diff --git a/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.h b/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.h
index b314bd4..b778e94 100644
--- a/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.h
+++ b/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.h
@@ -17,6 +17,7 @@ limitations under the License.
 #define TENSORFLOW_COMPILER_MLIR_HLO_INCLUDE_MLIR_HLO_DIALECT_MHLO_IR_CHLO_OPS_H_
 
 #include "llvm/ADT/StringRef.h"
+#include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
 #include "mlir-hlo/Dialect/mhlo/IR/infer_fusibility_op_interface.h"
 #include "mlir/IR/BuiltinTypes.h"
 #include "mlir/IR/Dialect.h"
diff --git a/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.td b/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.td
index c9e46ea..2116556 100644
--- a/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.td
+++ b/include/mlir-hlo/Dialect/mhlo/IR/chlo_ops.td
@@ -422,14 +422,28 @@ def HLOClient_BroadcastComplexOp : HLOClient_BroadcastBinaryElementwiseOp<
 
 class HLOClient_UnaryElementwiseOp<string mnemonic, list<OpTrait> traits,
     Type ArgTensorType, Type ResultTensorType> : HLOClient_Op<mnemonic,
-    traits # [InferFusibilityOpInterface, NoSideEffect,
-    SameOperandsAndResultShape]> {
+    traits # [InferFusibilityOpInterface, NoSideEffect, Elementwise,
+    SameOperandsAndResultShape, InferShapedTypeOpInterface]> {
   let arguments = (ins ArgTensorType:$operand);
   let results = (outs ResultTensorType:$result);
 
   let assemblyFormat = [{
     $operand attr-dict `:` type($operand) `->` type($result)
   }];
+
+  let extraClassDeclaration = [{
+    static LogicalResult inferReturnTypeComponents(MLIRContext* context,
+        Optional<Location> location, ValueRange operands,
+        DictionaryAttr attributes, RegionRange regions,
+        SmallVectorImpl<ShapedTypeComponents>& inferedReturnShapes) {
+      return failure();
+    }
+    LogicalResult reifyReturnTypeShapes(OpBuilder& builder,
+        SmallVectorImpl<Value>& reifiedReturnShapes) {
+      return ::mlir::mhlo::deriveShapeFromFirstOperand(&builder, getOperation(),
+          &reifiedReturnShapes);
+    }
+  }];
 }
 
 def HLOClient_AcosOp : HLOClient_UnaryElementwiseOp<"acos",
diff --git a/lib/Dialect/mhlo/IR/chlo_ops.cc b/lib/Dialect/mhlo/IR/chlo_ops.cc
index 1fa000e..ad149e2 100644
--- a/lib/Dialect/mhlo/IR/chlo_ops.cc
+++ b/lib/Dialect/mhlo/IR/chlo_ops.cc
@@ -16,7 +16,6 @@ limitations under the License.
 #include "mlir-hlo/Dialect/mhlo/IR/chlo_ops.h"
 
 #include "llvm/ADT/APFloat.h"
-#include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
 #include "mlir-hlo/utils/broadcast_utils.h"
 #include "mlir/IR/Attributes.h"
 #include "mlir/IR/Builders.h"
diff --git a/tests/rank-specialization.mlir b/tests/rank-specialization.mlir
index 6258ef0..aff12b9 100644
--- a/tests/rank-specialization.mlir
+++ b/tests/rank-specialization.mlir
@@ -66,3 +66,22 @@ func @select_mixed(%pred: tensor<*xi1>, %arg1: tensor<*xf32>,
       : (tensor<*xi1>, tensor<*xf32>, tensor<2xf32>) -> tensor<*xf32>
   return %0 : tensor<*xf32>
 }
+
+// -----
+
+// Unary CHLO operation.
+// CHECK-LABEL: @tan
+// CHECK-SAME: (%[[ARG:.*]]: tensor<*xf32>) -> tensor<*xf32>
+func @tan(%arg : tensor<*xf32>) -> tensor<*xf32> {
+  // CHECK: %[[RES:.*]] = "chlo.rank_specialization_cluster"(%[[ARG]]) ( {
+  // CHECK: ^bb0(%[[ARG_:.*]]: tensor<*xf32>)
+  // CHECK:   %[[TMP0:.*]] = chlo.tan %[[ARG_]]
+  // CHECK:   %[[TMP1:.*]] = chlo.tan %[[TMP0]]
+  // CHECK:   %[[TMP2:.*]] = chlo.tan %[[TMP1]]
+  // CHECK:   "chlo.rank_specialization_cluster_yield"(%[[TMP2]])
+  // CHECK: return %[[RES]]
+  %0 = chlo.tan %arg : tensor<*xf32> -> tensor<*xf32>
+  %1 = chlo.tan %0 : tensor<*xf32> -> tensor<*xf32>
+  %2 = chlo.tan %1 : tensor<*xf32> -> tensor<*xf32>
+  return %2 : tensor<*xf32>
+}