allow pytorch stream model loading

.github/workflows/docs.yml

@@ -19,7 +19,7 @@ jobs:
         with:
           python-version: '3.x'
       - name: Install CN fonts
-        run: apt-get update && apt-get install fonts-arphic-uming
+        run: sudo apt-get update && sudo apt-get install fonts-arphic-uming
       - name: install Python Dependencies
         run: pip3 install nbconvert==5.6.1 mkdocs mkdocs-exclude mknotebooks==0.4.1 mkdocs-material jupyter Pygments Markdown==3.2.2
       - name: Install IJava kernel

api/src/main/java/ai/djl/ndarray/NDArray.java

@@ -371,6 +371,15 @@ default boolean[] toBooleanArray() {
         return ret;
     }
 
+    /**
+     * Converts this {@code NDArray} to a String array.
+     *
+     * <p>This method is only applicable to the String typed NDArray and not for printing purpose
+     *
+     * @return Array of Strings
+     */
+    String[] toStringArray();
+
     /**
      * Converts this {@code NDArray} to a Number array based on its {@link DataType}.
      *

api/src/main/java/ai/djl/ndarray/NDArrayAdapter.java

@@ -135,6 +135,12 @@ default NDArray stopGradient() {
         throw new UnsupportedOperationException(UNSUPPORTED_MSG);
     }
 
+    /** {@inheritDoc} */
+    @Override
+    default String[] toStringArray() {
+        throw new UnsupportedOperationException(UNSUPPORTED_MSG);
+    }
+
     /** {@inheritDoc} */
     @Override
     default ByteBuffer toByteBuffer() {

dlr/dlr-engine/src/main/java/ai/djl/dlr/engine/DlrEngine.java

@@ -47,6 +47,9 @@ static Engine newInstance() {
     }
 
     private Engine getAlternativeEngine() {
+        if (Boolean.getBoolean("ai.djl.dlr.disable_alternative")) {
+            return null;
+        }
         if (alternativeEngine == null) {
             Engine engine = Engine.getInstance();
             if (engine.getRank() < getRank()) {

mxnet/mxnet-engine/src/main/java/ai/djl/mxnet/engine/MxNDArray.java

@@ -268,11 +268,18 @@ public boolean hasGradient() {
         return hasGradient;
     }
 
+    /** {@inheritDoc} */
     @Override
     public NDArray stopGradient() {
         return manager.invoke("stop_gradient", this, null);
     }
 
+    /** {@inheritDoc} */
+    @Override
+    public String[] toStringArray() {
+        throw new UnsupportedOperationException("String NDArray is not supported!");
+    }
+
     /** {@inheritDoc} */
     @Override
     public ByteBuffer toByteBuffer() {

onnxruntime/onnxruntime-engine/src/main/java/ai/djl/onnxruntime/engine/OrtEngine.java

@@ -57,6 +57,9 @@ public int getRank() {
     }
 
     private Engine getAlternativeEngine() {
+        if (Boolean.getBoolean("ai.djl.onnx.disable_alternative")) {
+            return null;
+        }
         if (alternativeEngine == null) {
             Engine engine = Engine.getInstance();
             if (engine.getRank() < getRank()) {

onnxruntime/onnxruntime-engine/src/main/java/ai/djl/onnxruntime/engine/OrtNDArray.java

@@ -13,12 +13,16 @@
 package ai.djl.onnxruntime.engine;
 
 import ai.djl.Device;
+import ai.djl.engine.EngineException;
 import ai.djl.ndarray.NDArray;
 import ai.djl.ndarray.NDArrayAdapter;
 import ai.djl.ndarray.NDManager;
 import ai.djl.ndarray.types.DataType;
 import ai.djl.ndarray.types.Shape;
 import ai.onnxruntime.OnnxTensor;
+import ai.onnxruntime.OrtException;
+import java.nio.ByteBuffer;
+import java.nio.ByteOrder;
 import java.util.Arrays;
 import java.util.UUID;
 
