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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/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
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