Examples with ND4JIllegalStateException org.nd4j.linalg.exception.ND4JIllegalStateException used on opensource projects

Example 56 with ND4JIllegalStateException

use of org.nd4j.linalg.exception.ND4JIllegalStateException in project nd4j by deeplearning4j.

the class JCublasNDArray method leverageTo.

@Override
public INDArray leverageTo(String id) {
    if (!isAttached()) {
        // log.info("Skipping detached");
        return this;
    }
    if (!Nd4j.getWorkspaceManager().checkIfWorkspaceExists(id)) {
        // log.info("Skipping non-existent");
        return this;
    }
    MemoryWorkspace current = Nd4j.getMemoryManager().getCurrentWorkspace();
    MemoryWorkspace target = Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(id);
    if (current == target) {
        // log.info("Skipping equals A");
        return this;
    }
    if (this.data.getParentWorkspace() == target) {
        // log.info("Skipping equals B");
        return this;
    }
    Nd4j.getMemoryManager().setCurrentWorkspace(target);
    // log.info("Leveraging...");
    INDArray copy = null;
    if (!this.isView()) {
        // if (1 < 0) {
        Nd4j.getExecutioner().commit();
        DataBuffer buffer = Nd4j.createBuffer(this.lengthLong(), false);
        AllocationPoint pointDst = AtomicAllocator.getInstance().getAllocationPoint(buffer);
        AllocationPoint pointSrc = AtomicAllocator.getInstance().getAllocationPoint(this.data);
        CudaContext context = AtomicAllocator.getInstance().getFlowController().prepareAction(pointDst, pointSrc);
        /*
            if (NativeOpsHolder.getInstance().getDeviceNativeOps().memsetAsync(pointDst.getDevicePointer(), 0, 1, 0, context.getOldStream()) == 0)
                throw new ND4JIllegalStateException("memsetAsync 1 failed");

            context.syncOldStream();

            if (NativeOpsHolder.getInstance().getDeviceNativeOps().memsetAsync(pointSrc.getDevicePointer(), 0, 1, 0, context.getOldStream()) == 0)
                throw new ND4JIllegalStateException("memsetAsync 2 failed");

            context.syncOldStream();
*/
        if (pointSrc.isActualOnDeviceSide()) {
            if (NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(pointDst.getDevicePointer(), pointSrc.getDevicePointer(), this.lengthLong() * Nd4j.sizeOfDataType(buffer.dataType()), CudaConstants.cudaMemcpyDeviceToDevice, context.getOldStream()) == 0)
                throw new ND4JIllegalStateException("memcpyAsync failed");
        } else {
            if (NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(pointDst.getDevicePointer(), pointSrc.getHostPointer(), this.lengthLong() * Nd4j.sizeOfDataType(buffer.dataType()), CudaConstants.cudaMemcpyHostToDevice, context.getOldStream()) == 0)
                throw new ND4JIllegalStateException("memcpyAsync failed");
        }
        context.syncOldStream();
        copy = Nd4j.createArrayFromShapeBuffer(buffer, this.shapeInfoDataBuffer());
        // tag buffer as valid on device side
        pointDst.tickHostRead();
        pointDst.tickDeviceWrite();
        AtomicAllocator.getInstance().getFlowController().registerAction(context, pointDst, pointSrc);
    } else {
        copy = this.dup(this.ordering());
        Nd4j.getExecutioner().commit();
    }
    Nd4j.getMemoryManager().setCurrentWorkspace(current);
    return copy;
}

Example 57 with ND4JIllegalStateException

use of org.nd4j.linalg.exception.ND4JIllegalStateException in project nd4j by deeplearning4j.

the class JCublasNDArray method migrate.

