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// Copyright Vespa.ai. 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 com.yahoo.config.subscription.ConfigGetter;
import com.yahoo.filedistribution.fileacquirer.FileAcquirer;
import com.yahoo.filedistribution.fileacquirer.MockFileAcquirer;
import com.yahoo.tensor.Tensor;
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.io.File;
import java.util.HashMap;
import java.util.Map;
import static org.junit.Assume.assumeTrue;
public class OnnxEvaluationHandlerTest {
private static HandlerTester handler;
private static final String CONFIG_DIR = "src/test/resources/config/onnx/";
@BeforeClass
static public void setUp() {
assumeTrue(OnnxRuntime.isRuntimeAvailable());
handler = new HandlerTester(createModels());
}
@Test
public void testListModels() {
String url = "http://localhost/model-evaluation/v1";
String expected = "{\"one_layer\":\"http://localhost/model-evaluation/v1/one_layer\"," +
"\"add_mul\":\"http://localhost/model-evaluation/v1/add_mul\"," +
"\"no_model\":\"http://localhost/model-evaluation/v1/no_model\"}";
handler.checkResponse(url, 200, HandlerTester.matchJson(expected));
}
@Test
public void testModelInfo() {
String url = "http://localhost/model-evaluation/v1/add_mul";
var check = HandlerTester.matchJson(
"{'model':'add_mul','functions':[",
" {'function':'output1',",
" 'info':'http://localhost/model-evaluation/v1/add_mul/output1',",
" 'eval':'http://localhost/model-evaluation/v1/add_mul/output1/eval',",
" 'arguments':[",
" {'name':'input1','type':'tensor<float>(d0[1])'},",
" {'name':'input2','type':'tensor<float>(d0[1])'}",
" ]},",
" {'function':'output2',",
" 'info':'http://localhost/model-evaluation/v1/add_mul/output2',",
" 'eval':'http://localhost/model-evaluation/v1/add_mul/output2/eval',",
" 'arguments':[",
" {'name':'input1','type':'tensor<float>(d0[1])'},",
" {'name':'input2','type':'tensor<float>(d0[1])'}",
" ]}]}");
handler.checkResponse(url, 200, check);
}
@Test
public void testEvaluationWithoutSpecifyingOutput() {
String url = "http://localhost/model-evaluation/v1/add_mul/eval";
String expected = "{\"error\":\"More than one function is available in model 'add_mul', but no name is given. Available functions: output1, output2\"}";
handler.assertResponse(url, 404, expected);
}
@Test
public void testEvaluationWithoutBindings() {
String url = "http://localhost/model-evaluation/v1/add_mul/output1/eval";
String expected = "{\"error\":\"Argument 'input1' must be bound to a value of type tensor<float>(d0[1])\"}";
handler.assertResponse(url, 400, expected);
}
@Test
public void testEvaluationOutput1() {
Map<String, String> properties = new HashMap<>();
properties.put("input1", "tensor<float>(d0[1]):[2]");
properties.put("input2", "tensor<float>(d0[1]):[3]");
properties.put("format.tensors", "long");
String url = "http://localhost/model-evaluation/v1/add_mul/output1/eval";
String expected = "{\"type\":\"tensor<float>(d0[1])\",\"cells\":[{\"address\":{\"d0\":\"0\"},\"value\":6.0}]}"; // output1 is a mul
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testEvaluationOutput2() {
Map<String, String> properties = new HashMap<>();
properties.put("input1", "tensor<float>(d0[1]):[2]");
properties.put("input2", "tensor<float>(d0[1]):[3]");
properties.put("format.tensors", "long");
String url = "http://localhost/model-evaluation/v1/add_mul/output2/eval";
String expected = "{\"type\":\"tensor<float>(d0[1])\",\"cells\":[{\"address\":{\"d0\":\"0\"},\"value\":5.0}]}"; // output2 is an add
handler.assertResponse(url, properties, 200, expected);
}
@Test
public void testBatchDimensionModelInfo() {
String url = "http://localhost/model-evaluation/v1/one_layer";
String expected = "{\"model\":\"one_layer\",\"functions\":[" +
"{\"function\":\"output\"," +
"\"info\":\"http://localhost/model-evaluation/v1/one_layer/output\"," +
"\"eval\":\"http://localhost/model-evaluation/v1/one_layer/output/eval\"," +
"\"arguments\":[" +
"{\"name\":\"input\",\"type\":\"tensor<float>(d0[],d1[3])\"}" +
"]}]}";
handler.assertResponse(url, 200, expected);
}
@Test
public void testBatchDimensionEvaluation() {
Map<String, String> properties = new HashMap<>();
properties.put("input", "tensor<float>(d0[],d1[3]):{{d0:0,d1:0}:0.1,{d0:0,d1:1}:0.2,{d0:0,d1:2}:0.3,{d0:1,d1:0}:0.4,{d0:1,d1:1}:0.5,{d0:1,d1:2}:0.6}");
properties.put("format.tensors", "long");
String url = "http://localhost/model-evaluation/v1/one_layer/eval"; // output not specified
Tensor expected = Tensor.from("tensor<float>(d0[2],d1[1]):[0.6393113,0.67574286]");
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"));
Map<String, File> fileMap = new HashMap<>();
for (OnnxModelsConfig.Model onnxModel : onnxModelsConfig.model()) {
fileMap.put(onnxModel.fileref().value(), new File(CONFIG_DIR + onnxModel.fileref().value()));
}
FileAcquirer fileAcquirer = MockFileAcquirer.returnFiles(fileMap);
return new ModelsEvaluator(config, constantsConfig, expressionsConfig, onnxModelsConfig, fileAcquirer);
}
private static String fileConfigId(String filename) {
return "file:" + CONFIG_DIR + filename;
}
}
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