Revert "Lesters/java probe onnx model 2"

2 files changed, 6 insertions, 184 deletions

diff --git a/config-model/src/main/java/com/yahoo/vespa/model/ml/OnnxModelInfo.java b/config-model/src/main/java/com/yahoo/vespa/model/ml/OnnxModelInfo.java
index 2742dc59fcd..88139de7888 100644
--- a/config-model/src/main/java/com/yahoo/vespa/model/ml/OnnxModelInfo.java
+++ b/config-model/src/main/java/com/yahoo/vespa/model/ml/OnnxModelInfo.java
@@ -36,15 +36,13 @@ import java.util.stream.Collectors;
  */
 public class OnnxModelInfo {
 
-    private final ApplicationPackage app;
     private final String modelPath;
     private final String defaultOutput;
     private final Map<String, OnnxTypeInfo> inputs;
     private final Map<String, OnnxTypeInfo> outputs;
     private final Map<String, TensorType> vespaTypes = new HashMap<>();
 
-    private OnnxModelInfo(ApplicationPackage app, String path, Map<String, OnnxTypeInfo> inputs, Map<String, OnnxTypeInfo> outputs, String defaultOutput) {
-        this.app = app;
+    private OnnxModelInfo(String path, Map<String, OnnxTypeInfo> inputs, Map<String, OnnxTypeInfo> outputs, String defaultOutput) {
         this.modelPath = path;
         this.inputs = Collections.unmodifiableMap(inputs);
         this.outputs = Collections.unmodifiableMap(outputs);
@@ -81,15 +79,7 @@ public class OnnxModelInfo {
             Set<Long> unboundSizes = new HashSet<>();
             Map<String, Long> symbolicSizes = new HashMap<>();
             resolveUnknownDimensionSizes(inputTypes, symbolicSizes, unboundSizes);
-
-            TensorType type = TensorType.empty;
-            if (inputTypes.size() > 0 && onnxTypeInfo.needModelProbe(symbolicSizes)) {
-                type = OnnxModelProbe.probeModel(app, Path.fromString(modelPath), onnxName, inputTypes);
-            }
-            if (type.equals(TensorType.empty)) {
-                type = onnxTypeInfo.toVespaTensorType(symbolicSizes, unboundSizes);
-            }
-            return type;
+            return onnxTypeInfo.toVespaTensorType(symbolicSizes, unboundSizes);
         }
         return vespaTypes.computeIfAbsent(onnxName, v -> onnxTypeInfo.toVespaTensorType());
     }
@@ -160,8 +150,7 @@ public class OnnxModelInfo {
             Onnx.ModelProto model = Onnx.ModelProto.parseFrom(inputStream);
             String json = onnxModelToJson(model, path);
             storeGeneratedInfo(json, path, app);
-            return jsonToModelInfo(json, app);
-
+            return jsonToModelInfo(json);
         } catch (IOException e) {
             throw new IllegalArgumentException("Unable to parse ONNX model", e);
         }
@@ -170,7 +159,7 @@ public class OnnxModelInfo {
     static private OnnxModelInfo loadFromGeneratedInfo(Path path, ApplicationPackage app) {
         try {
             String json = readGeneratedInfo(path, app);
-            return jsonToModelInfo(json, app);
+            return jsonToModelInfo(json);
         } catch (IOException e) {
             throw new IllegalArgumentException("Unable to parse ONNX model", e);
         }
@@ -213,7 +202,7 @@ public class OnnxModelInfo {
         return out.toString();
     }
 
-    static public OnnxModelInfo jsonToModelInfo(String json, ApplicationPackage app) throws IOException {
+    static public OnnxModelInfo jsonToModelInfo(String json) throws IOException {
         ObjectMapper m = new ObjectMapper();
         JsonNode root = m.readTree(json);
         Map<String, OnnxTypeInfo> inputs = new HashMap<>();
@@ -233,7 +222,7 @@ public class OnnxModelInfo {
         if (root.get("outputs").has(0)) {
             defaultOutput = root.get("outputs").get(0).get("name").textValue();
         }
-        return new OnnxModelInfo(app, path, inputs, outputs, defaultOutput);
+        return new OnnxModelInfo(path, inputs, outputs, defaultOutput);
     }
 
     static private void onnxTypeToJson(JsonGenerator g, Onnx.ValueInfoProto valueInfo) throws IOException {
@@ -364,21 +353,6 @@ public class OnnxModelInfo {
             return builder.build();
         }
 