/**
 * This method pulls this INDArray into current Workspace.
 *
 * PLEASE NOTE: If there's no current Workspace - INDArray returned as is
 *
 * @return
 */
@Override
public INDArray migrate() {
    MemoryWorkspace current = Nd4j.getMemoryManager().getCurrentWorkspace();
    if (current == null)
        return this;
    INDArray copy = null;
    if (!this.isView()) {
        Nd4j.getExecutioner().commit();
        DataBuffer buffer = Nd4j.createBuffer(this.lengthLong(), false);
        AllocationPoint pointDst = AtomicAllocator.getInstance().getAllocationPoint(buffer);
        AllocationPoint pointSrc = AtomicAllocator.getInstance().getAllocationPoint(this.data);
        // CudaContext context = (CudaContext) AtomicAllocator.getInstance().getDeviceContext().getContext();
        CudaContext context = AtomicAllocator.getInstance().getFlowController().prepareAction(pointDst, pointSrc);
        if (pointSrc.isActualOnDeviceSide()) {
            if (NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(pointDst.getDevicePointer(), pointSrc.getDevicePointer(), this.lengthLong() * Nd4j.sizeOfDataType(buffer.dataType()), CudaConstants.cudaMemcpyDeviceToDevice, context.getOldStream()) == 0)
                throw new ND4JIllegalStateException("memcpyAsync failed");
        } else {
            if (NativeOpsHolder.getInstance().getDeviceNativeOps().memcpyAsync(pointDst.getDevicePointer(), pointSrc.getHostPointer(), this.lengthLong() * Nd4j.sizeOfDataType(buffer.dataType()), CudaConstants.cudaMemcpyHostToDevice, context.getOldStream()) == 0)
                throw new ND4JIllegalStateException("memcpyAsync failed");
        }
        context.syncOldStream();
        if (pointDst.getDeviceId() != Nd4j.getMemoryManager().getCurrentWorkspace().getDeviceId()) {
            // log.info("Swapping [{}] -> [{}]", pointDst.getDeviceId(), Nd4j.getMemoryManager().getCurrentWorkspace().getDeviceId());
            pointDst.setDeviceId(Nd4j.getMemoryManager().getCurrentWorkspace().getDeviceId());
        }
        copy = Nd4j.createArrayFromShapeBuffer(buffer, this.shapeInfoDataBuffer());
        // tag buffer as valid on device side
        pointDst.tickHostRead();
        pointDst.tickDeviceWrite();
        AtomicAllocator.getInstance().getFlowController().registerAction(context, pointDst, pointSrc);
    } else {
        copy = this.dup(this.ordering());
    }
    return copy;
}

Example 58 with ND4JIllegalStateException

use of org.nd4j.linalg.exception.ND4JIllegalStateException in project nd4j by deeplearning4j.

the class CudaGridExecutioner method buildZ.

protected void buildZ(Accumulation op, int... dimension) {
    Arrays.sort(dimension);
    for (int i = 0; i < dimension.length; i++) {
        if (dimension[i] < 0)
            dimension[i] += op.x().rank();
    }
    // do op along all dimensions
    if (dimension.length == op.x().rank())
        dimension = new int[] { Integer.MAX_VALUE };
    int[] retShape = Shape.wholeArrayDimension(dimension) ? new int[] { 1, 1 } : ArrayUtil.removeIndex(op.x().shape(), dimension);
    // ensure vector is proper shape
    if (retShape.length == 1) {
        if (dimension[0] == 0)
            retShape = new int[] { 1, retShape[0] };
        else
            retShape = new int[] { retShape[0], 1 };
    } else if (retShape.length == 0) {
        retShape = new int[] { 1, 1 };
    }
    /*
        if(op.x().isVector() && op.x().length() == ArrayUtil.prod(retShape))
            return op.noOp();
        */
    INDArray ret = null;
    if (op.z() == null || op.z() == op.x()) {
        if (op.isComplexAccumulation()) {
            int xT = op.x().tensorssAlongDimension(dimension);
            int yT = op.y().tensorssAlongDimension(dimension);
            ret = Nd4j.create(xT, yT);
        } else {
            if (Math.abs(op.zeroDouble()) < Nd4j.EPS_THRESHOLD) {
                ret = Nd4j.zeros(retShape);
            } else {
                ret = Nd4j.valueArrayOf(retShape, op.zeroDouble());
            }
        }
        op.setZ(ret);
    } else {
        // compare length
        if (op.z().lengthLong() != ArrayUtil.prodLong(retShape))
            throw new ND4JIllegalStateException("Shape of target array for reduction [" + Arrays.toString(op.z().shape()) + "] doesn't match expected [" + Arrays.toString(retShape) + "]");
        if (op.x().data().dataType() == DataBuffer.Type.DOUBLE) {
            op.z().assign(op.zeroDouble());
        } else if (op.x().data().dataType() == DataBuffer.Type.FLOAT) {
            op.z().assign(op.zeroFloat());
        } else if (op.x().data().dataType() == DataBuffer.Type.HALF) {
            op.z().assign(op.zeroHalf());
        }
        ret = op.z();
    }
}

