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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.models.handler;
import ai.vespa.modelintegration.evaluator.OnnxRuntime;
import ai.vespa.models.evaluation.ModelsEvaluator;
import ai.vespa.models.evaluation.RankProfilesConfigImporterWithMockedConstants;
import com.yahoo.config.subscription.ConfigGetter;
import com.yahoo.filedistribution.fileacquirer.MockFileAcquirer;
import com.yahoo.path.Path;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import com.yahoo.vespa.config.search.RankProfilesConfig;
import com.yahoo.vespa.config.search.core.OnnxModelsConfig;
import com.yahoo.vespa.config.search.core.RankingConstantsConfig;
import com.yahoo.vespa.config.search.core.RankingExpressionsConfig;
import org.junit.BeforeClass;
import org.junit.Test;
import java.util.HashMap;
import java.util.Map;
import static org.junit.Assume.assumeTrue;
public class ModelsEvaluationHandlerTest {
private static final String MODELS_DIR = "src/test/resources/config/models/";
private static HandlerTester handler;
@BeforeClass
static public void setUp() {
handler = new HandlerTester(createModels());
}
@Test
public void testUnknownAPI() {
handler.assertResponse("http://localhost/wrong-api-binding", 404);
}
@Test
public void testUnknownVersion() {
handler.assertResponse("http://localhost/model-evaluation/v0", 404);
}
@Test
public void testNonExistingModel() {
handler.assertResponse("http://localhost/model-evaluation/v1/non-existing-model", 404);
}
@Test
public void testListModels() {
String url = "http://localhost/model-evaluation/v1";
String expected = "{" +
"\"lightgbm_regression\":\"http://localhost/model-evaluation/v1/lightgbm_regression\"," +
"\"mnist_saved\":\"http://localhost/model-evaluation/v1/mnist_saved\"," +
"\"mnist_softmax\":\"http://localhost/model-evaluation/v1/mnist_softmax\"," +
"\"mnist_softmax_saved\":\"http://localhost/model-evaluation/v1/mnist_softmax_saved\"," +
"\"vespa_model\":\"http://localhost/model-evaluation/v1/vespa_model\"," +
"\"xgboost_2_2\":\"http://localhost/model-evaluation/v1/xgboost_2_2\"," +
"\"xgboost_non_standalone\":\"http://localhost/model-evaluation/v1/xgboost_non_standalone\"" +
"}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testListModelsWithDifferentHost() {
String url = "http://localhost/model-evaluation/v1";
String expected = "{" +
"\"lightgbm_regression\":\"http://localhost:8088/model-evaluation/v1/lightgbm_regression\"," +
"\"mnist_saved\":\"http://localhost:8088/model-evaluation/v1/mnist_saved\"," +
"\"mnist_softmax\":\"http://localhost:8088/model-evaluation/v1/mnist_softmax\"," +
"\"mnist_softmax_saved\":\"http://localhost:8088/model-evaluation/v1/mnist_softmax_saved\"," +
"\"vespa_model\":\"http://localhost:8088/model-evaluation/v1/vespa_model\"," +
"\"xgboost_2_2\":\"http://localhost:8088/model-evaluation/v1/xgboost_2_2\"," +
"\"xgboost_non_standalone\":\"http://localhost:8088/model-evaluation/v1/xgboost_non_standalone\"" +
"}";
handler.assertResponse(url, 200, expected, Map.of("Host", "localhost:8088"));
}
@Test
public void testXgBoostEvaluationWithoutBindings() {
String url = "http://localhost/model-evaluation/v1/xgboost_2_2/eval"; // only has a single function
String expected = "{\"type\":\"tensor()\",\"values\":[-4.376589999999999]}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testXgBoostEvaluationWithBindings() {
Map<String, String> properties = new HashMap<>();
properties.put("f29", "-1.0");
properties.put("f56", "0.2");
properties.put("f60", "0.3");
properties.put("f109", "0.4");
properties.put("non-existing-binding", "-1");
String url = "http://localhost/model-evaluation/v1/xgboost_2_2/eval";
String expected = "{\"type\":\"tensor()\",\"values\":[-7.936679999999999]}";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testXgBoostEvaluationWithMissingValue() {
Map<String, String> properties = new HashMap<>();
properties.put("missing-value", "-1.0");
properties.put("f56", "0.2");
properties.put("f60", "0.3");
properties.put("f109", "0.4");
properties.put("non-existing-binding", "-1");
properties.put("format.tensors", "long");
String url = "http://localhost/model-evaluation/v1/xgboost_2_2/eval";