-        boolean needModelProbe(Map<String, Long> symbolicSizes) {
-            for (OnnxDimensionInfo onnxDimension : dimensions) {
-                if (onnxDimension.hasSymbolicName()) {
-                    if (symbolicSizes == null)
-                        return true;
-                    if ( ! symbolicSizes.containsKey(onnxDimension.getSymbolicName())) {
-                        return true;
-                    }
-                } else if (onnxDimension.getSize() == 0) {
-                    return true;
-                }
-            }
-            return false;
-        }
-
         @Override
         public String toString() {
             return "(" + valueType.id() + ")" +
diff --git a/config-model/src/main/java/com/yahoo/vespa/model/ml/OnnxModelProbe.java b/config-model/src/main/java/com/yahoo/vespa/model/ml/OnnxModelProbe.java
deleted file mode 100644
index 2e2ebdeb98f..00000000000
--- a/config-model/src/main/java/com/yahoo/vespa/model/ml/OnnxModelProbe.java
+++ /dev/null
@@ -1,152 +0,0 @@
-package com.yahoo.vespa.model.ml;
-
-import com.fasterxml.jackson.core.JsonEncoding;
-import com.fasterxml.jackson.core.JsonFactory;
-import com.fasterxml.jackson.core.JsonGenerator;
-import com.fasterxml.jackson.databind.JsonNode;
-import com.fasterxml.jackson.databind.ObjectMapper;
-import com.yahoo.config.application.api.ApplicationFile;
-import com.yahoo.config.application.api.ApplicationPackage;
-import com.yahoo.io.IOUtils;
-import com.yahoo.path.Path;
-import com.yahoo.tensor.TensorType;
-
-import java.io.BufferedReader;
-import java.io.ByteArrayOutputStream;
-import java.io.IOException;
-import java.io.InputStream;
-import java.io.OutputStream;
-import java.nio.charset.StandardCharsets;
-import java.util.Map;
-
-/**
- * Defers to 'vespa-analyze-onnx-model' to determine the output type given
- * a set of inputs. For situations with symbolic dimension sizes that can't
- * easily be determined.
- *
- * @author lesters
- */
-public class OnnxModelProbe {
-
-    private static final String binary = "vespa-analyze-onnx-model";
-
-    static TensorType probeModel(ApplicationPackage app, Path modelPath, String outputName, Map<String, TensorType> inputTypes) {
-        TensorType outputType = TensorType.empty;
-        String contextKey = createContextKey(outputName, inputTypes);
-
-        try {
-            // Check if output type has already been probed
-            outputType = readProbedOutputType(app, modelPath, contextKey);
-
-            // Otherwise, run vespa-analyze-onnx-model if the model is available
-            if (outputType.equals(TensorType.empty) && app.getFile(modelPath).exists()) {
-                String jsonInput = createJsonInput(app.getFileReference(modelPath).getAbsolutePath(), inputTypes);
-                String jsonOutput = callVespaAnalyzeOnnxModel(jsonInput);
-                outputType = outputTypeFromJson(jsonOutput, outputName);
-                if ( ! outputType.equals(TensorType.empty)) {
-                    writeProbedOutputType(app, modelPath, contextKey, outputType);
-                }
-            }
-
-        } catch (IllegalArgumentException | IOException | InterruptedException e) {
-            e.printStackTrace(System.err);
-        }
-
-        return outputType;
-    }
-
-    private static String createContextKey(String onnxName, Map<String, TensorType> inputTypes) {
-        StringBuilder key = new StringBuilder().append(onnxName).append(":");
-        inputTypes.entrySet().stream().sorted(Map.Entry.comparingByKey())
-                .forEachOrdered(e -> key.append(e.getKey()).append(":").append(e.getValue()).append(","));
-        return key.substring(0, key.length()-1);
-    }
-
-    private static Path probedOutputTypesPath(Path path) {
-        String fileName = OnnxModelInfo.asValidIdentifier(path.getRelative()) + ".probed_output_types";
