -3006,36 +3006,6 @@ func.func @dot_general_c2(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>) ->
 
 // -----
 
-func.func @dot_general_c3(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
-  // expected-error @+1 {{has duplicated dimension from lhs_batching_dimensions and lhs_contracting_dimensions: 0}}
-  %0 = "stablehlo.dot_general"(%arg0, %arg1) {
-    dot_dimension_numbers = #stablehlo.dot<
-      lhs_batching_dimensions = [0, 0],
-      rhs_batching_dimensions = [0, 0],
-      lhs_contracting_dimensions = [1],
-      rhs_contracting_dimensions = [1]
-    >
-  } : (tensor<?x?x?xf32>, tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
-  func.return %0 : tensor<?x?x?xf32>
-}
-
-// -----
-
-func.func @dot_general_c3(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
-  // expected-error @+1 {{has duplicated dimension from lhs_batching_dimensions and lhs_contracting_dimensions: 1}}
-  %0 = "stablehlo.dot_general"(%arg0, %arg1) {
-    dot_dimension_numbers = #stablehlo.dot<
-      lhs_batching_dimensions = [0],
-      rhs_batching_dimensions = [0],
-      lhs_contracting_dimensions = [1, 1],
-      rhs_contracting_dimensions = [1, 1]
-    >
-  } : (tensor<?x?x?xf32>, tensor<?x?x?xf32>) -> tensor<?x?x?xf32>
-  func.return %0 : tensor<?x?x?xf32>
-}
-
-// -----
-
 func.func @dot_general_c3(%arg0: tensor<?x?x?xf32>, %arg1: tensor<?x?x?xf32>) -> tensor<?x?x?xf32> {
   // expected-error @+1 {{has duplicated dimension from lhs_batching_dimensions and lhs_contracting_dimensions: 0}}
   %0 = "stablehlo.dot_general"(%arg0, %arg1) {