/* 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_CPU_CPU_HLO_SUPPORT_CHECKER_H_
#define TENSORFLOW_COMPILER_XLA_SERVICE_CPU_CPU_HLO_SUPPORT_CHECKER_H_

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

namespace xla {

// This pass should run early in the HLO pipeline and checks for HLO constructs
// which are not supported by the CPU backend and cannot be removed via HLO
// transformations (eg, sparse layouts).
class CpuHloSupportChecker : public HloModulePass {
 public:
  CpuHloSupportChecker() = default;
  ~CpuHloSupportChecker() override = default;

  absl::string_view name() const override { return "cpu_hlo_support_checker"; }

  // Note: always returns false (no instructions are ever modified by this
  // pass).
  StatusOr<bool> Run(HloModule* module) override;
};

}  // namespace xla

#endif  // TENSORFLOW_COMPILER_XLA_SERVICE_CPU_CPU_HLO_SUPPORT_CHECKER_H_
