Playing with some new code 2 - clean build/test

Signed-off-by: brian <brian@brutex.de>

cavis-dnn/cavis-dnn-api/src/main/java/org/nd4j/linalg/workspace/WorkspaceMgr.java

@@ -67,7 +67,7 @@ public interface WorkspaceMgr<T extends Enum<T>> {
 
     /**
      * Set arrays to be scoped out (not in any workspace) for the specified array type.
-     * This means that create, dup, leverage etc methods will return result arrays that are not attached to any workspace
+     * This means that create, dup, leverage etc. methods will return result arrays that are not attached to any workspace
      *
      * @param arrayType Array type to set scoped out for
      */
@@ -120,7 +120,7 @@ public interface WorkspaceMgr<T extends Enum<T>> {
     boolean isWorkspaceOpen(T arrayType);
 
     /**
-     * Assert thath the workspace for the specified array type is open.
+     * Assert that the workspace for the specified array type is open.
      * For array types that are set to scoped out, this will be treated as a no-op
      * @param arrayType Array type to check
      * @param msg       May be null. If non-null: include this in the exception
@@ -129,7 +129,7 @@ public interface WorkspaceMgr<T extends Enum<T>> {
     void assertOpen(T arrayType, String msg) throws ND4JWorkspaceException;
 
     /**
-     * Assert thath the workspace for the specified array type is not open.
+     * Assert that the workspace for the specified array type is not open.
      * For array types that are set to scoped out, this will be treated as a no-op
      * @param arrayType Array type to check
      * @param msg       May be null. If non-null: include this in the exception
@@ -193,7 +193,7 @@ public interface WorkspaceMgr<T extends Enum<T>> {
 
     /**
      * Create an uninitialized array in the specified array type's workspace (or detached if none is specified).
-     * Equivalent to {@link org.nd4j.linalg.factory.Nd4j#createUninitialized(int)} (int...)}, other than the array location
+     * Equivalent to {@link org.nd4j.linalg.factory.Nd4j#createUninitialized(int...)}, other than the array location
      * @param arrayType Array type
      * @param dataType  Data type of the created array
      * @param shape     Shape
@@ -231,7 +231,7 @@ public interface WorkspaceMgr<T extends Enum<T>> {
 
     /**
      * Cast the specified array to the specified datatype.<br>
-     * If the array is already the correct type, the bahaviour depends on the 'dupIfCorrectType' argument.<br>
+     * If the array is already the correct type, the behaviour depends on the 'dupIfCorrectType' argument.<br>
      * dupIfCorrectType = false && toCast.dataType() == dataType: return input array as-is (unless workspace is wrong)<br>
      * dupIfCorrectType = true && toCast.dataType() == dataType: duplicate the array into the specified workspace<br>
      * @param arrayType        Array type

cavis-dnn/cavis-dnn-core/src/test/java/org/deeplearning4j/eval/EvaluationToolsTests.java

@@ -81,7 +81,7 @@ public class EvaluationToolsTests extends BaseDL4JTest {
 
 
             String str = EvaluationTools.rocChartToHtml(roc);
-            //            System.out.println(str);
+            System.out.println(str);
         }
     }
 

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/Cnn3DLossLayer.java

@@ -58,6 +58,8 @@ public class Cnn3DLossLayer extends FeedForwardLayer {
                              int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType) {
         setNetConfiguration(conf);
         LayerConfiguration lconf = conf.getFlattenedLayerConfigurations().get(layerIndex);
+        runInheritance();
+
         org.deeplearning4j.nn.layers.convolution.Cnn3DLossLayer ret =
                         new org.deeplearning4j.nn.layers.convolution.Cnn3DLossLayer(lconf, networkDataType);
         ret.addTrainingListeners(trainingListeners);

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/CnnLossLayer.java

@@ -63,6 +63,8 @@ public class CnnLossLayer extends FeedForwardLayer {
                              int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType) {
         setNetConfiguration(conf);
         LayerConfiguration lconf = conf.getFlattenedLayerConfigurations().get(layerIndex);
+        runInheritance();
+
         org.deeplearning4j.nn.layers.convolution.CnnLossLayer ret =
                         new org.deeplearning4j.nn.layers.convolution.CnnLossLayer(lconf, networkDataType);
         ret.addTrainingListeners(trainingListeners);

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/GravesLSTM.java

@@ -77,7 +77,11 @@ public class GravesLSTM extends AbstractLSTM {
     public Layer instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners,
                              int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType) {
         LayerValidation.assertNInNOutSet("GravesLSTM", getLayerName(), layerIndex, getNIn(), getNOut());
+
         LayerConfiguration lconf = conf.getFlattenedLayerConfigurations().get(layerIndex);
+        lconf.setNetConfiguration(conf);
+        runInheritance();
+
         org.deeplearning4j.nn.layers.recurrent.GravesLSTM ret =
                         new org.deeplearning4j.nn.layers.recurrent.GravesLSTM(lconf, networkDataType);
 