String expected = "{\"type\":\"tensor()\",\"cells\":[{\"address\":{},\"value\":-7.936679999999999}]}";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testLightGBMEvaluationWithoutBindings() {
String url = "http://localhost/model-evaluation/v1/lightgbm_regression/eval";
String expected = "{\"type\":\"tensor()\",\"values\":[1.9130086820218188]}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testLightGBMEvaluationWithBindings() {
Map<String, String> properties = new HashMap<>();
properties.put("numerical_1", "0.1");
properties.put("numerical_2", "0.2");
properties.put("categorical_1", "a");
properties.put("categorical_2", "i");
properties.put("non-existing-binding", "-1");
String url = "http://localhost/model-evaluation/v1/lightgbm_regression/eval";
String expected = "{\"type\":\"tensor()\",\"values\":[2.054697758469921]}";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testLightGBMEvaluationWithMissingValue() {
Map<String, String> properties = new HashMap<>();
properties.put("missing-value", "-1.0");
properties.put("numerical_2", "0.5");
properties.put("categorical_1", "b");
properties.put("categorical_2", "j");
properties.put("non-existing-binding", "-1");
String url = "http://localhost/model-evaluation/v1/lightgbm_regression/eval";
String expected = "{\"type\":\"tensor()\",\"values\":[2.0745534018208094]}";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testMnistSoftmaxDetails() {
String url = "http://localhost:8080/model-evaluation/v1/mnist_softmax";
String expected = "{\"model\":\"mnist_softmax\",\"functions\":[{\"function\":\"default.add\",\"info\":\"http://localhost:8080/model-evaluation/v1/mnist_softmax/default.add\",\"eval\":\"http://localhost:8080/model-evaluation/v1/mnist_softmax/default.add/eval\",\"arguments\":[{\"name\":\"Placeholder\",\"type\":\"tensor(d0[],d1[784])\"}]}]}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testMnistSoftmaxTypeDetails() {
String url = "http://localhost/model-evaluation/v1/mnist_softmax/default.add/";
String expected = "{\"model\":\"mnist_softmax\",\"function\":\"default.add\",\"info\":\"http://localhost/model-evaluation/v1/mnist_softmax/default.add\",\"eval\":\"http://localhost/model-evaluation/v1/mnist_softmax/default.add/eval\",\"arguments\":[{\"name\":\"Placeholder\",\"type\":\"tensor(d0[],d1[784])\"}]}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testMnistSoftmaxEvaluateDefaultFunctionWithoutBindings() {
String url = "http://localhost/model-evaluation/v1/mnist_softmax/eval";
String expected = "{\"error\":\"Argument 'Placeholder' must be bound to a value of type tensor(d0[],d1[784])\"}";
handler.assertResponse(url, 400, expected);
}
@Test
public void testMnistSoftmaxEvaluateSpecificFunctionWithoutBindings() {
String url = "http://localhost/model-evaluation/v1/mnist_softmax/default.add/eval";
String expected = "{\"error\":\"Argument 'Placeholder' must be bound to a value of type tensor(d0[],d1[784])\"}";
handler.assertResponse(url, 400, expected);
}
@Test
public void testMnistSoftmaxEvaluateDefaultFunctionWithBindings() {
Map<String, String> properties = new HashMap<>();
properties.put("Placeholder", inputTensor());
String url = "http://localhost/model-evaluation/v1/mnist_softmax/eval";
String expected = "{\"type\":\"tensor(d0[],d1[10])\",\"values\":[[-0.3546536862850189,0.3759574592113495,0.06054411828517914,-0.251544713973999,0.017951013520359993,1.2899067401885986,-0.10389615595340729,0.6367976665496826,-1.4136744737625122,-0.2573896050453186]]}";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testMnistSoftmaxEvaluateSpecificFunctionWithBindings() {
Map<String, String> properties = new HashMap<>();
properties.put("Placeholder", inputTensor());
String url = "http://localhost/model-evaluation/v1/mnist_softmax/default.add/eval";
String expected = "{\"type\":\"tensor(d0[],d1[10])\",\"values\":[[-0.3546536862850189,0.3759574592113495,0.06054411828517914,-0.251544713973999,0.017951013520359993,1.2899067401885986,-0.10389615595340729,0.6367976665496826,-1.4136744737625122,-0.2573896050453186]]}";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testMnistSoftmaxEvaluateSpecificFunctionWithShortOutput() {
Map<String, String> properties = new HashMap<>();
