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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.modelintegration.evaluator;
import ai.onnxruntime.OnnxTensor;
import ai.onnxruntime.OnnxValue;
import ai.onnxruntime.OrtEnvironment;
import ai.onnxruntime.OrtException;
import ai.onnxruntime.OrtSession;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
/**
* Evaluates an ONNX Model by deferring to ONNX Runtime.
*
* @author lesters
*/
public class OnnxEvaluator {
private final OrtEnvironment environment;
private final OrtSession session;
public OnnxEvaluator(String modelPath) {
this(modelPath, null);
}
public OnnxEvaluator(String modelPath, OnnxEvaluatorOptions options) {
try {
if (options == null) {
options = new OnnxEvaluatorOptions();
}
environment = OrtEnvironment.getEnvironment();
session = environment.createSession(modelPath, options.getOptions());
} catch (OrtException e) {
throw new RuntimeException("ONNX Runtime exception", e);
}
}
public Tensor evaluate(Map<String, Tensor> inputs, String output) {
Map<String, OnnxTensor> onnxInputs = null;
try {
onnxInputs = TensorConverter.toOnnxTensors(inputs, environment, session);
try (OrtSession.Result result = session.run(onnxInputs, Collections.singleton(output))) {
return TensorConverter.toVespaTensor(result.get(0));
}
} catch (OrtException e) {
throw new RuntimeException("ONNX Runtime exception", e);
} finally {
if (onnxInputs != null) {
onnxInputs.values().forEach(OnnxTensor::close);
}
}
}
public Map<String, Tensor> evaluate(Map<String, Tensor> inputs) {
Map<String, OnnxTensor> onnxInputs = null;
try {
onnxInputs = TensorConverter.toOnnxTensors(inputs, environment, session);
Map<String, Tensor> outputs = new HashMap<>();
try (OrtSession.Result result = session.run(onnxInputs)) {
for (Map.Entry<String, OnnxValue> output : result) {
outputs.put(output.getKey(), TensorConverter.toVespaTensor(output.getValue()));
}
return outputs;
}
} catch (OrtException e) {
throw new RuntimeException("ONNX Runtime exception", e);
} finally {
if (onnxInputs != null) {
onnxInputs.values().forEach(OnnxTensor::close);
}
}
}
public Map<String, TensorType> getInputInfo() {
try {
return TensorConverter.toVespaTypes(session.getInputInfo());
} catch (OrtException e) {
throw new RuntimeException("ONNX Runtime exception", e);
}
}
public Map<String, TensorType> getOutputInfo() {
try {
return TensorConverter.toVespaTypes(session.getOutputInfo());
} catch (OrtException e) {
throw new RuntimeException("ONNX Runtime exception", e);
}
}
public static boolean isRuntimeAvailable() {
return isRuntimeAvailable("");
}
public static boolean isRuntimeAvailable(String modelPath) {
try {
new OnnxEvaluator(modelPath);
return true;
} catch (UnsatisfiedLinkError | RuntimeException | NoClassDefFoundError e) {
return false;
}
}
}
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