- numpy import fix for CUDA (#64)

- skip tagLocation for empty arrays Signed-off-by: raver119 <raver119@gmail.com>
deeplearning4j · Jul 20, 2019 · c499dc9 · c499dc9
1 parent c9e867b
commit c499dc9
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Showing 4 changed files with 22 additions and 31 deletions.
diff --git a/...j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/allocator/impl/AtomicAllocator.java b/...j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/allocator/impl/AtomicAllocator.java
@@ -529,7 +529,7 @@ public AllocationPoint allocateMemory(DataBuffer buffer, AllocationShape require
      * @param objectId
      * @return
      */
-    protected AllocationPoint getAllocationPoint(Long objectId) {
+    protected AllocationPoint getAllocationPoint(@NonNull Long objectId) {
         return allocationsMap.get(objectId);
     }
 

diff --git a/...-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/concurrency/CudaAffinityManager.java b/...-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/concurrency/CudaAffinityManager.java
@@ -339,6 +339,10 @@ public DataBuffer replicateToDevice(Integer deviceId, DataBuffer buffer) {
      */
     @Override
     public void tagLocation(INDArray array, Location location) {
+        // we can't tag empty arrays.
+        if (array.isEmpty())
+            return;
+
         if (location == Location.HOST)
             AtomicAllocator.getInstance().getAllocationPoint(array).tickHostWrite();
         else if (location == Location.DEVICE)

diff --git a/...kend-impls/nd4j-cuda/src/main/java/org/nd4j/linalg/jcublas/buffer/BaseCudaDataBuffer.java b/...kend-impls/nd4j-cuda/src/main/java/org/nd4j/linalg/jcublas/buffer/BaseCudaDataBuffer.java
@@ -116,6 +116,7 @@ public BaseCudaDataBuffer(Pointer pointer, Indexer indexer, long length) {
 
         //cuda specific bits
         this.allocationPoint = AtomicAllocator.getInstance().allocateMemory(this, new AllocationShape(length, elementSize, dataType()), false);
+        this.trackingPoint = allocationPoint.getObjectId();
 
         Nd4j.getDeallocatorService().pickObject(this);
 
@@ -124,40 +125,19 @@ public BaseCudaDataBuffer(Pointer pointer, Indexer indexer, long length) {
 
         val perfD = PerformanceTracker.getInstance().helperStartTransaction();
 
-        NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(allocationPoint.getHostPointer(), pointer, length * getElementSize(), CudaConstants.cudaMemcpyHostToHost, context.getSpecialStream());
-        NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(allocationPoint.getDevicePointer(), allocationPoint.getHostPointer(), length * getElementSize(), CudaConstants.cudaMemcpyHostToHost, context.getSpecialStream());
+        if (allocationPoint.getHostPointer() != null) {
+            NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(allocationPoint.getHostPointer(), pointer, length * getElementSize(), CudaConstants.cudaMemcpyHostToHost, context.getSpecialStream());
+            NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(allocationPoint.getDevicePointer(), allocationPoint.getHostPointer(), length * getElementSize(), CudaConstants.cudaMemcpyHostToHost, context.getSpecialStream());
+        } else {
+            NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(allocationPoint.getDevicePointer(), pointer, length * getElementSize(), CudaConstants.cudaMemcpyHostToDevice, context.getSpecialStream());
+        }
 
         context.getSpecialStream().synchronize();
 
-        PerformanceTracker.getInstance().helperRegisterTransaction(allocationPoint.getDeviceId(), perfD / 2, allocationPoint.getNumberOfBytes(), MemcpyDirection.HOST_TO_HOST);
-        PerformanceTracker.getInstance().helperRegisterTransaction(allocationPoint.getDeviceId(), perfD / 2, allocationPoint.getNumberOfBytes(), MemcpyDirection.HOST_TO_DEVICE);
-
-        this.pointer = new CudaPointer(allocationPoint.getHostPointer(), length * getElementSize(), 0);
-
-        switch (dataType()) {
-            case INT: {
-                setIndexer(IntIndexer.create(((CudaPointer) this.pointer).asIntPointer()));
-            }
-            break;
-            case FLOAT: {
-                setIndexer(FloatIndexer.create(((CudaPointer) this.pointer).asFloatPointer()));
-            }
-            break;
-            case DOUBLE: {
-                setIndexer(DoubleIndexer.create(((CudaPointer) this.pointer).asDoublePointer()));
-            }
-            break;
-            case HALF: {
-                setIndexer(ShortIndexer.create(((CudaPointer) this.pointer).asShortPointer()));
-            }
-            break;
-            case LONG: {
-                setIndexer(LongIndexer.create(((CudaPointer) this.pointer).asLongPointer()));
-            }
-            break;
-        }
+        if (allocationPoint.getHostPointer() != null)
+            PerformanceTracker.getInstance().helperRegisterTransaction(allocationPoint.getDeviceId(), perfD / 2, allocationPoint.getNumberOfBytes(), MemcpyDirection.HOST_TO_HOST);
 
-        this.trackingPoint = allocationPoint.getObjectId();
+        PerformanceTracker.getInstance().helperRegisterTransaction(allocationPoint.getDeviceId(), perfD / 2, allocationPoint.getNumberOfBytes(), MemcpyDirection.HOST_TO_DEVICE);
 
     }
 

diff --git a/nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/linalg/serde/NumpyFormatTests.java b/nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/linalg/serde/NumpyFormatTests.java
@@ -310,6 +310,13 @@ public void testAbsentNumpyFile_1() throws Exception {
         INDArray act1 = Nd4j.createFromNpyFile(f);
     }
 
+    @Test
+    public void testAbsentNumpyFile_2() throws Exception {
+        val f = new File("c:/develop/batch-x-1.npy");
+        INDArray act1 = Nd4j.createFromNpyFile(f);
+        log.info("Array shape: {}; sum: {};", act1.shape(), act1.sumNumber().doubleValue());
+    }
+
     @Override
     public char ordering() {
         return 'c';