properties.put("Placeholder", inputTensorShortForm());
properties.put("format.tensors", "short");
String url = "http://localhost/model-evaluation/v1/mnist_softmax/default.add/eval";
String expected =
"""
{
"type":"tensor(d0[],d1[10])",
"values":[[-0.3546536862850189,0.3759574592113495,0.06054411828517914,-0.251544713973999,0.017951013520359993,1.2899067401885986,-0.10389615595340729,0.6367976665496826,-1.4136744737625122,-0.2573896050453186]]
}
""";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testMnistSoftmaxEvaluateSpecificFunctionWithLongOutput() {
Map<String, String> properties = new HashMap<>();
properties.put("Placeholder", inputTensorShortForm());
properties.put("format.tensors", "long");
String url = "http://localhost/model-evaluation/v1/mnist_softmax/default.add/eval";
String expected =
"""
{
"type":"tensor(d0[],d1[10])",
"cells":[
{"address":{"d0":"0","d1":"0"},"value":-0.3546536862850189},
{"address":{"d0":"0","d1":"1"},"value":0.3759574592113495},
{"address":{"d0":"0","d1":"2"},"value":0.06054411828517914},
{"address":{"d0":"0","d1":"3"},"value":-0.251544713973999},
{"address":{"d0":"0","d1":"4"},"value":0.017951013520359993},
{"address":{"d0":"0","d1":"5"},"value":1.2899067401885986},
{"address":{"d0":"0","d1":"6"},"value":-0.10389615595340729},
{"address":{"d0":"0","d1":"7"},"value":0.6367976665496826},
{"address":{"d0":"0","d1":"8"},"value":-1.4136744737625122},
{"address":{"d0":"0","d1":"9"},"value":-0.2573896050453186}
]
}
""";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testMnistSoftmaxEvaluateSpecificFunctionWithShortDirectOutput() {
Map<String, String> properties = new HashMap<>();
properties.put("Placeholder", inputTensorShortForm());
properties.put("format.tensors", "short-value");
String url = "http://localhost/model-evaluation/v1/mnist_softmax/default.add/eval";
String expected =
"""
[[-0.3546536862850189,0.3759574592113495,0.06054411828517914,-0.251544713973999,0.017951013520359993,1.2899067401885986,-0.10389615595340729,0.6367976665496826,-1.4136744737625122,-0.2573896050453186]]
""";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testMnistSoftmaxEvaluateSpecificFunctionWithLongDirectOutput() {
Map<String, String> properties = new HashMap<>();
properties.put("Placeholder", inputTensorShortForm());
properties.put("format.tensors", "long-value");
String url = "http://localhost/model-evaluation/v1/mnist_softmax/default.add/eval";
String expected =
"""
[
{"address":{"d0":"0","d1":"0"},"value":-0.3546536862850189},
{"address":{"d0":"0","d1":"1"},"value":0.3759574592113495},
{"address":{"d0":"0","d1":"2"},"value":0.06054411828517914},
{"address":{"d0":"0","d1":"3"},"value":-0.251544713973999},
{"address":{"d0":"0","d1":"4"},"value":0.017951013520359993},
{"address":{"d0":"0","d1":"5"},"value":1.2899067401885986},
{"address":{"d0":"0","d1":"6"},"value":-0.10389615595340729},
{"address":{"d0":"0","d1":"7"},"value":0.6367976665496826},
{"address":{"d0":"0","d1":"8"},"value":-1.4136744737625122},
{"address":{"d0":"0","d1":"9"},"value":-0.2573896050453186}
]
""";
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testMnistSavedDetails() {
String url = "http://localhost:8080/model-evaluation/v1/mnist_saved";
String expected = "{\"model\":\"mnist_saved\",\"functions\":[{\"function\":\"serving_default.y\",\"info\":\"http://localhost:8080/model-evaluation/v1/mnist_saved/serving_default.y\",\"eval\":\"http://localhost:8080/model-evaluation/v1/mnist_saved/serving_default.y/eval\",\"arguments\":[{\"name\":\"input\",\"type\":\"tensor(d0[],d1[784])\"}]}]}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testMnistSavedTypeDetails() {
String url = "http://localhost/model-evaluation/v1/mnist_saved/serving_default.y/";
String expected = "{\"model\":\"mnist_saved\",\"function\":\"serving_default.y\",\"info\":\"http://localhost/model-evaluation/v1/mnist_saved/serving_default.y\",\"eval\":\"http://localhost/model-evaluation/v1/mnist_saved/serving_default.y/eval\",\"arguments\":[{\"name\":\"input\",\"type\":\"tensor(d0[],d1[784])\"}]}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testMnistSavedEvaluateDefaultFunctionShouldFail() {
String url = "http://localhost/model-evaluation/v1/mnist_saved/eval";