@@ -117,20 +121,35 @@ public void detach() {
         manager = OrtNDManager.getSystemManager();
     }
 
+    /** {@inheritDoc} */
+    @Override
+    public String[] toStringArray() {
+        try {
+            return (String[]) tensor.getValue();
+        } catch (OrtException e) {
+            throw new EngineException(e);
+        }
+    }
+
+    /** {@inheritDoc} */
+    @Override
+    public ByteBuffer toByteBuffer() {
+        return tensor.getByteBuffer().order(ByteOrder.nativeOrder());
+    }
+
     /** {@inheritDoc} */
     @Override
     public String toString() {
         if (isClosed) {
             return "This array is already closed";
         }
-        return "ND: "
-                + getShape()
-                + ' '
-                + getDevice()
-                + ' '
-                + getDataType()
-                + '\n'
-                + Arrays.toString(toArray());
+        String arrStr;
+        if (getDataType() == DataType.STRING) {
+            arrStr = Arrays.toString(toStringArray());
+        } else {
+            arrStr = Arrays.toString(toArray());
+        }
+        return "ND: " + getShape() + ' ' + getDevice() + ' ' + getDataType() + '\n' + arrStr;
     }
 
     /** {@inheritDoc} */

onnxruntime/onnxruntime-engine/src/main/java/ai/djl/onnxruntime/engine/OrtUtils.java

@@ -98,6 +98,8 @@ public static DataType toDataType(OnnxJavaType javaType) {
                 return DataType.BOOLEAN;
             case UNKNOWN:
                 return DataType.UNKNOWN;
+            case STRING:
+                return DataType.STRING;
             default:
                 throw new UnsupportedOperationException("type is not supported: " + javaType);
         }

onnxruntime/onnxruntime-engine/src/test/java/ai/djl/onnxruntime/engine/OrtTest.java

@@ -73,6 +73,7 @@ public void testOrt() throws TranslateException, ModelException, IOException {
     public void testStringTensor()
             throws MalformedModelException, ModelNotFoundException, IOException,
                     TranslateException {
+        System.setProperty("ai.djl.onnx.disable_alternative", "true");
         Criteria<NDList, NDList> criteria =
                 Criteria.builder()
                         .setTypes(NDList.class, NDList.class)
@@ -82,12 +83,15 @@ public void testStringTensor()
                         .build();
         try (ZooModel<NDList, NDList> model = ModelZoo.loadModel(criteria);
                 Predictor<NDList, NDList> predictor = model.newPredictor()) {
-            OrtNDManager manager = (OrtNDManager) OrtNDManager.getSystemManager().newSubManager();
+            OrtNDManager manager = (OrtNDManager) model.getNDManager();
             NDArray stringNd =
                     manager.create(
                             new String[] {" Re: Jack can't hide from keith@cco.", " I like dogs"},
                             new Shape(1, 2));
-            predictor.predict(new NDList(stringNd));
+            NDList result = predictor.predict(new NDList(stringNd));
+            Assert.assertEquals(result.size(), 2);
+            Assert.assertEquals(result.get(0).toLongArray(), new long[] {1});
         }
+        System.clearProperty("ai.djl.onnx.disable_alternative");
     }
 }

paddlepaddle/paddlepaddle-engine/src/main/java/ai/djl/paddlepaddle/engine/PpEngine.java

@@ -57,6 +57,9 @@ public int getRank() {
     }
 
     Engine getAlternativeEngine() {
+        if (Boolean.getBoolean("ai.djl.paddlepaddle.disable_alternative")) {
+            return null;
+        }
         if (alternativeEngine == null) {
             Engine engine = Engine.getInstance();
             if (engine.getRank() < getRank()) {

pytorch/pytorch-engine/src/main/java/ai/djl/pytorch/engine/PtModel.java

@@ -26,6 +26,7 @@
 import ai.djl.util.PairList;
 import java.io.FileNotFoundException;
 import java.io.IOException;
+import java.io.InputStream;
 import java.nio.file.Files;
 import java.nio.file.Path;
 import java.util.ArrayList;
@@ -101,6 +102,18 @@ public void load(Path modelPath, String prefix, Map<String, ?> options)
         }
     }
 
