GOOD WORKING INTERFACE

Author: carlosuc3m

Diff for: src/main/java/io/bioimage/modelrunner/pytorch/PytorchInterface.java

@@ -468,48 +468,6 @@ else if (task.status == TaskStatus.CRASHED)
 		model = null;
 	}
 
-	/** TODO remove
-	 * Create the arguments needed to execute Pytorch in another 
-	 * process with the corresponding tensors
-	 * @return the command used to call the separate process
-	 * @throws IOException if the command needed to execute interprocessing is too long
-	 * @throws URISyntaxException if there is any error with the URIs retrieved from the classes
-	 */
-	private List<String> getProcessCommandsWithoutArgs2() throws IOException, URISyntaxException {
-		String javaHome = System.getProperty("java.home");
-        String javaBin = javaHome +  File.separator + "bin" + File.separator + "java";
-
-        String modelrunnerPath = getPathFromClass(DeepLearningEngineInterface.class);
-        String imglib2Path = getPathFromClass(NativeType.class);
-        String gsonPath = getPathFromClass(Gson.class);
-        String jnaPath = getPathFromClass(com.sun.jna.Library.class);
-        String jnaPlatformPath = getPathFromClass(com.sun.jna.platform.FileUtils.class);
-        if (modelrunnerPath == null || (modelrunnerPath.endsWith("DeepLearningEngineInterface.class") 
-        		&& !modelrunnerPath.contains(File.pathSeparator)))
-        	modelrunnerPath = System.getProperty("java.class.path");
-        String classpath =  modelrunnerPath + File.pathSeparator + imglib2Path + File.pathSeparator;
-        classpath =  classpath + gsonPath + File.pathSeparator;
-        classpath =  classpath + jnaPath + File.pathSeparator;
-        classpath =  classpath + jnaPlatformPath + File.pathSeparator;
-        ProtectionDomain protectionDomain = PytorchInterface.class.getProtectionDomain();
-        String codeSource = protectionDomain.getCodeSource().getLocation().getPath();
-        String f_name = URLDecoder.decode(codeSource, StandardCharsets.UTF_8.toString());
-        f_name = new File(f_name).getAbsolutePath();
-        for (File ff : new File(f_name).getParentFile().listFiles()) {
-        	if (ff.getName().startsWith(JAR_FILE_NAME) && !ff.getAbsolutePath().equals(f_name))
-        		continue;
-        	classpath += ff.getAbsolutePath() + File.pathSeparator;
-        }
-        String className = PytorchInterface.class.getName();
-        List<String> command = new LinkedList<String>();
-        command.add(padSpecialJavaBin(javaBin));
-        command.add("-cp");
-        command.add(classpath);
-        command.add(className);
-        command.add(modelSource);
-        return command;
-	}
-	
 	/**
 	 * Create the arguments needed to execute tensorflow 2 in another 
 	 * process with the corresponding tensors

Diff for: src/main/java/io/bioimage/modelrunner/pytorch/shm/ShmBuilder.java

@@ -25,7 +25,6 @@
 import io.bioimage.modelrunner.utils.CommonUtils;
 
 import java.io.IOException;
-import java.nio.ByteBuffer;
 import java.util.Arrays;
 
 import ai.djl.ndarray.NDArray;
@@ -61,7 +60,6 @@ private ShmBuilder()
      */
 	public static void build(NDArray  tensor, String memoryName) throws IllegalArgumentException, IOException
     {
-		System.out.println(tensor.getDataType().asNumpy());
 		switch (tensor.getDataType())
         {
             case UINT8:
@@ -91,7 +89,7 @@ private static void buildFromTensorUByte(NDArray tensor, String memoryName) thro
 			throw new IllegalArgumentException("Model output tensor with shape " + Arrays.toString(arrayShape) 
 					+ " is too big. Max number of elements per ubyte output tensor supported: " + Integer.MAX_VALUE / 1);
         SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new UnsignedByteType(), false, true);
-        shma.setBuffer(ByteBuffer.wrap(tensor.toByteArray()));
+        shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -103,7 +101,7 @@ private static void buildFromTensorInt(NDArray tensor, String memoryName) throws
 					+ " is too big. Max number of elements per int output tensor supported: " + Integer.MAX_VALUE / 4);
 
         SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new IntType(), false, true);
-        shma.setBuffer(ByteBuffer.wrap(tensor.toByteArray()));
+        shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -115,7 +113,7 @@ private static void buildFromTensorFloat(NDArray tensor, String memoryName) thro
 					+ " is too big. Max number of elements per float output tensor supported: " + Integer.MAX_VALUE / 4);
 
         SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new FloatType(), false, true);
-        shma.setBuffer(ByteBuffer.wrap(tensor.toByteArray()));
+        shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -127,7 +125,7 @@ private static void buildFromTensorDouble(NDArray tensor, String memoryName) thr
 					+ " is too big. Max number of elements per double output tensor supported: " + Integer.MAX_VALUE / 8);
 
         SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new DoubleType(), false, true);
-        shma.setBuffer(ByteBuffer.wrap(tensor.toByteArray()));
+        shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -140,7 +138,7 @@ private static void buildFromTensorLong(NDArray tensor, String memoryName) throw
 
 
         SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new LongType(), false, true);
-        shma.setBuffer(ByteBuffer.wrap(tensor.toByteArray()));
+        shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
 }