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/RnnLossLayer.java

@@ -61,6 +61,8 @@ public class RnnLossLayer extends FeedForwardLayer {
                              int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType) {
 
         LayerConfiguration lconf = conf.getFlattenedLayerConfigurations().get(layerIndex);
+        lconf.setNetConfiguration(conf);
+        runInheritance();
 
         org.deeplearning4j.nn.layers.recurrent.RnnLossLayer ret =
                         new org.deeplearning4j.nn.layers.recurrent.RnnLossLayer(lconf, networkDataType);

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/conf/layers/SubsamplingLayer.java

@@ -135,6 +135,7 @@ public class SubsamplingLayer extends NoParamLayer {
                                                        Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView,
                                                        boolean initializeParams, DataType networkDataType) {
         LayerConfiguration lconf = conf.getFlattenedLayerConfigurations().get(layerIndex);
+        runInheritance();
 
         org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer ret =
                 new org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingLayer(lconf, networkDataType);

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/layers/AbstractLayer.java

@@ -24,6 +24,8 @@ import java.util.ArrayList;
 import java.util.Collection;
 import java.util.List;
 import java.util.Map;
+import java.util.stream.Collectors;
+
 import lombok.*;
 import net.brutex.ai.dnn.api.IModel;
 import org.deeplearning4j.nn.api.ITraininableLayerConfiguration;
@@ -328,13 +330,9 @@ public abstract class AbstractLayer<LayerConf_T extends LayerConfiguration> impl
   @Override
   public void clearNoiseWeightParams() {}
 
-  public List<String> variables() {
+  public List<String> getVariables(boolean copy) {
-    return variables;
-  }
-
-  public List<String> variables(boolean copy) {
     if (copy) {
-      return variables();
+      return new ArrayList<>(getVariables());
     }
     return variables;
   }
@@ -585,7 +583,7 @@ public abstract class AbstractLayer<LayerConf_T extends LayerConfiguration> impl
    */
   @Override
   public INDArray getParams() {
-    // throw new RuntimeException("Not implemented");
+    //throw new RuntimeException("Not implemented");
     return null;
   }
 

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/layers/BaseLayer.java

@@ -184,6 +184,17 @@ public abstract class BaseLayer<LayerConfT extends BaseLayerConfiguration>
     setParams(params, 'f');
   }
 
+  /**
+   * * The AbstractLayer does not implement Params, ParamTable and GradientView. A RuntimeException
+   * * will be triggered when calling this.
+   *
+   * @return 1d parameter vector
+   */
+  @Override
+  public INDArray getParams() {
+    return paramsFlattened;
+  }
+
   /** */
   @Override
   public void close() {}
@@ -358,7 +369,7 @@ public abstract class BaseLayer<LayerConfT extends BaseLayerConfiguration>
 
   protected void setParams(INDArray params, char order) {
     if (params == null) {
-      log.warn(
+      log.trace(
           "setParams(INDArray params, char order): params is null. Skipping setParams in Layer {}[{}] at index {}",
           getLayerConfiguration().getLayerName(),
           getClass().getSimpleName(),

cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/params/DefaultParamInitializer.java

@@ -110,14 +110,14 @@ public class DefaultParamInitializer extends AbstractParamInitializer {
         INDArray weightView = paramsView.get(NDArrayIndex.interval(0,0,true), NDArrayIndex.interval(0, nWeightParams));
 
         params.put(WEIGHT_KEY, createWeightMatrix(layerConf, weightView, initializeParams));
-        layerConf.getNetConfiguration().addNetWideVariable(WEIGHT_KEY);
+        layerConf.addVariable(WEIGHT_KEY);
 
         long offset = nWeightParams;
         if(hasBias(layerConf)){
             INDArray biasView = paramsView.get(NDArrayIndex.interval(0,0,true),
                     NDArrayIndex.interval(offset, offset + nOut));
             params.put(BIAS_KEY, createBias(layerConf, biasView, initializeParams));
-            layerConf.getNetConfiguration().addNetWideVariable(BIAS_KEY);
+            layerConf.addVariable(BIAS_KEY);
             offset += nOut;
         }
 