+    /**
+     * Load PyTorch model from {@link InputStream}.
+     *
+     * <p>Currently, only TorchScript file are supported
+     *
+     * @param modelStream the stream of the model file
+     * @throws IOException model loading error
+     */
+    public void load(InputStream modelStream) throws IOException {
+        block = JniUtils.loadModule((PtNDManager) manager, modelStream, manager.getDevice(), false);
+    }
+
     private Path findModelFile(String prefix) {
         if (Files.isRegularFile(modelDir)) {
             Path file = modelDir;

pytorch/pytorch-engine/src/main/java/ai/djl/pytorch/engine/PtNDArray.java

@@ -211,6 +211,12 @@ public ByteBuffer toByteBuffer() {
         return JniUtils.getByteBuffer(this);
     }
 
+    /** {@inheritDoc} */
+    @Override
+    public String[] toStringArray() {
+        throw new UnsupportedOperationException("String NDArray is not supported!");
+    }
+
     /** {@inheritDoc} */
     @Override
     public void set(Buffer data) {

pytorch/pytorch-engine/src/test/java/ai/djl/pytorch/integration/PtModelTest.java

@@ -0,0 +1,43 @@
+/*
+ * Copyright 2021 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
+ * with the License. A copy of the License is located at
+ *
+ * http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES
+ * OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
+ * and limitations under the License.
+ */
+package ai.djl.pytorch.integration;
+
+import ai.djl.Model;
+import ai.djl.inference.Predictor;
+import ai.djl.ndarray.NDArray;
+import ai.djl.ndarray.NDList;
+import ai.djl.ndarray.types.Shape;
+import ai.djl.pytorch.engine.PtModel;
+import ai.djl.translate.NoopTranslator;
+import ai.djl.translate.TranslateException;
+import java.io.IOException;
+import java.net.URL;
+import org.testng.Assert;
+import org.testng.annotations.Test;
+
+public class PtModelTest {
+
+    @Test
+    public void testLoadFromStream() throws IOException, TranslateException {
+        URL url =
+                new URL("https://djl-ai.s3.amazonaws.com/resources/test-models/traced_resnet18.pt");
+        try (PtModel model = (PtModel) Model.newInstance("test model")) {
+            model.load(url.openStream());
+            try (Predictor<NDList, NDList> predictor = model.newPredictor(new NoopTranslator())) {
+                NDArray array = model.getNDManager().ones(new Shape(1, 3, 224, 224));
+                NDArray result = predictor.predict(new NDList(array)).singletonOrThrow();
+                Assert.assertEquals(result.getShape(), new Shape(1, 1000));
+            }
+        }
+    }
+}

tensorflow/tensorflow-engine/src/main/java/ai/djl/tensorflow/engine/TfNDArray.java

@@ -257,6 +257,13 @@ public boolean[] toBooleanArray() {
         return result;
     }
 
+    @Override
+    public String[] toStringArray() {
+        // TODO: Parse String Array from bytes[]
+        throw new UnsupportedOperationException(
+                "TensorFlow does not supporting printing String NDArray");
+    }
+
     /** {@inheritDoc} */
     @Override
     public ByteBuffer toByteBuffer() {

tflite/tflite-engine/src/main/java/ai/djl/tflite/engine/TfLiteEngine.java

@@ -54,6 +54,9 @@ public int getRank() {
     }
 
     private Engine getAlternativeEngine() {
+        if (Boolean.getBoolean("ai.djl.tflite.disable_alternative")) {
+            return null;
+        }
         if (alternativeEngine == null) {
             Engine engine = Engine.getInstance();
             if (engine.getRank() < getRank()) {
@@ -67,7 +70,7 @@ private Engine getAlternativeEngine() {
     /** {@inheritDoc} */
     @Override
     public String getVersion() {
-        return "1.4.0";
+        return "2.4.1";
     }
 
     /** {@inheritDoc} */