actually copy the bytes from pytorch tensor into the array

Author: carlosuc3m

src/main/java/io/bioimage/modelrunner/pytorch/javacpp/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 org.bytedeco.pytorch.Tensor;
@@ -81,8 +80,7 @@ private static void buildFromTensorByte(Tensor tensor, String memoryName) throws
 			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);
-        ByteBuffer buff = shma.getDataBufferNoHeader();
-        buff = tensor.asByteBuffer();
+        shma.getDataBufferNoHeader().put(tensor.asByteBuffer());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -93,8 +91,7 @@ private static void buildFromTensorInt(Tensor 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 UnsignedByteType(), false, true);
-        ByteBuffer buff = shma.getDataBufferNoHeader();
-        buff = tensor.asByteBuffer();
+        shma.getDataBufferNoHeader().put(tensor.asByteBuffer());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -105,8 +102,7 @@ private static void buildFromTensorFloat(Tensor tensor, String memoryName) throw
 			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 UnsignedByteType(), false, true);
-        ByteBuffer buff = shma.getDataBufferNoHeader();
-        buff = tensor.asByteBuffer();
+        shma.getDataBufferNoHeader().put(tensor.asByteBuffer());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -117,8 +113,7 @@ private static void buildFromTensorDouble(Tensor tensor, String memoryName) thro
 			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 UnsignedByteType(), false, true);
-        ByteBuffer buff = shma.getDataBufferNoHeader();
-        buff = tensor.asByteBuffer();
+        shma.getDataBufferNoHeader().put(tensor.asByteBuffer());
         if (PlatformDetection.isWindows()) shma.close();
     }
 
@@ -129,8 +124,7 @@ private static void buildFromTensorLong(Tensor tensor, String memoryName) throws
 			throw new IllegalArgumentException("Model output tensor with shape " + Arrays.toString(arrayShape) 
 					+ " is too big. Max number of elements per long output tensor supported: " + Integer.MAX_VALUE / 8);
 		SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new UnsignedByteType(), false, true);
-        ByteBuffer buff = shma.getDataBufferNoHeader();
-        buff = tensor.asByteBuffer();
+        shma.getDataBufferNoHeader().put(tensor.asByteBuffer());
         if (PlatformDetection.isWindows()) shma.close();
     }
 }