latest tests

src/main/java/tfhello.java

@@ -8,6 +8,7 @@ import org.tensorflow.Operation;
 
 import org.tensorflow.framework.ConfigProto;
 import org.tensorflow.framework.GPUOptions;
+import org.tensorflow.framework.CallableOptions;
 
 import static jcuda.driver.JCudaDriver.cuCtxCreate;
 import static jcuda.driver.JCudaDriver.cuCtxSynchronize;
@@ -34,6 +35,10 @@ import jcuda.driver.CUdevice;
 import jcuda.driver.JCudaDriver;
 import jcuda.nvrtc.JNvrtc;
 
+import jcuda.runtime.cudaPointerAttributes;
+import jcuda.runtime.JCuda;
+import jcuda.runtime.cudaError;
+
 import java.nio.ByteBuffer;
 
 import java.lang.reflect.Field;
@@ -108,14 +113,14 @@ public class tfhello{
 		CUdeviceptr ptr1 = new CUdeviceptr();
 		cuMemAlloc(ptr1,cuSize);
 		System.out.println("CUdeviceptr ptr1 after cuMemAlloc: "+ptr1);
-		
+				
 		// we will get pointer address as 'long' from JNI
 		long ptr1_addr = getPointerAddress(ptr1);
 		System.out.println("Extracted ptr1 address as (long): "+String.format("0x%08x", ptr1_addr));
 		
 		// notice, there's no cuMemAlloc
 		CUdeviceptr ptr2 = longToCUdeviceptr(ptr1_addr);
-		
+				
 		System.out.println("CUdeviceptr ptr2 created from ptr1's long address using java.reflection: "+ptr2);
 		
 		// test: copy a test array px_in to CUDA
@@ -143,10 +148,12 @@ public class tfhello{
 		System.out.println("Test 3 start\n  - Print TF version");
 		System.out.println(TensorFlow.version());
 		System.out.println("Test 3 end\n");
-		
+				
 		System.out.println("Test 4 start\n  - Test simple custom JNI function added to TF");
 		System.out.println(TensorFlow.elphelVersion());
 		System.out.println("Test 4 end\n");
+				
+		//callableOpts.newBuilder().putFeedDevices(key, value);
 		
 	    try (Graph g = new Graph()) {
 	        final String value = "Hello from " + TensorFlow.version();
@@ -171,18 +178,64 @@ public class tfhello{
 	        System.out.println("Is CUDA tensor? "+String.valueOf(t.elphel_isCUDATensor()));
 	        System.out.println(t.elphelTestCUDAPointer());
 	        
+	        long handle1;
+	        //session.makeCallable(handle1);
+	        
 	        try (
-	        	Session s = new Session(g, config.toByteArray());
+	        	Session s = new Session(g, config.toByteArray())
+	        	//s.runner().makeCallable("",handle1);
+	        	//s.runner().runCallable(handle1);
 		        // Generally, there may be multiple output tensors,
 		        // all of them must be closed to prevent resource leaks.
-		        Tensor output = s.runner().fetch("array_tensor_out").feed("array_tensor_in", t).run().get(0);
-		    ){
+	        ){
+	        	
+	        	Tensor output = s.runner().fetch("array_tensor_out").feed("array_tensor_in", t).run().get(0);
+	        	
 	        	System.out.println(output.numBytes());
 	        	
 	        	int[] obuf = new int[output.numBytes()/Sizeof.INT];
 	        	output.copyTo(obuf);
 	        	System.out.println(Arrays.toString(obuf));
 	        	
+	        	// natively got GPU device name to insert into options
+	        	// it's the same all the time
+	        	String gpuDeviceName = s.elphelGPUDeviceName();
+	        	
+	    		// that's for RunCallable() if it ever gets implemented
+	    		CallableOptions callableOpts = CallableOptions.newBuilder()
+	    			.addFetch("array_tensor_out:0")
+	    		    .addFeed("array_tensor_in:0")
+	    		    .putFeedDevices("array_tensor_in:0", gpuDeviceName)
+	    		    .build();
+	    		
+	    		System.out.println(callableOpts);
+	        	
+	    		// GPU allocation:
+	    		Tensor t3 = Tensor.elphelCreateGPUTensor(new long[]{256},DataType.INT32);
+	    		//System.out.println(t2.nativeRef);
+	    	
+	    		long t3_gpuptr = t3.elphel_GetGPUTensorPointer();
+	    		System.out.println(String.format("0x%08x", t3_gpuptr));
+	    		
+	    		CUdeviceptr ptr3 = longToCUdeviceptr(t3_gpuptr);
+	    		
+	    		cudaPointerAttributes attrs = new cudaPointerAttributes();
+	    		int res = JCuda.cudaPointerGetAttributes(attrs, ptr3);
+	    		if (res==cudaError.cudaErrorInvalidValue) {
+	    			System.out.println("Invalid pointer value");
+	    		}
+	    		if (attrs.device==-1){
+	    			System.out.println("Not a CUDA device");
+	    		}
+	    		
+	    		System.out.println("cuda pointer attributes?! "+res);
+	    		System.out.println(attrs.toString());
+	    		
+	    		cuMemcpyHtoD(ptr3, Pointer.to(px_in), cuSize);
+	    		cuMemcpyDtoH(Pointer.to(px_out), ptr3, cuSize);
+	    		System.out.println(Arrays.toString(px_out));
+	    		// check if it a GPU pointer
+	    		
 		    }
 	        
 	        /*