// CHECK-NEXT: mhlo.or
  %0 = "tf.BitwiseOr"(%arg0, %arg1) : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>
  func.return %0: tensor<4xi32>
}

// CHECK-LABEL: func @bitwise_or_unsigned
func.func @bitwise_or_unsigned(%arg0: tensor<4xui32>, %arg1: tensor<4xui32>) -> tensor<4xui32> {
  // CHECK-NEXT: mhlo.or
  %0 = "tf.BitwiseOr"(%arg0, %arg1) : (tensor<4xui32>, tensor<4xui32>) -> tensor<4xui32>

// CHECK-LABEL:   func @bitwise_or(
// CHECK-SAME:                     %[[VAL_0:.*]]: tensor<4xi32>,
// CHECK-SAME:                     %[[VAL_1:.*]]: tensor<4xi32>) -> tensor<4xi32> {
// CHECK:           %[[VAL_2:.*]] = "tf.BitwiseOr"(%[[VAL_0]], %[[VAL_1]]) : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>
// CHECK:           return %[[VAL_2]] : tensor<4xi32>
// CHECK:         }

            // Binary
            "Add", "AddV2", "Sub", "Mul", "Div", "Atan2", "Complex", "DivNoNan",
            "MulNoNan", "FloorDiv", "Xlogy", "Xlog1py", "Xdivy", "FloorMod",
            "BitwiseAnd", "BitwiseOr", "BitwiseXor", "LeftShift", "RightShift",
            "LogicalAnd", "LogicalOr", "Mod", "Maximum", "Minimum", "RealDiv",
            "ReciprocalGrad", "RsqrtGrad", "SqrtGrad", "TruncateDiv",

    TF_IntTensor:$y
  );

  let results = (outs
    TF_IntTensor:$z
  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}

def TF_BitwiseOrOp : TF_Op<"BitwiseOr", [Commutative, Pure, ResultsBroadcastableShape]>,
                     WithBroadcastableBinOpBuilder {
  let summary = "Elementwise computes the bitwise OR of `x` and `y`.";

  let description = [{