@@ -125,7 +125,7 @@ public class DefaultParamInitializer extends AbstractParamInitializer {
             INDArray gainView = paramsView.get(NDArrayIndex.interval(0,0,true),
                     NDArrayIndex.interval(offset, offset + nOut));
             params.put(GAIN_KEY, createGain(conf, gainView, initializeParams));
-            conf.getNetConfiguration().addNetWideVariable(GAIN_KEY);
+            conf.addVariable(GAIN_KEY);
         }
 
         return params;

cavis-native/cavis-native-cpu/src/main/java/org/nd4j/linalg/cpu/nativecpu/ops/CpuOpContext.java

@@ -50,7 +50,8 @@ public class CpuOpContext extends BaseOpContext implements OpContext, Deallocata
 
     @Override
     public void close() {
-        // no-op
+        nativeOps.ctxPurge(context);
+        context.deallocate();
     }
 
     @Override

cavis-native/cavis-native-jcublas/src/main/java/org/nd4j/jita/workspace/CudaWorkspace.java

@@ -20,6 +20,8 @@
 
 package org.nd4j.jita.workspace;
 
+import java.util.List;
+import java.util.Queue;
 import lombok.NonNull;
 import lombok.extern.slf4j.Slf4j;
 import lombok.val;
@@ -39,10 +41,6 @@ import org.nd4j.linalg.exception.ND4JIllegalStateException;
 import org.nd4j.linalg.factory.Nd4j;
 import org.nd4j.nativeblas.NativeOpsHolder;
 
-import java.util.List;
-import java.util.Queue;
-
-
 /**
  * CUDA-aware MemoryWorkspace implementation
  *
@@ -51,7 +49,6 @@ import java.util.Queue;
 @Slf4j
 public class CudaWorkspace extends Nd4jWorkspace {
 
-
   public CudaWorkspace(@NonNull WorkspaceConfiguration configuration) {
     super(configuration);
   }
@@ -60,7 +57,10 @@ public class CudaWorkspace extends Nd4jWorkspace {
     super(configuration, workspaceId);
   }
 
-    public CudaWorkspace(@NonNull WorkspaceConfiguration configuration, @NonNull String workspaceId, Integer deviceId) {
+  public CudaWorkspace(
+      @NonNull WorkspaceConfiguration configuration,
+      @NonNull String workspaceId,
+      Integer deviceId) {
     super(configuration, workspaceId);
     this.deviceId = deviceId;
   }
@@ -74,29 +74,39 @@ public class CudaWorkspace extends Nd4jWorkspace {
     super.init();
 
     if (currentSize.get() > 0) {
-            //log.info("Allocating {} bytes at DEVICE & HOST space...", currentSize.get());
+      log.debug("Allocating {} bytes at DEVICE & HOST space...", currentSize.get());
       isInit.set(true);
 
       long bytes = currentSize.get();
 
-            if (isDebug.get())
+      log.debug(
-                log.info("Allocating [{}] workspace on device_{}, {} bytes...", id, Nd4j.getAffinityManager().getDeviceForCurrentThread(), bytes);
+          "Allocating [{}] workspace on device_{}, {} bytes...",
+          id,
+          Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+          bytes);
 
       if (isDebug.get()) {
         Nd4j.getWorkspaceManager().printAllocationStatisticsForCurrentThread();
       }
 
       Pointer ptr = memoryManager.allocate((bytes + SAFETY_OFFSET), MemoryKind.HOST, false);
-            if (ptr == null)
+      if (ptr == null) throw new ND4JIllegalStateException("Can't allocate memory for workspace");
-                throw new ND4JIllegalStateException("Can't allocate memory for workspace");
 
       workspace.setHostPointer(new PagedPointer(ptr));
 
       if (workspaceConfiguration.getPolicyMirroring() != MirroringPolicy.HOST_ONLY) {
-                workspace.setDevicePointer(new PagedPointer(memoryManager.allocate((bytes + SAFETY_OFFSET), MemoryKind.DEVICE, false)));
+        workspace.setDevicePointer(
-                AllocationsTracker.getInstance().markAllocated(AllocationKind.GENERAL, Nd4j.getAffinityManager().getDeviceForCurrentThread(), bytes + SAFETY_OFFSET);
+            new PagedPointer(
+                memoryManager.allocate((bytes + SAFETY_OFFSET), MemoryKind.DEVICE, false)));
+        AllocationsTracker.getInstance()
+            .markAllocated(
+                AllocationKind.GENERAL,
+                Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+                bytes + SAFETY_OFFSET);
 
-                MemoryTracker.getInstance().incrementWorkspaceAllocatedAmount(Nd4j.getAffinityManager().getDeviceForCurrentThread(), bytes + SAFETY_OFFSET);
+        MemoryTracker.getInstance()
+            .incrementWorkspaceAllocatedAmount(
+                Nd4j.getAffinityManager().getDeviceForCurrentThread(), bytes + SAFETY_OFFSET);
 
