%values, %indices = "tf.ApproxTopK"(%arg0) {aggregate_to_topk = true, is_max_k = true, k = 4 : i64, recall_target = 8.500000e-01 : f32, reduction_dimension = 1 : i64, reduction_input_size_override = -1 : i64} : (tensor<1x4xf32>) -> (tensor<1x4xf32>, tensor<1x4xi32>)
  func.return %values, %indices: tensor<1x4xf32>, tensor<1x4xi32>

  // CHECK-LABEL: approx_top_k_with_max_k_last_reduction_dimension

      auto name = attr.getName();
      if (!(name == "top_k" || name == "reduction_dim" ||
            name == "recall_target" || name == "aggregate_to_topk" ||
            name == "reduction_input_size_override" || name == "is_fallback")) {
        return op.emitOpError()
               << name.getValue() << " is not a supported backend_config"
               << " attribute for ApproxTopK";
      }
    }