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// Copyright 2018 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.rankingexpression.importer.tensorflow;
import ai.vespa.rankingexpression.importer.ImportedModel;
import ai.vespa.rankingexpression.importer.IntermediateGraph;
import ai.vespa.rankingexpression.importer.ModelImporter;
import ai.vespa.rankingexpression.importer.onnx.OnnxImporter;
import com.yahoo.collections.Pair;
import com.yahoo.io.IOUtils;
import com.yahoo.system.ProcessExecuter;
import org.tensorflow.SavedModelBundle;
import java.io.File;
import java.io.IOException;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.logging.Logger;
/**
* Converts a saved TensorFlow model into a ranking expression and set of constants.
*
* @author bratseth
* @author lesters
*/
public class TensorFlowImporter extends ModelImporter {
private static final Logger log = Logger.getLogger(TensorFlowImporter.class.getName());
private final static int defaultOnnxOpset = 8;
private final OnnxImporter onnxImporter = new OnnxImporter();
@Override
public boolean canImport(String modelPath) {
File modelDir = new File(modelPath);
if ( ! modelDir.isDirectory()) return false;
// No other model types are stored in protobuf files thus far
for (File file : modelDir.listFiles()) {
if (file.toString().endsWith(".pbtxt")) return true;
if (file.toString().endsWith(".pb")) return true;
}
return false;
}
/**
* Imports a saved TensorFlow model from a directory.
* The model should be saved as a .pbtxt or .pb file.
*
* @param modelName the name of the model to import, consisting of characters in [A-Za-z0-9_]
* @param modelDir the directory containing the TensorFlow model files to import
*/
@Override
public ImportedModel importModel(String modelName, String modelDir) {
// Temporary (for testing): if path contains "tf_2_onnx", convert to ONNX then import that model.
if (modelDir.contains("tf_2_onnx")) {
return convertToOnnxAndImport(modelName, modelDir);
}
try (SavedModelBundle model = SavedModelBundle.load(modelDir, "serve")) {
return importModel(modelName, modelDir, model);
}
catch (IllegalArgumentException e) {
throw new IllegalArgumentException("Could not import TensorFlow model from directory '" + modelDir + "'", e);
}
}
/** Imports a TensorFlow model */
public ImportedModel importModel(String modelName, String modelDir, SavedModelBundle model) {
try {
IntermediateGraph graph = GraphImporter.importGraph(modelName, model);
return convertIntermediateGraphToModel(graph, modelDir);
}
catch (IOException e) {
throw new IllegalArgumentException("Could not import TensorFlow model '" + model + "'", e);
}
}
private ImportedModel convertToOnnxAndImport(String modelName, String modelDir) {
Path tempDir = null;
try {
log.info("Converting TensorFlow model '" + modelDir + "' to ONNX...");
tempDir = Files.createTempDirectory("tf2onnx");
String convertedPath = tempDir.toString() + File.separatorChar + "converted.onnx";
Pair<Integer, String> res = convertToOnnx(modelDir, convertedPath, defaultOnnxOpset);
if (res.getFirst() != 0) {
throw new IllegalArgumentException("Conversion from TensorFlow to ONNX failed for '" + modelDir + "'. " +
"Reason: " + res.getSecond());
}
return onnxImporter.importModel(modelName, convertedPath);
} catch (IOException e) {
throw new IllegalArgumentException("Conversion from TensorFlow to ONNX failed for '" + modelDir + "'");
} finally {
if (tempDir != null) {
IOUtils.recursiveDeleteDir(tempDir.toFile());
}
}
}
private Pair<Integer, String> convertToOnnx(String savedModel, String output, int opset) throws IOException {
ProcessExecuter executer = new ProcessExecuter();
String job = "python3 -m tf2onnx.convert --saved-model " + savedModel + " --output " + output + " --opset " + opset;
return executer.exec(job);
}
}
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