119 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			C++
		
	
	
	
			
		
		
	
	
			119 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			C++
		
	
	
	
| //===- MLModelRunnerTest.cpp - test for MLModelRunner ---------------------===//
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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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| #include "llvm/Analysis/MLModelRunner.h"
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| #include "llvm/Analysis/NoInferenceModelRunner.h"
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| #include "llvm/Analysis/ReleaseModeModelRunner.h"
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| #include "gtest/gtest.h"
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| 
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| using namespace llvm;
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| 
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| namespace llvm {
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| // This is a mock of the kind of AOT-generated model evaluator. It has 2 tensors
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| // of shape {1}, and 'evaluation' adds them.
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| // The interface is the one expected by ReleaseModelRunner.
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| class MockAOTModel final {
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|   int64_t A = 0;
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|   int64_t B = 0;
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|   int64_t R = 0;
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| 
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| public:
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|   MockAOTModel() = default;
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|   int LookupArgIndex(const std::string &Name) {
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|     if (Name == "prefix_a")
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|       return 0;
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|     if (Name == "prefix_b")
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|       return 1;
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|     return -1;
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|   }
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|   int LookupResultIndex(const std::string &) { return 0; }
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|   void Run() { R = A + B; }
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|   void *result_data(int RIndex) {
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|     if (RIndex == 0)
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|       return &R;
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|     return nullptr;
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|   }
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|   void *arg_data(int Index) {
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|     switch (Index) {
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|     case 0:
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|       return &A;
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|     case 1:
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|       return &B;
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|     default:
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|       return nullptr;
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|     }
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|   }
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| };
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| } // namespace llvm
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| 
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| TEST(NoInferenceModelRunner, AccessTensors) {
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|   const std::vector<TensorSpec> Inputs{
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|       TensorSpec::createSpec<int64_t>("F1", {1}),
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|       TensorSpec::createSpec<int64_t>("F2", {10}),
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|       TensorSpec::createSpec<float>("F2", {5}),
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|   };
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|   LLVMContext Ctx;
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|   NoInferenceModelRunner NIMR(Ctx, Inputs);
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|   NIMR.getTensor<int64_t>(0)[0] = 1;
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|   std::memcpy(NIMR.getTensor<int64_t>(1),
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|               std::vector<int64_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}.data(),
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|               10 * sizeof(int64_t));
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|   std::memcpy(NIMR.getTensor<float>(2),
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|               std::vector<float>{0.1f, 0.2f, 0.3f, 0.4f, 0.5f}.data(),
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|               5 * sizeof(float));
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|   ASSERT_EQ(NIMR.getTensor<int64_t>(0)[0], 1);
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|   ASSERT_EQ(NIMR.getTensor<int64_t>(1)[8], 9);
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|   ASSERT_EQ(NIMR.getTensor<float>(2)[1], 0.2f);
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| }
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| 
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| TEST(ReleaseModeRunner, NormalUse) {
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|   LLVMContext Ctx;
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|   std::vector<TensorSpec> Inputs{TensorSpec::createSpec<int64_t>("a", {1}),
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|                                  TensorSpec::createSpec<int64_t>("b", {1})};
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|   auto Evaluator = std::make_unique<ReleaseModeModelRunner<MockAOTModel>>(
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|       Ctx, Inputs, "", "prefix_");
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|   *Evaluator->getTensor<int64_t>(0) = 1;
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|   *Evaluator->getTensor<int64_t>(1) = 2;
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|   EXPECT_EQ(Evaluator->evaluate<int64_t>(), 3);
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(0), 1);
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(1), 2);
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| }
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| 
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| TEST(ReleaseModeRunner, ExtraFeatures) {
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|   LLVMContext Ctx;
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|   std::vector<TensorSpec> Inputs{TensorSpec::createSpec<int64_t>("a", {1}),
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|                                  TensorSpec::createSpec<int64_t>("b", {1}),
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|                                  TensorSpec::createSpec<int64_t>("c", {1})};
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|   auto Evaluator = std::make_unique<ReleaseModeModelRunner<MockAOTModel>>(
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|       Ctx, Inputs, "", "prefix_");
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|   *Evaluator->getTensor<int64_t>(0) = 1;
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|   *Evaluator->getTensor<int64_t>(1) = 2;
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|   *Evaluator->getTensor<int64_t>(2) = -3;
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|   EXPECT_EQ(Evaluator->evaluate<int64_t>(), 3);
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(0), 1);
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(1), 2);
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(2), -3);
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| }
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| 
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| TEST(ReleaseModeRunner, ExtraFeaturesOutOfOrder) {
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|   LLVMContext Ctx;
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|   std::vector<TensorSpec> Inputs{
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|       TensorSpec::createSpec<int64_t>("a", {1}),
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|       TensorSpec::createSpec<int64_t>("c", {1}),
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|       TensorSpec::createSpec<int64_t>("b", {1}),
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|   };
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|   auto Evaluator = std::make_unique<ReleaseModeModelRunner<MockAOTModel>>(
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|       Ctx, Inputs, "", "prefix_");
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|   *Evaluator->getTensor<int64_t>(0) = 1;         // a
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|   *Evaluator->getTensor<int64_t>(1) = 2;         // c
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|   *Evaluator->getTensor<int64_t>(2) = -3;        // b
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|   EXPECT_EQ(Evaluator->evaluate<int64_t>(), -2); // a + b
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(0), 1);
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(1), 2);
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|   EXPECT_EQ(*Evaluator->getTensor<int64_t>(2), -3);
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| } |