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Add unit test to cover TreeEnsembleClassifier applied to binary classification and 2 classes (#3230)

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* Add unit test to cover TreeEnsembleClassifier for binary classification
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Xavier Dupré 2020-03-18 11:32:58 +01:00 committed by GitHub
parent 88c65f8add
commit bd348ec6ca
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1 changed files with 58 additions and 0 deletions
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onnxruntime/test/providers/cpu/ml/tree_ensembler_classifier_test.cc
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@ -151,5 +151,63 @@ TEST(MLOpTest, TreeEnsembleClassifierBinary) {
test.Run();
}
TEST(MLOpTest, TreeEnsembleClassifierBinaryProbabilities) {
OpTester test("TreeEnsembleClassifier", 1, onnxruntime::kMLDomain);
std::vector<int64_t> lefts = {1, -1, 3, -1, -1, 1, -1, 3, 4, -1, -1, -1, 1, 2, -1, 4, -1, -1, -1};
std::vector<int64_t> rights = {2, -1, 4, -1, -1, 2, -1, 6, 5, -1, -1, -1, 6, 3, -1, 5, -1, -1, -1};
std::vector<int64_t> treeids = {0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2};
std::vector<int64_t> nodeids = {0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 5, 6, 0, 1, 2, 3, 4, 5, 6};
std::vector<int64_t> featureids = {2, -2, 0, -2, -2, 0, -2, 2, 1, -2, -2, -2, 0, 2, -2, 1, -2, -2, -2};
std::vector<float> thresholds = {-172.f, -2.f, 2.5f, -2.f, -2.f, 1.5f, -2.f, -62.5f, 213.09999084f, -2.f,
-2.f, -2.f, 27.5f, -172.f, -2.f, 8.10000038f, -2.f, -2.f, -2.f};
std::vector<std::string> modes = {"BRANCH_LEQ", "LEAF", "BRANCH_LEQ", "LEAF", "LEAF", "BRANCH_LEQ",
"LEAF", "BRANCH_LEQ", "BRANCH_LEQ", "LEAF", "LEAF", "LEAF",
"BRANCH_LEQ", "BRANCH_LEQ", "LEAF", "BRANCH_LEQ", "LEAF", "LEAF", "LEAF"};
//std::vector<int64_t> classes = {0, 1, 2, 3};
std::vector<int64_t> class_treeids = {0, 1, 0, 1, 1, 1, 1, 2, 2, 2, 2};
std::vector<int64_t> class_nodeids = {1, 3, 4, 1, 4, 5, 6, 2, 4, 5, 6};
std::vector<int64_t> class_classids = {0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1};
std::vector<float> class_weights = {-1.f, 4.f, -1.f, 2.f, -1.f, +1.f, -2.f, 1.f, -1.f, 2.f, -3.f};
std::vector<int64_t> classes = {0, 1};
std::vector<float> X = {1.f, 0.0f, 0.4f, 3.0f, 44.0f, -3.f, 12.0f, 12.9f, -312.f, 23.0f, 11.3f, -222.f,
23.0f, 11.3f, -222.f, 23.0f, 3311.3f, -222.f, 23.0f, 11.3f, -222.f, 43.0f, 413.3f,
-114.f};
std::vector<int64_t> results = {1, 1, 0, 0, 0, 1, 0, 0};
std::vector<float> probs = {};
std::vector<float> log_probs = {};
std::vector<float> scores{
0.2689414f, 0.73105859f,
0.04742586f, 0.88079702f,
0.73105859f, 0.26894140f,
0.73105859f, 0.26894140f,
0.73105859f, 0.26894140f,
0.26894140f, 0.73105859f,
0.73105859f, 0.26894140f,
0.5f, 0.04742586f};
//define the context of the operator call
const int N = 8;
test.AddAttribute("nodes_truenodeids", lefts);
test.AddAttribute("nodes_falsenodeids", rights);
test.AddAttribute("nodes_treeids", treeids);
test.AddAttribute("nodes_nodeids", nodeids);
test.AddAttribute("nodes_featureids", featureids);
test.AddAttribute("nodes_values", thresholds);
test.AddAttribute("nodes_modes", modes);
test.AddAttribute("class_treeids", class_treeids);
test.AddAttribute("class_nodeids", class_nodeids);
test.AddAttribute("class_ids", class_classids);
test.AddAttribute("class_weights", class_weights);
test.AddAttribute("classlabels_int64s", classes);
test.AddAttribute("post_transform", "LOGISTIC");
test.AddInput<float>("X", {N, 3}, X);
test.AddOutput<int64_t>("Y", {N}, results);
test.AddOutput<float>("Z", {N, 2}, scores);
test.Run();
}
} // namespace test
} // namespace onnxruntime