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Drop jinja2 in trained model serialization tests and use typed tests
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tests/unit/base/trained_model_serialization_unittest.cc
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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| #include "environments/LinearTestEnvironment.h" | ||
| #include "environments/MultiLabelTestEnvironment.h" | ||
| #include "environments/RegressionTestEnvironment.h" | ||
| #include "utils/Utils.h" | ||
| #include <gtest/gtest.h> | ||
| #include <shogun/base/some.h> | ||
| #include <shogun/features/DenseFeatures.h> | ||
| #include <shogun/io/CSVFile.h> | ||
| #include <shogun/io/SGIO.h> | ||
| #include <shogun/io/SerializableAsciiFile.h> | ||
| #include <shogun/io/SerializableHdf5File.h> | ||
| #include <shogun/kernel/GaussianKernel.h> | ||
| #include <shogun/labels/BinaryLabels.h> | ||
| #include <shogun/labels/Labels.h> | ||
| #include <shogun/labels/RegressionLabels.h> | ||
| #include <shogun/machine/Machine.h> | ||
|
|
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| using namespace shogun; | ||
|
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| extern LinearTestEnvironment* linear_test_env; | ||
| extern MultiLabelTestEnvironment* multilabel_test_env; | ||
| extern RegressionTestEnvironment* regression_test_env; | ||
|
|
||
| template <class T> | ||
| class TrainedModelSerializationFixture : public ::testing::Test | ||
| { | ||
| protected: | ||
| void SetUp() | ||
| { | ||
| machine = new T(); | ||
| SG_REF(machine) | ||
|
|
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| deserialized_machine = new T(); | ||
| SG_REF(deserialized_machine) | ||
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| this->load_data(this->machine->get_machine_problem_type()); | ||
| } | ||
|
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| void TearDown() | ||
| { | ||
| SG_UNREF(train_feats) | ||
| SG_UNREF(test_feats) | ||
| SG_UNREF(train_labels) | ||
| SG_UNREF(machine) | ||
| SG_UNREF(deserialized_machine) | ||
| } | ||
|
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| void load_data(EProblemType pt) | ||
| { | ||
| switch (pt) | ||
| { | ||
| case PT_BINARY: | ||
| case PT_CLASS: | ||
| { | ||
| std::shared_ptr<GaussianCheckerboard> mock_data = | ||
| linear_test_env->getBinaryLabelData(); | ||
| train_feats = mock_data->get_features_train(); | ||
| test_feats = mock_data->get_features_test(); | ||
| train_labels = mock_data->get_labels_train(); | ||
| break; | ||
| } | ||
|
|
||
| case PT_MULTICLASS: | ||
| { | ||
| std::shared_ptr<GaussianCheckerboard> mock_data = | ||
| multilabel_test_env->getMulticlassFixture(); | ||
| train_feats = mock_data->get_features_train(); | ||
| test_feats = mock_data->get_features_test(); | ||
| train_labels = mock_data->get_labels_train(); | ||
| break; | ||
| } | ||
|
|
||
| case PT_REGRESSION: | ||
| train_feats = regression_test_env->get_features_train(); | ||
| test_feats = regression_test_env->get_features_test(); | ||
| train_labels = regression_test_env->get_labels_train(); | ||
| break; | ||
|
|
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| default: | ||
| SG_SERROR("Unsupported problem type: %d\n", pt); | ||
| FAIL(); | ||
| } | ||
|
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| SG_REF(train_feats) | ||
| SG_REF(test_feats) | ||
| SG_REF(train_labels) | ||
| } | ||
|
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| bool serialize_machine( | ||
| CMachine* cmachine, std::string& filename, | ||
| bool store_model_features = false) | ||
| { | ||
| std::string class_name = cmachine->get_name(); | ||
| filename = "shogun-unittest-trained-model-serialization-" + class_name + | ||
| ".XXXXXX"; | ||
| generate_temp_filename(const_cast<char*>(filename.c_str())); | ||
|
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| CSerializableHdf5File* file = | ||
| new CSerializableHdf5File(filename.c_str(), 'w'); | ||
| cmachine->set_store_model_features(store_model_features); | ||
| bool save_success = cmachine->save_serializable(file); | ||
| file->close(); | ||
| SG_FREE(file); | ||
|
