// -2147483648 is MIN for INT32
  %0 = mhlo.constant dense<-2147483648> : tensor<i32>
  %1 = mhlo.reduce(%arg0 init: %0) across dimensions = [1] : (tensor<1x4xi32>, tensor<i32>) -> tensor<1xi32>
   reducer(%arg2: tensor<i32>, %arg3: tensor<i32>)  {
    %892 = mhlo.maximum %arg2, %arg3 : tensor<i32>
    "mhlo.return"(%892) : (tensor<i32>) -> ()
  }
  func.return %1 : tensor<1xi32>
}

      block->addArguments({type, type}, SmallVector<Location, 2>(2, loc));

      auto reducer = rewriter.create<CompareOp>(loc, block->getArgument(0),
                                                block->getArgument(1),
                                                ComparisonDirection::GE);
      rewriter.create<ReturnOp>(loc, reducer.getResult());
    }

    rewriter.replaceOp(op, result);

    return success();

  // CHECK: return %[[REDUCE]]
  %0 = "tf.XlaVariadicReduceV2"(%arg0, %arg1) {_XlaHasReferenceVars = false, device = "/job:localhost/replica:0/task:0/device:XLA_GPU:0", dimensions_to_reduce = [0], operandSegmentSizes = array<i32: 1, 1>, reducer = @sum_reducer} : (tensor<2x3xcomplex<f64>>, tensor<complex<f64>>) -> tensor<3xcomplex<f64>>
  func.return %0 : tensor<3xcomplex<f64>>
}