add prints everywhere

Author: carlosuc3m

src/main/java/io/bioimage/modelrunner/pytorch/javacpp/PytorchJavaCPPInterface.java

@@ -253,8 +253,10 @@ protected void runFromShmas(List<String> inputs, List<String> outputs) throws IO
         IValue output = model.forward(inputsVector);
         TensorVector outputTensorVector = null;
         if (output.isTensorList()) {
+        	System.out.println("SSECRET_KEY :  1 ");
         	outputTensorVector = output.toTensorVector();
         } else {
+        	System.out.println("SSECRET_KEY :  2 ");
         	outputTensorVector = new TensorVector();
         	outputTensorVector.put(output.toTensor());
         }
@@ -263,6 +265,7 @@ protected void runFromShmas(List<String> inputs, List<String> outputs) throws IO
 		int c = 0;
 		for (String ee : outputs) {
 			Map<String, Object> decoded = Types.decode(ee);
+			System.out.println("ENTERED: " + ee);
 			ShmBuilder.build(outputTensorVector.get(c ++), (String) decoded.get(MEM_NAME_KEY));
 		}
 		outputTensorVector.close();

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

@@ -68,14 +68,19 @@ public static void build(Tensor tensor, String memoryName) throws IllegalArgumen
     {
         if (tensor.dtype().isScalarType(org.bytedeco.pytorch.global.torch.ScalarType.Byte)
     			|| tensor.dtype().isScalarType(org.bytedeco.pytorch.global.torch.ScalarType.Char)) {
+        	System.out.println("SSECRET_KEY :  BYTE ");
         	buildFromTensorByte(tensor, memoryName);
     	} else if (tensor.dtype().isScalarType(org.bytedeco.pytorch.global.torch.ScalarType.Int)) {
+        	System.out.println("SSECRET_KEY :  INT ");
         	buildFromTensorInt(tensor, memoryName);
     	} else if (tensor.dtype().isScalarType(org.bytedeco.pytorch.global.torch.ScalarType.Float)) {
+        	System.out.println("SSECRET_KEY :  FLOAT ");
         	buildFromTensorFloat(tensor, memoryName);
     	} else if (tensor.dtype().isScalarType(org.bytedeco.pytorch.global.torch.ScalarType.Double)) {
+        	System.out.println("SSECRET_KEY :  SOUBKE ");
         	buildFromTensorDouble(tensor, memoryName);
     	} else if (tensor.dtype().isScalarType(org.bytedeco.pytorch.global.torch.ScalarType.Long)) {
+        	System.out.println("SSECRET_KEY :  LONG ");
         	buildFromTensorLong(tensor, memoryName);
     	} else {
             throw new IllegalArgumentException("Unsupported tensor type: " + tensor.scalar_type());