         // if base pointer isn't aligned to 16 bytes (128 bits) - adjust the offfset then
         val addr = workspace.getDevicePointer().address();
@@ -114,14 +124,12 @@ public class CudaWorkspace extends Nd4jWorkspace {
     return this.alloc(requiredMemory, MemoryKind.DEVICE, type, initialize);
   }
 
-
   @Override
   public synchronized void destroyWorkspace(boolean extended) {
     val size = currentSize.getAndSet(0);
     reset();
 
-        if (extended)
+    if (extended) clearExternalAllocations();
-            clearExternalAllocations();
 
     clearPinnedAllocations(extended);
 
@@ -129,20 +137,27 @@ public class CudaWorkspace extends Nd4jWorkspace {
       NativeOpsHolder.getInstance().getDeviceNativeOps().freeHost(workspace.getHostPointer());
 
     if (workspace.getDevicePointer() != null) {
-            NativeOpsHolder.getInstance().getDeviceNativeOps().freeDevice(workspace.getDevicePointer(), 0);
+      NativeOpsHolder.getInstance()
-            AllocationsTracker.getInstance().markReleased(AllocationKind.GENERAL, Nd4j.getAffinityManager().getDeviceForCurrentThread(), size + SAFETY_OFFSET);
+          .getDeviceNativeOps()
+          .freeDevice(workspace.getDevicePointer(), 0);
+      AllocationsTracker.getInstance()
+          .markReleased(
+              AllocationKind.GENERAL,
+              Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+              size + SAFETY_OFFSET);
 
-            MemoryTracker.getInstance().decrementWorkspaceAmount(Nd4j.getAffinityManager().getDeviceForCurrentThread(), size + SAFETY_OFFSET);
+      MemoryTracker.getInstance()
+          .decrementWorkspaceAmount(
+              Nd4j.getAffinityManager().getDeviceForCurrentThread(), size + SAFETY_OFFSET);
     }
 
     workspace.setDevicePointer(null);
     workspace.setHostPointer(null);
-
   }
 
-
   @Override
-    public PagedPointer alloc(long requiredMemory, MemoryKind kind, DataType type, boolean initialize) {
+  public PagedPointer alloc(
+      long requiredMemory, MemoryKind kind, DataType type, boolean initialize) {
     long numElements = requiredMemory / Nd4j.sizeOfDataType(type);
 
     // alignment
@@ -151,48 +166,74 @@ public class CudaWorkspace extends Nd4jWorkspace {
 
     if (!isUsed.get()) {
       if (disabledCounter.incrementAndGet() % 10 == 0)
-                log.warn("Worskpace was turned off, and wasn't enabled after {} allocations", disabledCounter.get());
+        log.warn(
+            "Workspace was turned off, and wasn't enabled after {} allocations",
+            disabledCounter.get());
 
       if (kind == MemoryKind.DEVICE) {
-                val pointer = new PagedPointer(memoryManager.allocate(requiredMemory, MemoryKind.DEVICE, initialize), numElements);
+        val pointer =
+            new PagedPointer(
+                memoryManager.allocate(requiredMemory, MemoryKind.DEVICE, initialize), numElements);
         externalAllocations.add(new PointersPair(null, pointer));
-                MemoryTracker.getInstance().incrementWorkspaceAllocatedAmount(Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory);
+        MemoryTracker.getInstance()
+            .incrementWorkspaceAllocatedAmount(
+                Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory);
         return pointer;
       } else {
-                val pointer = new PagedPointer(memoryManager.allocate(requiredMemory, MemoryKind.HOST, initialize), numElements);
+        val pointer =
+            new PagedPointer(
+                memoryManager.allocate(requiredMemory, MemoryKind.HOST, initialize), numElements);
         externalAllocations.add(new PointersPair(pointer, null));
         return pointer;
       }
-
-
     }
 
-        boolean trimmer = (workspaceConfiguration.getPolicyReset() == ResetPolicy.ENDOFBUFFER_REACHED && requiredMemory + cycleAllocations.get() > initialBlockSize.get() && initialBlockSize.get() > 0 && kind == MemoryKind.DEVICE) || trimmedMode.get();
+    boolean trimmer =
+        (workspaceConfiguration.getPolicyReset() == ResetPolicy.ENDOFBUFFER_REACHED
+                && requiredMemory + cycleAllocations.get() > initialBlockSize.get()
+                && initialBlockSize.get() > 0
+                && kind == MemoryKind.DEVICE)
+            || trimmedMode.get();
 
