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#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/Config/llvm-config.h"
#ifdef LLVM_HAVE_TF_API
#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<LoggedFeatureSpec> &outputLoggedFeatureSpecs() const {
return OutputSpecs;
}
const 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 = "");
private:
ModelUnderTrainingRunner(LLVMContext &Ctx, const std::string &ModelPath,
const std::vector<TensorSpec> &InputSpecs,
const std::vector<LoggedFeatureSpec> &OutputSpecs);
std::unique_ptr<TFModelEvaluator> Evaluator;
const std::vector<LoggedFeatureSpec> OutputSpecs;
Optional<TFModelEvaluator::EvaluationResult> LastEvaluationResult;
void *evaluateUntyped() override;
void *getTensorUntyped(size_t Index) override;
bool isValid() const { return !!Evaluator; }
};
} // namespace llvm
#endif // define(LLVM_HAVE_TF_API)
#endif // LLVM_ANALYSIS_MODELUNDERTRAININGRUNNER_H
#ifdef __GNUC__
#pragma GCC diagnostic pop
#endif
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