Example 59 with ND4JIllegalStateException

use of org.nd4j.linalg.exception.ND4JIllegalStateException in project nd4j by deeplearning4j.

the class NetworkOrganizer method getIntersections.

/**
 * This method returns specified numbers of IP's by parsing original list of trees into some form of binary tree
 *
 * @param numShards
 * @param primary
 * @return
 */
protected List<String> getIntersections(int numShards, Collection<String> primary) {
    /**
     * Since each ip address can be represented in 4-byte sequence, 1 byte per value, with leading order - we'll use that to build tree
     */
    if (primary == null) {
        for (NetworkInformation information : informationCollection) {
            for (String ip : information.getIpAddresses()) {
                // first we get binary representation for each IP
                String octet = convertIpToOctets(ip);
                // then we map each of them into virtual "tree", to find most popular networks within cluster
                tree.map(octet);
            }
        }
        // we get most "popular" A network from tree now
        String octetA = tree.getHottestNetworkA();
        List<String> candidates = new ArrayList<>();
        AtomicInteger matchCount = new AtomicInteger(0);
        for (NetworkInformation node : informationCollection) {
            for (String ip : node.getIpAddresses()) {
                String octet = convertIpToOctets(ip);
                // calculating matches
                if (octet.startsWith(octetA)) {
                    matchCount.incrementAndGet();
                    candidates.add(ip);
                    break;
                }
            }
        }
        /**
         * TODO: improve this. we just need to iterate over popular networks instead of single top A network
         */
        if (matchCount.get() != informationCollection.size())
            throw new ND4JIllegalStateException("Mismatching A class");
        Collections.shuffle(candidates);
        return new ArrayList<>(candidates.subList(0, Math.min(numShards, candidates.size())));
    } else {
        // if primary isn't null, we expect network to be already filtered
        String octetA = tree.getHottestNetworkA();
        List<String> candidates = new ArrayList<>();
        for (NetworkInformation node : informationCollection) {
            for (String ip : node.getIpAddresses()) {
                String octet = convertIpToOctets(ip);
                // calculating matches
                if (octet.startsWith(octetA) && !primary.contains(ip)) {
                    candidates.add(ip);
                    break;
                }
            }
        }
        Collections.shuffle(candidates);
        return new ArrayList<>(candidates.subList(0, Math.min(numShards, candidates.size())));
    }
}

Example 60 with ND4JIllegalStateException

use of org.nd4j.linalg.exception.ND4JIllegalStateException in project nd4j by deeplearning4j.

the class NetworkOrganizer method toBinaryOctet.

protected static String toBinaryOctet(@NonNull Integer value) {
    if (value < 0 || value > 255)
        throw new ND4JIllegalStateException("IP octets cant hold values below 0 or above 255");
    String octetBase = Integer.toBinaryString(value);
    StringBuilder builder = new StringBuilder();
    for (int i = 0; i < 8 - octetBase.length(); i++) {
        builder.append("0");
    }
    builder.append(octetBase);
    return builder.toString();
}