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#pragma once
#ifdef __GNUC__
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wunused-parameter"
#endif
//===- ReleaseModeModelRunner.h - Fast, precompiled model runner ---------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// This file implements a model runner wrapping an AOT compiled ML model.
// Only inference is supported.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_ANALYSIS_RELEASEMODEMODELRUNNER_H
#define LLVM_ANALYSIS_RELEASEMODEMODELRUNNER_H
#include "llvm/Analysis/MLModelRunner.h"
#include <memory>
#include <vector>
using namespace llvm;
namespace llvm {
/// ReleaseModeModelRunner - production mode implementation of the
/// MLModelRunner. It uses an AOT-compiled SavedModel for efficient execution.
template <class TGen>
class ReleaseModeModelRunner final : public MLModelRunner {
public:
/// FeatureNames' type should be an indexed collection of std::string, like
/// std::array or std::vector, that has a size() method.
template <class FType>
ReleaseModeModelRunner(LLVMContext &Ctx, const FType &FeatureNames,
StringRef DecisionName, StringRef FeedPrefix = "feed_",
StringRef FetchPrefix = "fetch_")
: MLModelRunner(Ctx, MLModelRunner::Kind::Release),
CompiledModel(std::make_unique<TGen>()) {
assert(CompiledModel && "The CompiledModel should be valid");
const size_t FeatureCount = FeatureNames.size();
FeatureIndices.resize(FeatureCount);
for (size_t I = 0; I < FeatureCount; ++I) {
const int Index =
CompiledModel->LookupArgIndex(FeedPrefix.str() + FeatureNames[I]);
assert(Index >= 0 && "Cannot find Feature in inlining model");
FeatureIndices[I] = Index;
}
ResultIndex = CompiledModel->LookupResultIndex(FetchPrefix.str() +
DecisionName.str());
assert(ResultIndex >= 0 && "Cannot find DecisionName in inlining model");
}
virtual ~ReleaseModeModelRunner() = default;
static bool classof(const MLModelRunner *R) {
return R->getKind() == MLModelRunner::Kind::Release;
}
private:
void *evaluateUntyped() override {
CompiledModel->Run();
return CompiledModel->result_data(ResultIndex);
}
void *getTensorUntyped(size_t Index) override {
return reinterpret_cast<char *>(
CompiledModel->arg_data(FeatureIndices[Index]));
}
std::vector<int32_t> FeatureIndices;
int32_t ResultIndex = -1;
std::unique_ptr<TGen> CompiledModel;
};
} // namespace llvm
#endif // LLVM_ANALYSIS_RELEASEMODEMODELRUNNER_H
#ifdef __GNUC__
#pragma GCC diagnostic pop
#endif
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