| //===- ModelUnderTrainingRunner.cpp - 'development' mode 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 |
| // |
| //===----------------------------------------------------------------------===// |
| // |
| // Implementation of a MLModelRunner for 'development' mode, i.e. evaluation |
| // happens off a model that's provided from the command line and is interpreted. |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #include "llvm/Config/config.h" |
| #if defined(LLVM_HAVE_TF_API) |
| |
| #include "llvm/Analysis/ModelUnderTrainingRunner.h" |
| |
| using namespace llvm; |
| |
| ModelUnderTrainingRunner::ModelUnderTrainingRunner( |
| LLVMContext &Ctx, const std::string &ModelPath, |
| const std::vector<TensorSpec> &InputSpecs, |
| const std::vector<LoggedFeatureSpec> &OutputSpecs) |
| : MLModelRunner(Ctx, MLModelRunner::Kind::Development), |
| OutputSpecs(OutputSpecs) { |
| Evaluator = std::make_unique<TFModelEvaluator>( |
| ModelPath, InputSpecs, [&](size_t I) { return OutputSpecs[I].Spec; }, |
| OutputSpecs.size()); |
| if (!Evaluator || !Evaluator->isValid()) { |
| Ctx.emitError("Failed to create saved model evaluator"); |
| Evaluator.reset(); |
| return; |
| } |
| } |
| |
| void *ModelUnderTrainingRunner::evaluateUntyped() { |
| LastEvaluationResult = Evaluator->evaluate(); |
| if (!LastEvaluationResult.hasValue()) { |
| Ctx.emitError("Error evaluating model."); |
| return nullptr; |
| } |
| return LastEvaluationResult->getUntypedTensorValue(0); |
| } |
| |
| void *ModelUnderTrainingRunner::getTensorUntyped(size_t Index) { |
| return Evaluator->getUntypedInput(Index); |
| } |
| |
| std::unique_ptr<ModelUnderTrainingRunner> |
| ModelUnderTrainingRunner::createAndEnsureValid( |
| LLVMContext &Ctx, const std::string &ModelPath, StringRef DecisionName, |
| const std::vector<TensorSpec> &InputSpecs, |
| StringRef OutputSpecsPathOverride) { |
| std::unique_ptr<ModelUnderTrainingRunner> MUTR; |
| if (auto MaybeOutputSpecs = loadOutputSpecs(Ctx, DecisionName, ModelPath, |
| OutputSpecsPathOverride)) |
| MUTR.reset(new ModelUnderTrainingRunner(Ctx, ModelPath, InputSpecs, |
| *MaybeOutputSpecs)); |
| if (MUTR && MUTR->isValid()) |
| return MUTR; |
| |
| Ctx.emitError("Could not load the policy model from the provided path"); |
| return nullptr; |
| } |
| |
| #endif // defined(LLVM_HAVE_TF_API) |