-        if (trimmer && workspaceConfiguration.getPolicySpill() == SpillPolicy.REALLOCATE && !trimmedMode.get()) {
+    if (trimmer
+        && workspaceConfiguration.getPolicySpill() == SpillPolicy.REALLOCATE
+        && !trimmedMode.get()) {
       trimmedMode.set(true);
       trimmedStep.set(stepsCount.get());
     }
 
     if (kind == MemoryKind.DEVICE) {
-            if (deviceOffset.get() + requiredMemory <= currentSize.get() && !trimmer && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
+      if (deviceOffset.get() + requiredMemory <= currentSize.get()
+          && !trimmer
+          && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
         cycleAllocations.addAndGet(requiredMemory);
         long prevOffset = deviceOffset.getAndAdd(requiredMemory);
 
-                if (workspaceConfiguration.getPolicyMirroring() == MirroringPolicy.HOST_ONLY)
+        if (workspaceConfiguration.getPolicyMirroring() == MirroringPolicy.HOST_ONLY) return null;
-                    return null;
 
         val ptr = workspace.getDevicePointer().withOffset(prevOffset, numElements);
 
-                if (isDebug.get())
+        log.debug(
-                    log.info("Workspace [{}] device_{}: alloc array of {} bytes, capacity of {} elements; prevOffset: {}; newOffset: {}; size: {}; address: {}", id, Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory, numElements, prevOffset, deviceOffset.get(), currentSize.get(), ptr.address());
+            "Workspace [{}] device_{}: alloc array of {} bytes, capacity of {} elements; prevOffset: {}; newOffset: {}; size: {}; address: {}",
+            id,
+            Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+            requiredMemory,
+            numElements,
+            prevOffset,
+            deviceOffset.get(),
+            currentSize.get(),
+            ptr.address());
 
         if (initialize) {
           val context = AtomicAllocator.getInstance().getDeviceContext();
 
-                    int ret = NativeOpsHolder.getInstance().getDeviceNativeOps().memsetAsync(ptr, 0, requiredMemory, 0, context.getSpecialStream());
+          int ret =
+              NativeOpsHolder.getInstance()
+                  .getDeviceNativeOps()
+                  .memsetAsync(ptr, 0, requiredMemory, 0, context.getSpecialStream());
           if (ret == 0)
-                        throw new ND4JIllegalStateException("memset failed device_" + Nd4j.getAffinityManager().getDeviceForCurrentThread());
+            throw new ND4JIllegalStateException(
+                "memset failed device_" + Nd4j.getAffinityManager().getDeviceForCurrentThread());
 
           context.syncSpecialStream();
         }
@@ -201,28 +242,34 @@ public class CudaWorkspace extends Nd4jWorkspace {
       } else {
 
         // spill
-                if (workspaceConfiguration.getPolicyReset() == ResetPolicy.ENDOFBUFFER_REACHED && currentSize.get() > 0 && !trimmer && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
+        if (workspaceConfiguration.getPolicyReset() == ResetPolicy.ENDOFBUFFER_REACHED
-                    //log.info("End of space reached. Current offset: {}; requiredMemory: {}", deviceOffset.get(), requiredMemory);
+            && currentSize.get() > 0
+            && !trimmer
+            && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
+          // log.info("End of space reached. Current offset: {}; requiredMemory: {}",
+          // deviceOffset.get(), requiredMemory);
           deviceOffset.set(0);
           resetPlanned.set(true);
           return alloc(requiredMemory, kind, type, initialize);
         }
 
-                if (!trimmer)
+        if (!trimmer) spilledAllocationsSize.addAndGet(requiredMemory);
-                    spilledAllocationsSize.addAndGet(requiredMemory);
+        else pinnedAllocationsSize.addAndGet(requiredMemory);
-                else
-                    pinnedAllocationsSize.addAndGet(requiredMemory);
 
-                if (isDebug.get()) {
+        log.debug(
-                    log.info("Workspace [{}] device_{}: spilled DEVICE array of {} bytes, capacity of {} elements", id, Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory, numElements);
+            "Workspace [{}] device_{}: spilled DEVICE array of {} bytes, capacity of {} elements",
-                }
+            id,
+            Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+            requiredMemory,
+            numElements);
 
-                val shape = new AllocationShape(requiredMemory / Nd4j.sizeOfDataType(type), Nd4j.sizeOfDataType(type), type);
+        val shape =
+            new AllocationShape(
+                requiredMemory / Nd4j.sizeOfDataType(type), Nd4j.sizeOfDataType(type), type);
 
         cycleAllocations.addAndGet(requiredMemory);
 