-        return ApplicationPackage.MODELS_GENERATED_REPLICATED_DIR.append(fileName);
-    }
-
-    static void writeProbedOutputType(ApplicationPackage app, Path modelPath, String output,
-                                      Map<String, TensorType> inputTypes, TensorType type) throws IOException {
-        writeProbedOutputType(app, modelPath, createContextKey(output, inputTypes), type);
-    }
-
-    private static void writeProbedOutputType(ApplicationPackage app, Path modelPath,
-                                              String contextKey, TensorType type) throws IOException {
-        String path = app.getFileReference(probedOutputTypesPath(modelPath)).getAbsolutePath();
-        IOUtils.writeFile(path, contextKey + "\t" + type + "\n", true);
-    }
-
-    private static TensorType readProbedOutputType(ApplicationPackage app, Path modelPath,
-                                                   String contextKey) throws IOException {
-        ApplicationFile file = app.getFile(probedOutputTypesPath(modelPath));
-        if ( ! file.exists()) {
-            return TensorType.empty;
-        }
-        try (BufferedReader reader = new BufferedReader(file.createReader())) {
-            String line;
-            while (null != (line = reader.readLine())) {
-                String[] parts = line.split("\t");
-                String key = parts[0];
-                if (key.equals(contextKey)) {
-                    return TensorType.fromSpec(parts[1]);
-                }
-            }
-        }
-        return TensorType.empty;
-    }
-
-    private static TensorType outputTypeFromJson(String json, String outputName) throws IOException {
-        ObjectMapper m = new ObjectMapper();
-        JsonNode root = m.readTree(json);
-        if ( ! root.isObject() || ! root.has("outputs")) {
-            return TensorType.empty;
-        }
-        JsonNode outputs = root.get("outputs");
-        if ( ! outputs.has(outputName)) {
-            return TensorType.empty;
-        }
-        return TensorType.fromSpec(outputs.get(outputName).asText());
-    }
-
-    private static String createJsonInput(String modelPath, Map<String, TensorType> inputTypes) throws IOException {
-        ByteArrayOutputStream out = new ByteArrayOutputStream();
-        JsonGenerator g = new JsonFactory().createGenerator(out, JsonEncoding.UTF8);
-        g.writeStartObject();
-        g.writeStringField("model", modelPath);
-        g.writeObjectFieldStart("inputs");
-        for (Map.Entry<String, TensorType> input : inputTypes.entrySet()) {
-            g.writeStringField(input.getKey(), input.getValue().toString());
-        }
-        g.writeEndObject();
-        g.writeEndObject();
-        g.close();
-        return out.toString();
-    }
-
-    private static String callVespaAnalyzeOnnxModel(String jsonInput) throws IOException, InterruptedException {
-        ProcessBuilder processBuilder = new ProcessBuilder(binary, "--probe-types");
-        StringBuilder output = new StringBuilder();
-        Process process = processBuilder.start();
-
-        // Write json array to process stdin
-        OutputStream os = process.getOutputStream();
-        os.write(jsonInput.getBytes(StandardCharsets.UTF_8));
-        os.close();
-
-        // Read output from stdout
-        InputStream inputStream = process.getInputStream();
-        while (true) {
-            int b = inputStream.read();
-            if (b == -1) break;
-            output.append((char)b);
-        }
-        int returnCode = process.waitFor();
-        if (returnCode != 0) {
-            throw new IllegalArgumentException("Error from '" + binary + "'. Return code: " + returnCode + ". Output:\n" + output);
-        }
-        return output.toString();
-    }
-
-}