6024e5c395
clang 20.0.0 (based on r547379) from build 12806354. Bug: http://b/379133546 Test: N/A Change-Id: I2eb8938af55d809de674be63cb30cf27e801862b Upstream-Commit: ad834e67b1105d15ef907f6255d4c96e8e733f57
82 lines
2.7 KiB
C++
82 lines
2.7 KiB
C++
//===- MLModelRunner.h ---- ML model runner interface -----------*- C++ -*-===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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//
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#ifndef LLVM_ANALYSIS_MLMODELRUNNER_H
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#define LLVM_ANALYSIS_MLMODELRUNNER_H
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#include "llvm/Analysis/TensorSpec.h"
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#include "llvm/IR/PassManager.h"
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namespace llvm {
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class LLVMContext;
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/// MLModelRunner interface: abstraction of a mechanism for evaluating a
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/// ML model. More abstractly, evaluating a function that has as tensors as
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/// arguments, described via TensorSpecs, and returns a tensor. Currently, the
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/// latter is assumed to be a scalar, in absence of more elaborate scenarios.
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/// NOTE: feature indices are expected to be consistent all accross
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/// MLModelRunners (pertaining to the same model), and also Loggers (see
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/// TFUtils.h)
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class MLModelRunner {
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public:
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// Disallows copy and assign.
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MLModelRunner(const MLModelRunner &) = delete;
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MLModelRunner &operator=(const MLModelRunner &) = delete;
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virtual ~MLModelRunner() = default;
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template <typename T> T evaluate() {
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return *reinterpret_cast<T *>(evaluateUntyped());
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}
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template <typename T, typename I> T *getTensor(I FeatureID) {
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return reinterpret_cast<T *>(
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getTensorUntyped(static_cast<size_t>(FeatureID)));
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}
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template <typename T, typename I> const T *getTensor(I FeatureID) const {
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return reinterpret_cast<const T *>(
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getTensorUntyped(static_cast<size_t>(FeatureID)));
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}
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void *getTensorUntyped(size_t Index) { return InputBuffers[Index]; }
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const void *getTensorUntyped(size_t Index) const {
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return (const_cast<MLModelRunner *>(this))->getTensorUntyped(Index);
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}
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enum class Kind : int { Unknown, Release, Development, NoOp, Interactive };
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Kind getKind() const { return Type; }
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virtual void switchContext(StringRef Name) {}
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protected:
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MLModelRunner(LLVMContext &Ctx, Kind Type, size_t NrInputs)
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: Ctx(Ctx), Type(Type), InputBuffers(NrInputs) {
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assert(Type != Kind::Unknown);
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}
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virtual void *evaluateUntyped() = 0;
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void setUpBufferForTensor(size_t Index, const TensorSpec &Spec,
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void *Buffer) {
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if (!Buffer) {
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OwnedBuffers.emplace_back(Spec.getTotalTensorBufferSize());
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Buffer = OwnedBuffers.back().data();
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}
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InputBuffers[Index] = Buffer;
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}
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LLVMContext &Ctx;
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const Kind Type;
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private:
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std::vector<void *> InputBuffers;
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std::vector<std::vector<char *>> OwnedBuffers;
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};
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} // namespace llvm
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#endif // LLVM_ANALYSIS_MLMODELRUNNER_H
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