-                if (workspaceConfiguration.getPolicyMirroring() == MirroringPolicy.HOST_ONLY)
+        if (workspaceConfiguration.getPolicyMirroring() == MirroringPolicy.HOST_ONLY) return null;
-                    return null;
 
         switch (workspaceConfiguration.getPolicySpill()) {
           case REALLOCATE:
@@ -230,116 +277,149 @@ public class CudaWorkspace extends Nd4jWorkspace {
             if (!trimmer) {
               externalCount.incrementAndGet();
               //
-                            //AtomicAllocator.getInstance().getMemoryHandler().getMemoryProvider().malloc(shape, null, AllocationStatus.DEVICE).getDevicePointer()
+              // AtomicAllocator.getInstance().getMemoryHandler().getMemoryProvider().malloc(shape,
-                            val pointer = new PagedPointer(memoryManager.allocate(requiredMemory, MemoryKind.DEVICE, initialize), numElements);
+              // null, AllocationStatus.DEVICE).getDevicePointer()
+              val pointer =
+                  new PagedPointer(
+                      memoryManager.allocate(requiredMemory, MemoryKind.DEVICE, initialize),
+                      numElements);
               pointer.isLeaked();
 
               val pp = new PointersPair(null, pointer);
               pp.setRequiredMemory(requiredMemory);
               externalAllocations.add(pp);
 
-                            MemoryTracker.getInstance().incrementWorkspaceAllocatedAmount(Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory);
+              MemoryTracker.getInstance()
+                  .incrementWorkspaceAllocatedAmount(
+                      Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory);
               return pointer;
             } else {
               pinnedCount.incrementAndGet();
 
-                            val pointer = new PagedPointer(memoryManager.allocate(requiredMemory, MemoryKind.DEVICE, initialize), numElements);
+              val pointer =
+                  new PagedPointer(
+                      memoryManager.allocate(requiredMemory, MemoryKind.DEVICE, initialize),
+                      numElements);
               pointer.isLeaked();
 
-                            pinnedAllocations.add(new PointersPair(stepsCount.get(), requiredMemory, null, pointer));
+              pinnedAllocations.add(
-                            MemoryTracker.getInstance().incrementWorkspaceAllocatedAmount(Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory);
+                  new PointersPair(stepsCount.get(), requiredMemory, null, pointer));
+              MemoryTracker.getInstance()
+                  .incrementWorkspaceAllocatedAmount(
+                      Nd4j.getAffinityManager().getDeviceForCurrentThread(), requiredMemory);
               return pointer;
             }
           case FAIL:
-                    default: {
+          default:
+            {
               throw new ND4JIllegalStateException("Can't allocate memory: Workspace is full");
             }
         }
       }
     } else if (kind == MemoryKind.HOST) {
-            if (hostOffset.get() + requiredMemory <= currentSize.get() && !trimmer && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
+      if (hostOffset.get() + requiredMemory <= currentSize.get()
+          && !trimmer
+          && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
 
         long prevOffset = hostOffset.getAndAdd(requiredMemory);
 
         val ptr = workspace.getHostPointer().withOffset(prevOffset, numElements);
 
         // && workspaceConfiguration.getPolicyMirroring() == MirroringPolicy.HOST_ONLY
-                if (initialize)
+        if (initialize) Pointer.memset(ptr, 0, requiredMemory);
-                    Pointer.memset(ptr, 0, requiredMemory);
         return ptr;
       } else {
-           //     log.info("Spilled HOST array of {} bytes, capacity of {} elements", requiredMemory, numElements);
+        //     log.info("Spilled HOST array of {} bytes, capacity of {} elements", requiredMemory,
-                if (workspaceConfiguration.getPolicyReset() == ResetPolicy.ENDOFBUFFER_REACHED && currentSize.get() > 0 && !trimmer && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
+        // numElements);
-                    //log.info("End of space reached. Current offset: {}; requiredMemory: {}", deviceOffset.get(), requiredMemory);
+        if (workspaceConfiguration.getPolicyReset() == ResetPolicy.ENDOFBUFFER_REACHED
+            && currentSize.get() > 0
+            && !trimmer
+            && Nd4j.getWorkspaceManager().getDebugMode() != DebugMode.SPILL_EVERYTHING) {
+          // log.info("End of space reached. Current offset: {}; requiredMemory: {}",
+          // deviceOffset.get(), requiredMemory);
           hostOffset.set(0);
-                    //resetPlanned.set(true);
+          // resetPlanned.set(true);
           return alloc(requiredMemory, kind, type, initialize);
         }
 
