avoid transposition

Author: carlosuc3m

src/main/java/io/bioimage/modelrunner/pytorch/PytorchInterface.java

@@ -390,7 +390,7 @@ private <T extends RealType<T> & NativeType<T>> List<String> encodeInputs(List<T
 		List<String> encodedInputTensors = new ArrayList<String>();
 		Gson gson = new Gson();
 		for (Tensor<?> tt : inputTensors) {
-			SharedMemoryArray shma = SharedMemoryArray.createSHMAFromRAI(tt.getData(), false, true);
+			SharedMemoryArray shma = SharedMemoryArray.createSHMAFromRAI(tt.getData(), true, true);
 			shmaInputList.add(shma);
 			HashMap<String, Object> map = new HashMap<String, Object>();
 			map.put(NAME_KEY, tt.getName());
@@ -415,7 +415,7 @@ List<String> encodeOutputs(List<Tensor<T>> outputTensors) {
 			if (!tt.isEmpty()) {
 				map.put(SHAPE_KEY, tt.getShape());
 				map.put(DTYPE_KEY, CommonUtils.getDataTypeFromRAI(tt.getData()));
-				SharedMemoryArray shma = SharedMemoryArray.createSHMAFromRAI(tt.getData(), false, true);
+				SharedMemoryArray shma = SharedMemoryArray.createSHMAFromRAI(tt.getData(), true, true);
 				shmaOutputList.add(shma);
 				map.put(MEM_NAME_KEY, shma.getName());
 			} else if (PlatformDetection.isWindows()){

src/main/java/io/bioimage/modelrunner/pytorch/shm/ShmBuilder.java

@@ -88,7 +88,7 @@ private static void buildFromTensorUByte(NDArray tensor, String memoryName) thro
 		if (CommonUtils.int32Overflows(arrayShape, 1))
 			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);
+        SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new UnsignedByteType(), true, true);
         shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -100,7 +100,7 @@ private static void buildFromTensorInt(NDArray tensor, String memoryName) throws
 			throw new IllegalArgumentException("Model output tensor with shape " + Arrays.toString(arrayShape) 
 					+ " 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);
+        SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new IntType(), true, true);
         shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -112,7 +112,7 @@ private static void buildFromTensorFloat(NDArray tensor, String memoryName) thro
 			throw new IllegalArgumentException("Model output tensor with shape " + Arrays.toString(arrayShape) 
 					+ " 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);
+        SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new FloatType(), true, true);
         shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -124,7 +124,7 @@ private static void buildFromTensorDouble(NDArray tensor, String memoryName) thr
 			throw new IllegalArgumentException("Model output tensor with shape " + Arrays.toString(arrayShape) 
 					+ " 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);
+        SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new DoubleType(), true, true);
         shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -137,7 +137,7 @@ private static void buildFromTensorLong(NDArray tensor, String memoryName) throw
 					+ " is too big. Max number of elements per long output tensor supported: " + Integer.MAX_VALUE / 8);
 
 
-        SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new LongType(), false, true);
+        SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new LongType(), true, true);
         shma.getDataBufferNoHeader().put(tensor.toByteArray());
         if (PlatformDetection.isWindows()) shma.close();
     }