#pragma once

#ifdef __GNUC__
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wunused-parameter"
#endif

//===- ModelUnderTrainingRunner.h -- 'development' mode runner --*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//

#ifndef LLVM_ANALYSIS_MODELUNDERTRAININGRUNNER_H
#define LLVM_ANALYSIS_MODELUNDERTRAININGRUNNER_H

#include "llvm/ADT/STLExtras.h"
#include "llvm/ADT/iterator_range.h"
#include "llvm/Analysis/TensorSpec.h"
#include "llvm/Config/llvm-config.h"

#ifdef LLVM_HAVE_TFLITE
#include "llvm/Analysis/MLModelRunner.h"
#include "llvm/Analysis/Utils/TFUtils.h"
#include "llvm/IR/LLVMContext.h"
#include "llvm/IR/PassManager.h"

namespace llvm {

/// ModelUnderTrainingRunner - training mode implementation. It uses TF C APIs
/// to dynamically load and evaluate a TF SavedModel
/// (https://www.tensorflow.org/guide/saved_model). Runtime performance is
/// sacrificed for ease of use while training.
class ModelUnderTrainingRunner final : public MLModelRunner {
public:
  // Disallows copy and assign.
  ModelUnderTrainingRunner(const ModelUnderTrainingRunner &) = delete;
  ModelUnderTrainingRunner &
  operator=(const ModelUnderTrainingRunner &) = delete;

  const std::vector<TensorSpec> &extraOutputsForLoggingSpecs() const {
    return ExtraOutputsForLogging;
  }

  const void *getUntypedExtraOutputValue(size_t ExtraOutputIndex) const {
    return lastEvaluationResult()->getUntypedTensorValue(ExtraOutputIndex + 1);
  }

  const std::optional<TFModelEvaluator::EvaluationResult> &
  lastEvaluationResult() const {
    return LastEvaluationResult;
  }
  static bool classof(const MLModelRunner *R) {
    return R->getKind() == MLModelRunner::Kind::Development;
  }

  static std::unique_ptr<ModelUnderTrainingRunner>
  createAndEnsureValid(LLVMContext &Ctx, const std::string &ModelPath,
                       StringRef DecisionName,
                       const std::vector<TensorSpec> &InputSpecs,
                       StringRef OutputSpecsPathOverride = "");

  ModelUnderTrainingRunner(
      LLVMContext &Ctx, const std::string &ModelPath,
      const std::vector<TensorSpec> &InputSpecs,
      const std::vector<TensorSpec> &OutputSpecs,
      const std::vector<TensorSpec> &ExtraOutputsForLogging = {});

  bool isValid() const { return !!Evaluator; }

private:
  std::unique_ptr<TFModelEvaluator> Evaluator;
  const std::vector<TensorSpec> OutputSpecs;
  const std::vector<TensorSpec> ExtraOutputsForLogging;
  std::optional<TFModelEvaluator::EvaluationResult> LastEvaluationResult;
  void *evaluateUntyped() override;
};

} // namespace llvm
#endif // define(LLVM_HAVE_TFLITE)
#endif // LLVM_ANALYSIS_MODELUNDERTRAININGRUNNER_H

#ifdef __GNUC__
#pragma GCC diagnostic pop
#endif