-                val shape = new AllocationShape(requiredMemory / Nd4j.sizeOfDataType(type), Nd4j.sizeOfDataType(type), type);
+        val shape =
+            new AllocationShape(
+                requiredMemory / Nd4j.sizeOfDataType(type), Nd4j.sizeOfDataType(type), type);
 
         switch (workspaceConfiguration.getPolicySpill()) {
           case REALLOCATE:
           case EXTERNAL:
             if (!trimmer) {
-                            //memoryManager.allocate(requiredMemory, MemoryKind.HOST, true)
+              // memoryManager.allocate(requiredMemory, MemoryKind.HOST, true)
-                            //AtomicAllocator.getInstance().getMemoryHandler().getMemoryProvider().malloc(shape, null, AllocationStatus.DEVICE).getDevicePointer()
+              // AtomicAllocator.getInstance().getMemoryHandler().getMemoryProvider().malloc(shape,
-                            PagedPointer pointer = new PagedPointer(memoryManager.allocate(requiredMemory, MemoryKind.HOST, initialize), numElements);
+              // null, AllocationStatus.DEVICE).getDevicePointer()
+              PagedPointer pointer =
+                  new PagedPointer(
+                      memoryManager.allocate(requiredMemory, MemoryKind.HOST, initialize),
+                      numElements);
 
               externalAllocations.add(new PointersPair(pointer, null));
               return pointer;
             } else {
-                            //AtomicAllocator.getInstance().getMemoryHandler().getMemoryProvider().malloc(shape, null, AllocationStatus.DEVICE).getDevicePointer()
+              // AtomicAllocator.getInstance().getMemoryHandler().getMemoryProvider().malloc(shape,
-                            PagedPointer pointer = new PagedPointer(memoryManager.allocate(requiredMemory, MemoryKind.HOST, initialize), numElements);
+              // null, AllocationStatus.DEVICE).getDevicePointer()
+              PagedPointer pointer =
+                  new PagedPointer(
+                      memoryManager.allocate(requiredMemory, MemoryKind.HOST, initialize),
+                      numElements);
               pointer.isLeaked();
 
               pinnedAllocations.add(new PointersPair(stepsCount.get(), 0L, pointer, null));
               return pointer;
             }
           case FAIL:
-                    default: {
+          default:
+            {
               throw new ND4JIllegalStateException("Can't allocate memory: Workspace is full");
             }
         }
       }
     } else throw new ND4JIllegalStateException("Unknown MemoryKind was passed in: " + kind);
 
-        //throw new ND4JIllegalStateException("Shouldn't ever reach this line");
+    // throw new ND4JIllegalStateException("Shouldn't ever reach this line");
   }
 
   @Override
   protected void clearPinnedAllocations(boolean extended) {
-        if (isDebug.get())
+
-            log.info("Workspace [{}] device_{} threadId {} cycle {}: clearing pinned allocations...", id, Nd4j.getAffinityManager().getDeviceForCurrentThread(), Thread.currentThread().getId(), cyclesCount.get());
+    log.debug(
+        "Workspace [{}] device_{} threadId {} cycle {}: clearing pinned allocations...",
+        id,
+        Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+        Thread.currentThread().getId(),
+        cyclesCount.get());
 
     while (!pinnedAllocations.isEmpty()) {
       val pair = pinnedAllocations.peek();
-            if (pair == null)
+      if (pair == null) throw new RuntimeException();
-                throw new RuntimeException();
 
       long stepNumber = pair.getAllocationCycle();
       long stepCurrent = stepsCount.get();
 
-            if (isDebug.get())
+      log.debug("Allocation step: {}; Current step: {}", stepNumber, stepCurrent);
-                log.info("Allocation step: {}; Current step: {}", stepNumber, stepCurrent);
 
       if (stepNumber + 2 < stepCurrent || extended) {
         pinnedAllocations.remove();
 
         if (pair.getDevicePointer() != null) {
           NativeOpsHolder.getInstance().getDeviceNativeOps().freeDevice(pair.getDevicePointer(), 0);
-                    MemoryTracker.getInstance().decrementWorkspaceAmount(Nd4j.getAffinityManager().getDeviceForCurrentThread(), pair.getRequiredMemory());
+          MemoryTracker.getInstance()
+              .decrementWorkspaceAmount(
+                  Nd4j.getAffinityManager().getDeviceForCurrentThread(), pair.getRequiredMemory());
           pinnedCount.decrementAndGet();
 
-                    if (isDebug.get())
+          log.debug("deleting external device allocation ");
-                        log.info("deleting external device allocation ");
         }
 
         if (pair.getHostPointer() != null) {
           NativeOpsHolder.getInstance().getDeviceNativeOps().freeHost(pair.getHostPointer());
 
