/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_COMPILER_XLA_SERVICE_TUPLE_UTIL_H_
#define TENSORFLOW_COMPILER_XLA_SERVICE_TUPLE_UTIL_H_

#include "tensorflow/compiler/xla/service/hlo_instruction.h"

namespace xla {
class TupleUtil {
 public:
  // Generates HLO instructions to get a prefix tuple from `input_tuple` (which
  // must be of tuple shape) of length `elements`.  Returns the root of the
  // graph of instructions generated.
  //
  // The instructions are generated into the computation containing
  // `input_tuple`.
  static HloInstruction* ExtractPrefix(HloInstruction* input_tuple,
                                       int64 elements);

  // Generates HLO instructions to create a tuple that consists of the values in
  // `trailing_values` appended to `input_tuple` (which must be of tuple shape).
  // Returns the root of the graph of instructions generated.
  //
  // The instructions are generated into the computation containing
  // `input_tuple`.
  static HloInstruction* AppendSuffix(
      HloInstruction* input_tuple,
      tensorflow::gtl::ArraySlice<HloInstruction*> trailing_values);
};
}  // namespace xla

#endif  // TENSORFLOW_COMPILER_XLA_SERVICE_TUPLE_UTIL_H_