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| return save_success; | ||
| } | ||
|
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| bool deserialize_machine(CMachine* cmachine, std::string filename) | ||
| { | ||
| CSerializableHdf5File* file = | ||
| new CSerializableHdf5File(filename.c_str(), 'r'); | ||
| bool load_success = cmachine->load_serializable(file); | ||
|
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| file->close(); | ||
| SG_FREE(file); | ||
| int delete_success = unlink(filename.c_str()); | ||
|
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| return load_success && (delete_success == 0); | ||
| } | ||
|
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| CDenseFeatures<float64_t> *train_feats, *test_feats; | ||
| CLabels* train_labels; | ||
| T* machine; | ||
| T* deserialized_machine; | ||
| }; | ||
|
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| #include "trained_model_serialization_unittest.h" | ||
|
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| template <class T> | ||
| class TrainedMachineSerialization : public TrainedModelSerializationFixture<T> | ||
| { | ||
| }; | ||
|
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| TYPED_TEST_CASE(TrainedMachineSerialization, MachineTypes); | ||
|
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| TYPED_TEST(TrainedMachineSerialization, Test) | ||
| { | ||
| this->machine->set_labels(this->train_labels); | ||
| this->machine->train(this->train_feats); | ||
|
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| /* to avoid serialization of the data */ | ||
| // machine->set_features(NULL); | ||
| // machine->set_labels(NULL); | ||
|
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| auto predictions = wrap<CLabels>(this->machine->apply(this->test_feats)); | ||
|
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| std::string filename; | ||
| ASSERT_TRUE(this->serialize_machine(this->machine, filename)); | ||
|
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| ASSERT_TRUE( | ||
| this->deserialize_machine(this->deserialized_machine, filename)); | ||
|
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| auto deserialized_predictions = | ||
| wrap<CLabels>(this->deserialized_machine->apply(this->test_feats)); | ||
|
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| set_global_fequals_epsilon(1e-7); | ||
| ASSERT(predictions->equals(deserialized_predictions)) | ||
| set_global_fequals_epsilon(0); | ||
| } | ||
|
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| template <class T> | ||
| class TrainedKernelMachineSerialization | ||
| : public TrainedModelSerializationFixture<T> | ||
| { | ||
| }; | ||
|
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| TYPED_TEST_CASE(TrainedKernelMachineSerialization, KernelMachineTypes); | ||
|
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| TYPED_TEST(TrainedKernelMachineSerialization, Test) | ||
| { | ||
| CGaussianKernel* kernel = new CGaussianKernel(2.0); | ||
| this->machine->set_kernel(kernel); | ||
| this->machine->set_labels(this->train_labels); | ||
|
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| this->machine->train(this->train_feats); | ||
|
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| auto predictions = wrap<CLabels>(this->machine->apply(this->test_feats)); | ||
|
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| for (auto store_model_features : {false, true}) | ||
| { | ||
| std::string filename; | ||
| ASSERT_TRUE( | ||
| this->serialize_machine( | ||
| this->machine, filename, store_model_features)); | ||
|
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| ASSERT_TRUE( | ||
| this->deserialize_machine(this->deserialized_machine, filename)); | ||
|
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| auto deserialized_predictions = | ||
| wrap<CLabels>(this->deserialized_machine->apply(this->test_feats)); | ||
|
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| // allow for lossy serialization format | ||
| set_global_fequals_epsilon(1e-6); | ||
| ASSERT(predictions->equals(deserialized_predictions)) | ||
| set_global_fequals_epsilon(0); | ||
| } | ||
| } |
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