String expected = "{\"error\":\"More than one function is available in model 'mnist_saved', but no name is given. Available functions: imported_ml_function_mnist_saved_dnn_hidden1_add, serving_default.y\"}";
handler.assertResponse(url, 404, expected);
}
@Test
public void testVespaModelShortOutput() {
Map<String, String> properties = new HashMap<>();
properties.put("format.tensors", "short");
String url = "http://localhost/model-evaluation/v1/vespa_model/";
handler.assertResponse(url + "test_mapped/eval", properties, 200,
"{\"type\":\"tensor(d0{})\",\"cells\":{\"a\":1.0,\"b\":2.0}}");
handler.assertResponse(url + "test_indexed/eval", properties, 200,
"{\"type\":\"tensor(d0[2],d1[3])\",\"values\":[[1.0,2.0,3.0],[4.0,5.0,6.0]]}");
handler.assertResponse(url + "test_mixed/eval", properties, 200,
"{\"type\":\"tensor(x{},y[3])\",\"blocks\":{\"a\":[1.0,2.0,3.0],\"b\":[4.0,5.0,6.0]}}");
handler.assertResponse(url + "test_mixed_2/eval", properties, 200,
"{\"type\":\"tensor(a[2],b[2],c{},d[2])\",\"blocks\":{\"a\":[[[1.0,2.0],[3.0,4.0]],[[5.0,6.0],[7.0,8.0]]],\"b\":[[[1.0,2.0],[3.0,4.0]],[[5.0,6.0],[7.0,8.0]]]}}");
}
@Test
public void testVespaModelLiteralOutput() {
Map<String, String> properties = new HashMap<>();
properties.put("format.tensors", "string");
String url = "http://localhost/model-evaluation/v1/vespa_model/";
handler.assertStringResponse(url + "test_mapped/eval", properties, 200,
"tensor(d0{}):{a:1.0, b:2.0}", Map.of());
handler.assertStringResponse(url + "test_indexed/eval", properties, 200,
"tensor(d0[2],d1[3]):[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]", Map.of());
handler.assertStringResponse(url + "test_mixed/eval", properties, 200,
"tensor(x{},y[3]):{a:[1.0, 2.0, 3.0], b:[4.0, 5.0, 6.0]}", Map.of());
handler.assertStringResponse(url + "test_mixed_2/eval", properties, 200,
"tensor(a[2],b[2],c{},d[2]):{a:[[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]], b:[[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]]}", Map.of());
}
@Test
public void testMnistSavedEvaluateSpecificFunction() {
assumeTrue(OnnxRuntime.isRuntimeAvailable());
Map<String, String> properties = new HashMap<>();
properties.put("input", inputTensor());
properties.put("format.tensors", "long");
String url = "http://localhost/model-evaluation/v1/mnist_saved/serving_default.y/eval";
Tensor expected = Tensor.from("tensor(d0[1],d1[10]):{"+
"{d0:0,d1:0}:-0.6319251673007533,"+
"{d0:0,d1:1}:-0.0007577770600619843,"+
"{d0:0,d1:2}:-0.010707969042025622,"+
"{d0:0,d1:3}:-0.6344759233540788,"+
"{d0:0,d1:4}:-0.17529455385847528,"+
"{d0:0,d1:5}:0.7490809723192187,"+
"{d0:0,d1:6}:-0.022790284182901716,"+
"{d0:0,d1:7}:0.26799240657608936,"+
"{d0:0,d1:8}:-0.3152438845465862,"+
"{d0:0,d1:9}:0.05949304847735276}");
handler.assertResponse(url, properties, 200, expected);
}
@SuppressWarnings("deprecation")
static private ModelsEvaluator createModels() {
RankProfilesConfig config = ConfigGetter.getConfig(RankProfilesConfig.class, fileConfigId("rank-profiles.cfg"));
RankingConstantsConfig constantsConfig = ConfigGetter.getConfig(RankingConstantsConfig.class, fileConfigId("ranking-constants.cfg"));
RankingExpressionsConfig expressionsConfig = ConfigGetter.getConfig(RankingExpressionsConfig.class, fileConfigId("ranking-expressions.cfg"));
OnnxModelsConfig onnxModelsConfig = ConfigGetter.getConfig(OnnxModelsConfig.class, fileConfigId("onnx-models.cfg"));
return new ModelsEvaluator(new RankProfilesConfigImporterWithMockedConstants(Path.fromString(MODELS_DIR), MockFileAcquirer.returnFile(null)),
config, constantsConfig, expressionsConfig, onnxModelsConfig);
}
private static String fileConfigId(String filename) {
return "file:" + MODELS_DIR + filename;
}
private String inputTensor() {
Tensor.Builder b = Tensor.Builder.of(TensorType.fromSpec("tensor(d0[],d1[784])"));
for (int i = 0; i < 784; i++)
b.cell(0.0, 0, i);
return b.build().toString();
}
private String inputTensorShortForm() {
StringBuilder sb = new StringBuilder();
sb.append("[[");
for (int i = 0; i < 784; i++) {
sb.append("0.0");
if (i < 783) {
sb.append(",");
}
}
sb.append("]]");
return sb.toString();
}
}
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