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Refactor JNI code in C++ into Java code with JavaCPP#18
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -15,7 +15,21 @@ | ||
| package org.tensorflow; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_DeleteOp; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_DeleteTensorHandle; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_OpGetInputLength; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_OpGetOutputLength; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_TensorHandleDataType; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_TensorHandleDim; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_TensorHandleNumDims; | ||
| import static org.tensorflow.internal.c_api.global.tensorflow.TFE_TensorHandleResolve; | ||
| import java.util.concurrent.atomic.AtomicReferenceArray; | ||
| import org.bytedeco.javacpp.PointerScope; | ||
| import org.tensorflow.internal.c_api.TFE_Op; | ||
| import org.tensorflow.internal.c_api.TFE_TensorHandle; | ||
| import org.tensorflow.internal.c_api.TF_Status; | ||
| import org.tensorflow.internal.c_api.TF_Tensor; | ||
| import org.tensorflow.tools.Shape; | ||
| /** | ||
| @@ -31,8 +45,8 @@ class EagerOperation extends AbstractOperation { | ||
| EagerOperation( | ||
| EagerSession session, | ||
| TFE_Op opNativeHandle, | ||
| TFE_TensorHandle[] outputNativeHandles, | ||
| String type, | ||
| String name) { | ||
| this.session = session; | ||
| @@ -68,7 +82,7 @@ public int inputListLength(final String name) { | ||
| } | ||
| @Override | ||
| public TFE_TensorHandle getUnsafeNativeHandle(int outputIndex) { | ||
| return nativeRef.outputHandles[outputIndex]; | ||
| } | ||
| @@ -80,7 +94,7 @@ public Shape shape(int outputIndex) { | ||
| if (tensor != null) { | ||
| return tensor.shape(); | ||
| } | ||
| TFE_TensorHandle outputNativeHandle = getUnsafeNativeHandle(outputIndex); | ||
| long[] shape = new long[numDims(outputNativeHandle)]; | ||
| for (int i = 0; i < shape.length; ++i) { | ||
| shape[i] = dim(outputNativeHandle, i); | ||
| @@ -96,7 +110,7 @@ public DataType<?> dtype(int outputIndex) { | ||
| if (tensor != null) { | ||
| return tensor.dataType(); | ||
| } | ||
| TFE_TensorHandle outputNativeHandle = getUnsafeNativeHandle(outputIndex); | ||
| return DataTypes.fromNativeCode(dataType(outputNativeHandle)); | ||
| } | ||
| @@ -119,7 +133,7 @@ private Tensor<?> resolveTensor(int outputIndex) { | ||
| // Take an optimistic approach, where we attempt to resolve the output tensor without locking. | ||
| // If another thread has resolved it meanwhile, release our copy and reuse the existing one | ||
| // instead. | ||
| TF_Tensor tensorNativeHandle = resolveTensorHandle(getUnsafeNativeHandle(outputIndex)); | ||
| Tensor<?> tensor = Tensor.fromHandle(tensorNativeHandle, session); | ||
| if (!outputTensors.compareAndSet(outputIndex, null, tensor)) { | ||
| tensor.close(); | ||
| @@ -131,43 +145,104 @@ private Tensor<?> resolveTensor(int outputIndex) { | ||
| private static class NativeReference extends EagerSession.NativeReference { | ||
| NativeReference( | ||
| EagerSession session, EagerOperation operation, TFE_Op opHandle, TFE_TensorHandle[] outputHandles) { | ||
| super(session, operation); | ||
| this.opHandle = opHandle; | ||
| this.outputHandles = outputHandles; | ||
| } | ||
| @Override | ||
| void delete() { | ||
| if (opHandle != null && !opHandle.isNull()) { | ||
| for (int i = 0; i < outputHandles.length; ++i) { | ||
| if (outputHandles[i] != null && !outputHandles[i].isNull()) { | ||
| EagerOperation.deleteTensorHandle(outputHandles[i]); | ||
| outputHandles[i] = null; | ||
| } | ||
