diff --git a/libnd4j/include/ops/declarable/helpers/cuda/lup.cu b/libnd4j/include/ops/declarable/helpers/cuda/lup.cu
index bf9c73e7c..97d47079b 100644
--- a/libnd4j/include/ops/declarable/helpers/cuda/lup.cu
+++ b/libnd4j/include/ops/declarable/helpers/cuda/lup.cu
@@ -31,8 +31,6 @@
 namespace nd4j {
 namespace ops {
 namespace helpers {
-    nd4j::LaunchContext* defaultContext = nd4j::LaunchContext::defaultContext();
-
 //    template <typename T>
 //    static __device__ void swapRows_(T* matrix, Nd4jLong* shape, int theFirst, int theSecond, Nd4jLong N) {
 //        if (theFirst != theSecond) {
@@ -204,7 +202,7 @@ namespace helpers {
 
         if (inputMatrix->isIdentityMatrix()) return;
 
-        auto stream = defaultContext->getCudaStream();
+        auto stream = LaunchContext::defaultContext()->getCudaStream();
 
         // invert main diagonal
         upvertKernel<T> << < 1, n, 512, *stream >> >
@@ -227,7 +225,7 @@ namespace helpers {
     static void invertUpperMatrix_(NDArray* inputMatrix, NDArray* invertedMatrix) {
         int n = inputMatrix->rows();
         invertedMatrix->setIdentity();
-        auto stream = defaultContext->getCudaStream();
+        auto stream = LaunchContext::defaultContext()->getCudaStream();
         if (inputMatrix->isIdentityMatrix()) { // the inverse for I is I
             return;
         }
@@ -392,7 +390,6 @@ namespace helpers {
             auto n = input->rows();
             cusolverDnHandle_t cusolverH = nullptr;
             cusolverStatus_t status = cusolverDnCreate(&cusolverH);
-            defaultContext = context;
             if (CUSOLVER_STATUS_SUCCESS != status) {
                 throw cuda_exception::build("Cannot create cuSolver handle", status);
             }
@@ -543,9 +540,8 @@ namespace helpers {
 //        DataType dtype = input->dataType();
 //        if (dtype != DataType::DOUBLE)
 //            dtype = DataType::FLOAT32;
-            defaultContext = context;
             auto matrix = NDArrayFactory::create(input->ordering(), {n, n}, DataTypeUtils::fromT<T>(),
-                                                 defaultContext); //, block.getWorkspace());
+                                                 LaunchContext::defaultContext()); //, block.getWorkspace());
             auto det = NDArrayFactory::create<T>(1);
             auto stream = context->getCudaStream();
             NDArray::prepareSpecialUse({output}, {input});
@@ -578,7 +574,6 @@ namespace helpers {
         }
 
         int determinant(nd4j::LaunchContext *context, NDArray *input, NDArray *output) {
-            defaultContext = context;
             NDArray::prepareSpecialUse({output}, {input});
             BUILD_SINGLE_SELECTOR(input->dataType(), return determinant_, (context, input, output), FLOAT_NATIVE);
             NDArray::registerSpecialUse({output}, {input});
@@ -586,7 +581,6 @@ namespace helpers {
 
         template<typename T>
         int logAbsDeterminant_(LaunchContext *context, NDArray *input, NDArray *output) {
-            defaultContext = context;
             Nd4jLong n = input->sizeAt(-1);
             Nd4jLong n2 = n * n;
             std::vector<int> dims();
@@ -598,7 +592,7 @@ namespace helpers {
                 dtype = DataType::FLOAT32;
 
             auto matrix = NDArrayFactory::create(input->ordering(), {n, n}, dtype,
-                                                 defaultContext); //, block.getWorkspace());
+                                                 LaunchContext::defaultContext()); //, block.getWorkspace());
             auto det = NDArrayFactory::create<T>(1);
             auto stream = context->getCudaStream();
             NDArray::prepareSpecialUse({output}, {input});
@@ -633,7 +627,6 @@ namespace helpers {
         }
 
         int logAbsDeterminant(nd4j::LaunchContext *context, NDArray *input, NDArray *output) {
-            defaultContext = context;
             NDArray::prepareSpecialUse({output}, {input});
             BUILD_SINGLE_SELECTOR(input->dataType(), return logAbsDeterminant_, (context, input, output), FLOAT_NATIVE);
             NDArray::registerSpecialUse({output}, {input});
@@ -696,17 +689,16 @@ namespace helpers {
 