-                    if (isDebug.get())
+          log.debug("deleting external host allocation ");
-                        log.info("deleting external host allocation ");
         }
 
         val sizez = pair.getRequiredMemory() * -1;
@@ -352,8 +432,13 @@ public class CudaWorkspace extends Nd4jWorkspace {
 
   @Override
   protected void clearExternalAllocations() {
-        if (isDebug.get())
+
-            log.info("Workspace [{}] device_{} threadId {} guid [{}]: clearing external allocations...", id, Nd4j.getAffinityManager().getDeviceForCurrentThread(), Thread.currentThread().getId(), guid);
+    log.debug(
+        "Workspace [{}] device_{} threadId {} guid [{}]: clearing external allocations...",
+        id,
+        Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+        Thread.currentThread().getId(),
+        guid);
 
     Nd4j.getExecutioner().commit();
 
@@ -362,25 +447,34 @@ public class CudaWorkspace extends Nd4jWorkspace {
         if (pair.getHostPointer() != null) {
           NativeOpsHolder.getInstance().getDeviceNativeOps().freeHost(pair.getHostPointer());
 
-                    if (isDebug.get())
+          log.debug("deleting external host allocation... ");
-                        log.info("deleting external host allocation... ");
         }
 
         if (pair.getDevicePointer() != null) {
           NativeOpsHolder.getInstance().getDeviceNativeOps().freeDevice(pair.getDevicePointer(), 0);
 
-                    if (isDebug.get())
+          log.debug("deleting external device allocation... ");
-                        log.info("deleting external device allocation... ");
 
           val sizez = pair.getRequiredMemory();
           if (sizez != null) {
-                        AllocationsTracker.getInstance().markReleased(AllocationKind.GENERAL, Nd4j.getAffinityManager().getDeviceForCurrentThread(), sizez);
+            AllocationsTracker.getInstance()
-                        MemoryTracker.getInstance().decrementWorkspaceAmount(Nd4j.getAffinityManager().getDeviceForCurrentThread(), sizez);
+                .markReleased(
+                    AllocationKind.GENERAL,
+                    Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+                    sizez);
+            MemoryTracker.getInstance()
+                .decrementWorkspaceAmount(
+                    Nd4j.getAffinityManager().getDeviceForCurrentThread(), sizez);
           }
         }
       }
     } catch (Exception e) {
-            log.error("RC: Workspace [{}] device_{} threadId {} guid [{}]: clearing external allocations...", id, Nd4j.getAffinityManager().getDeviceForCurrentThread(), Thread.currentThread().getId(), guid);
+      log.error(
+          "RC: Workspace [{}] device_{} threadId {} guid [{}]: clearing external allocations...",
+          id,
+          Nd4j.getAffinityManager().getDeviceForCurrentThread(),
+          Thread.currentThread().getId(),
+          guid);
       throw new RuntimeException(e);
     }
 
@@ -391,11 +485,9 @@ public class CudaWorkspace extends Nd4jWorkspace {
 
   @Override
   protected void resetWorkspace() {
-        if (currentSize.get() < 1) {
+    if (currentSize.get() < 1) {}
-        }
 
-
+    /*
-/*
     if (Nd4j.getExecutioner() instanceof GridExecutioner)
         ((GridExecutioner) Nd4j.getExecutioner()).flushQueueBlocking();
 

cavis-native/cavis-native-jcublas/src/main/java/org/nd4j/jita/workspace/CudaWorkspaceDeallocator.java

@@ -48,7 +48,7 @@ public class CudaWorkspaceDeallocator implements Deallocator {
 
     @Override
     public void deallocate() {
-        log.trace("Deallocating CUDA workspace");
+        log.debug("Deallocating CUDA workspace");
 
         // purging workspace planes
         if (pointersPair != null) {

cavis-native/cavis-native-jcublas/src/main/java/org/nd4j/linalg/jcublas/ops/executioner/CudaExecutioner.java

@@ -1582,7 +1582,7 @@ public class CudaExecutioner extends DefaultOpExecutioner {
         }
 
         if (nativeOps.lastErrorCode() != 0)
-            throw new RuntimeException(nativeOps.lastErrorMessage());
+            throw new RuntimeException(nativeOps.lastErrorMessage() + " error code: " + nativeOps.lastErrorCode());
 
         profilingConfigurableHookOut(op, oc, st);
 

cavis-native/cavis-native-jcublas/src/main/java/org/nd4j/linalg/jcublas/ops/executioner/CudaOpContext.java

@@ -56,7 +56,8 @@ public class CudaOpContext extends BaseOpContext implements OpContext, Deallocat
 
     @Override
     public void close() {
-        // no-op
+        nativeOps.ctxPurge(context);
+        context.deallocate();
     }
 
     @Override