| } | ||
| EagerOperation.delete(opHandle); | ||
| opHandle = null; | ||
| } | ||
| } | ||
| private TFE_Op opHandle; | ||
| private final TFE_TensorHandle[] outputHandles; | ||
| } | ||
| private static void requireOp(TFE_Op handle) { | ||
| if (handle == null || handle.isNull()) { | ||
| throw new IllegalStateException("Eager session has been closed"); | ||
| } | ||
| } | ||
| private static void requireTensorHandle(TFE_TensorHandle handle) { | ||
| if (handle == null || handle.isNull()) { | ||
| throw new IllegalStateException("Eager session has been closed"); | ||
| } | ||
| } | ||
| private static void delete(TFE_Op handle) { | ||
| if (handle == null || handle.isNull()) return; | ||
| TFE_DeleteOp(handle); | ||
| } | ||
| private static void deleteTensorHandle(TFE_TensorHandle handle) { | ||
| if (handle == null || handle.isNull()) return; | ||
| TFE_DeleteTensorHandle(handle); | ||
| } | ||
| private static TF_Tensor resolveTensorHandle(TFE_TensorHandle handle) { | ||
| requireTensorHandle(handle); | ||
| try (PointerScope scope = new PointerScope()) { | ||
| TF_Status status = TF_Status.newStatus(); | ||
| TF_Tensor tensor = TFE_TensorHandleResolve(handle, status); | ||
| status.throwExceptionIfNotOK(); | ||
| return tensor; | ||
karllessard marked this conversation as resolved.
Uh oh!There was an error while loading. Please reload this page. | ||
| } | ||
| } | ||
| private static int outputListLength(TFE_Op handle, String name) { | ||
| requireOp(handle); | ||
| try (PointerScope scope = new PointerScope()) { | ||
| TF_Status status = TF_Status.newStatus(); | ||
| int length = TFE_OpGetOutputLength(handle, name, status); | ||
| status.throwExceptionIfNotOK(); | ||
| return length; | ||
| } | ||
Collaborator There was a problem hiding this comment. Instead of starting new scopes in all of these methods, could it be simpler and more efficient to just create the status in a try (TF_Statusstatus = TF_Status.newStatus()) { ... }ContributorAuthor There was a problem hiding this comment. Yes, it would be more efficient, but it would also make it more error-prone when we start creating other objects in there that may start doing temporary allocations. Collaborator There was a problem hiding this comment. Yeah... I would still prefer we go with the most efficient approach but it's up to you if you want to make the changes or not, we can merge it like this too. | ||
| } | ||
| private static int inputListLength(TFE_Op handle, String name) { | ||
| requireOp(handle); | ||
| try (PointerScope scope = new PointerScope()) { | ||
| TF_Status status = TF_Status.newStatus(); | ||
| int length = TFE_OpGetInputLength(handle, name, status); | ||
| status.throwExceptionIfNotOK(); | ||
| return length; | ||
| } | ||
| } | ||
| private static int dataType(TFE_TensorHandle handle) { | ||
| requireTensorHandle(handle); | ||
| return TFE_TensorHandleDataType(handle); | ||
| } | ||
| private static int numDims(TFE_TensorHandle handle) { | ||
| requireTensorHandle(handle); | ||
| try (PointerScope scope = new PointerScope()) { | ||
| TF_Status status = TF_Status.newStatus(); | ||
| int numDims = TFE_TensorHandleNumDims(handle, status); | ||
| status.throwExceptionIfNotOK(); | ||
| return numDims; | ||
| } | ||
| } | ||
| private static long dim(TFE_TensorHandle handle, int index) { | ||
| requireTensorHandle(handle); | ||
| try (PointerScope scope = new PointerScope()) { | ||
| TF_Status status = TF_Status.newStatus(); | ||
| long dim = TFE_TensorHandleDim(handle, index, status); | ||
| status.throwExceptionIfNotOK(); | ||
| return dim; | ||
| } | ||
| } | ||
| } | ||
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