improve small errors on shm communication

Author: carlosuc3m

src/main/java/io/bioimage/modelrunner/tensorflow/v1/shm/ShmBuilder.java

@@ -93,7 +93,7 @@ private static void buildFromTensorUByte(Tensor<UInt8> tensor, String memoryName
 			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.getDataBuffer();
+        ByteBuffer buff = shma.getDataBufferNoHeader();
         tensor.writeTo(buff);
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -106,7 +106,7 @@ private static void buildFromTensorInt(Tensor<Integer> tensor, String memoryName
 					+ " 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);
-        ByteBuffer buff = shma.getDataBuffer();
+        ByteBuffer buff = shma.getDataBufferNoHeader();
         tensor.writeTo(buff);
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -119,7 +119,7 @@ private static void buildFromTensorFloat(Tensor<Float> tensor, String memoryName
 					+ " 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);
-        ByteBuffer buff = shma.getDataBuffer();
+        ByteBuffer buff = shma.getDataBufferNoHeader();
         tensor.writeTo(buff);
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -132,7 +132,7 @@ private static void buildFromTensorDouble(Tensor<Double> tensor, String memoryNa
 					+ " 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);
-        ByteBuffer buff = shma.getDataBuffer();
+        ByteBuffer buff = shma.getDataBufferNoHeader();
         tensor.writeTo(buff);
         if (PlatformDetection.isWindows()) shma.close();
     }
@@ -146,7 +146,7 @@ private static void buildFromTensorLong(Tensor<Long> tensor, String memoryName)
 
 
         SharedMemoryArray shma = SharedMemoryArray.readOrCreate(memoryName, arrayShape, new LongType(), false, true);
-        ByteBuffer buff = shma.getDataBuffer();
+        ByteBuffer buff = shma.getDataBufferNoHeader();
         tensor.writeTo(buff);
         if (PlatformDetection.isWindows()) shma.close();
     }

src/main/java/io/bioimage/modelrunner/tensorflow/v1/shm/TensorBuilder.java

@@ -105,8 +105,6 @@ private static Tensor<Integer> buildInt(SharedMemoryArray tensor)
 			throw new IllegalArgumentException("Shared memory arrays must be saved in numpy format.");
 		ByteBuffer buff = tensor.getDataBufferNoHeader();
 		IntBuffer intBuff = buff.asIntBuffer();
-		int[] intArray = new int[intBuff.capacity()];
-		intBuff.get(intArray);
 		Tensor<Integer> ndarray = Tensor.create(ogShape, intBuff);
 		return ndarray;
 	}
@@ -122,8 +120,6 @@ private static Tensor<Long> buildLong(SharedMemoryArray tensor)
 			throw new IllegalArgumentException("Shared memory arrays must be saved in numpy format.");
 		ByteBuffer buff = tensor.getDataBufferNoHeader();
 		LongBuffer longBuff = buff.asLongBuffer();
-		long[] longArray = new long[longBuff.capacity()];
-		longBuff.get(longArray);
 		Tensor<Long> ndarray = Tensor.create(ogShape, longBuff);
 		return ndarray;
 	}
@@ -139,8 +135,6 @@ private static Tensor<Float> buildFloat(SharedMemoryArray tensor)
 			throw new IllegalArgumentException("Shared memory arrays must be saved in numpy format.");
 		ByteBuffer buff = tensor.getDataBufferNoHeader();
 		FloatBuffer floatBuff = buff.asFloatBuffer();
-		float[] floatArray = new float[floatBuff.capacity()];
-		floatBuff.get(floatArray);
 		Tensor<Float> ndarray = Tensor.create(ogShape, floatBuff);
 		return ndarray;
 	}
@@ -156,8 +150,6 @@ private static Tensor<Double> buildDouble(SharedMemoryArray tensor)
 			throw new IllegalArgumentException("Shared memory arrays must be saved in numpy format.");
 		ByteBuffer buff = tensor.getDataBufferNoHeader();
 		DoubleBuffer doubleBuff = buff.asDoubleBuffer();
-		double[] doubleArray = new double[doubleBuff.capacity()];
-		doubleBuff.get(doubleArray);
 		Tensor<Double> ndarray = Tensor.create(ogShape, doubleBuff);
 		return ndarray;
 	}