         template<typename T>
         static int inverse_(nd4j::LaunchContext *context, NDArray *input, NDArray *output) {
-            defaultContext = context;
             auto n = input->sizeAt(-1);
             auto n2 = n * n;
             auto dtype = DataTypeUtils::fromT<T>(); //input->dataType();
 //            if (dtype != DataType::DOUBLE)
 //                dtype = DataType::FLOAT32;
-            NDArray matrix = NDArrayFactory::create('c', {n, n}, dtype, defaultContext);
-            NDArray upper = NDArrayFactory::create('c', {n, n}, dtype, defaultContext);
-            NDArray lower = NDArrayFactory::create('c', {n, n}, dtype, defaultContext);
-            NDArray compound = NDArrayFactory::create('c', {n, n}, dtype, defaultContext);
-            NDArray permutation = NDArrayFactory::create('c', {n, n}, dtype, defaultContext);
+            NDArray matrix = NDArrayFactory::create('c', {n, n}, dtype, LaunchContext::defaultContext());
+            NDArray upper = NDArrayFactory::create('c', {n, n}, dtype, LaunchContext::defaultContext());
+            NDArray lower = NDArrayFactory::create('c', {n, n}, dtype, LaunchContext::defaultContext());
+            NDArray compound = NDArrayFactory::create('c', {n, n}, dtype, LaunchContext::defaultContext());
+            NDArray permutation = NDArrayFactory::create('c', {n, n}, dtype, LaunchContext::defaultContext());
             auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(input->getShapeInfo(),
                                                                                   {input->rankOf() - 2,
                                                                                    input->rankOf() - 1});
@@ -745,7 +737,6 @@ namespace helpers {
         }
 
         int inverse(nd4j::LaunchContext *context, NDArray *input, NDArray *output) {
-            defaultContext = context;
             NDArray::prepareSpecialUse({output}, {input});
             BUILD_SINGLE_SELECTOR(input->dataType(), return inverse_, (context, input, output), FLOAT_NATIVE);
             NDArray::registerSpecialUse({output}, {input});
@@ -788,7 +779,6 @@ namespace helpers {
         int cholesky__(LaunchContext *context, NDArray *input, NDArray *output, bool inplace) {
             if (!inplace)
                 output->assign(input);
-            defaultContext = context;
             std::unique_ptr<NDArray> tempOutput(output->dup());
             cusolverDnHandle_t handle = nullptr;
             auto n = input->sizeAt(-1);
@@ -868,7 +858,6 @@ namespace helpers {
 
 //    template <typename T>
         int cholesky_(LaunchContext *context, NDArray *input, NDArray *output, bool inplace) {
-            defaultContext = context;
             NDArray::prepareSpecialUse({output}, {input});
             if (input->dataType() == DataType::DOUBLE)
                 cholesky__<double>(context, input, output, inplace);
@@ -877,7 +866,7 @@ namespace helpers {
             else {
                 std::unique_ptr<NDArray> tempOutput(
                         NDArrayFactory::create_('c', input->getShapeAsVector(), DataType::FLOAT32,
-                                                defaultContext));
+                                                LaunchContext::defaultContext()));
                 tempOutput->assign(input);
                 cholesky__<float>(context, tempOutput.get(), tempOutput.get(), true);
                 output->assign(tempOutput.get());
@@ -888,7 +877,6 @@ namespace helpers {
 
         int cholesky(nd4j::LaunchContext *context, NDArray *input, NDArray *output, bool inplace) {
 //        BUILD_SINGLE_SELECTOR(input->dataType(), return cholesky_, (context, input, output, inplace), FLOAT_TYPES);
-            defaultContext = context;
             return cholesky_(context, input, output, inplace);
         }
 //    BUILD_SINGLE_TEMPLATE(template int cholesky_, (LaunchContext* context, NDArray* input, NDArray* output, bool inplace), FLOAT_TYPES);
@@ -927,7 +915,6 @@ namespace helpers {
 
         template<typename T>
         int logdetFunctor_(nd4j::LaunchContext *context, NDArray *input, NDArray *output) {
-            defaultContext = context;
             NDArray::prepareSpecialUse({output}, {input});
             auto n2 = input->sizeAt(-1) * input->sizeAt(-2);
             auto stream = context->getCudaStream();
@@ -957,7 +944,6 @@ namespace helpers {
         }
 
         int logdetFunctor(nd4j::LaunchContext *context, NDArray *input, NDArray *output) {
-            defaultContext = context;
             BUILD_SINGLE_SELECTOR(output->dataType(), logdetFunctor_, (context, input, output), FLOAT_NATIVE);
         }