- new NDArray methods like()/ulike() (#77)

- fix for depthwise_conv2d_bp + special test

Signed-off-by: raver119 <raver119@gmail.com>

libnd4j/blas/NDArray.h

@@ -212,6 +212,20 @@ namespace nd4j {
         */
         NDArray(void *buffer, const char order, const std::vector<Nd4jLong> &shape,  nd4j::DataType dtype, nd4j::LaunchContext* context = nd4j::LaunchContext::defaultContext(), const bool isBuffAlloc = false);
 
+
+        /**
+        * This method returns new array with the same shape & data type
+        * @return
+        */
+        NDArray like();
+
+        /**
+         * This method returns new uninitialized array with the same shape & data type
+         * @return
+         */
+        NDArray ulike();
+
+
         /**
         *  this constructor creates new NDArray with shape matching "other" array,
         *  doesn't copy "other" elements into new array !!!

libnd4j/blas/NDArray.hpp

@@ -4129,6 +4129,19 @@ Nd4jLong NDArray::getOffset(const Nd4jLong i) const {
     return shape::getIndexOffset(i, _shapeInfo, lengthOf());
 }
 
+NDArray NDArray::like() {
+    NDArray res(this->shapeInfo(), this->dataType(), false, this->getContext());
+
+    return res;
+}
+
+NDArray NDArray::ulike() {
+    // FIXME: it should be non-memset array
+    NDArray res(this->shapeInfo(), this->dataType(), false, this->getContext());
+
+    return res;
+}
+
 ////////////////////////////////////////////////////////////////////////
 NDArray* NDArray::diagonal(const char type) const {
 

libnd4j/include/ops/declarable/helpers/cpu/convolutions.cpp

@@ -990,8 +990,9 @@ void ConvolutionUtils::getMKLDNNMemoryDescConv3d(
                 if(gradB->rankOf() == 2)
                     gradBR = new NDArray(gradB->reshape(gradB->ordering(), {(int)gradB->lengthOf()}));
                 gradO->reduceAlongDimension(reduce::Sum, gradBR, {0,indOoH,indOoH+1});                      // sum over bS, oH, oW
+
                 if(gradBR != gradB)
-                    delete gradB;
+                    delete gradBR;
             }
 
             //----- calculation of gradI -----//

libnd4j/tests_cpu/layers_tests/DeclarableOpsTests15.cpp

@@ -156,6 +156,21 @@ TEST_F(DeclarableOpsTests15, Test_standarize_bp_1) {
     delete result;
 }
 
+TEST_F(DeclarableOpsTests15, Test_depthwise_bp_1) {
+    auto in = NDArrayFactory::create<float>('c', {4, 8, 64, 64});
+    auto w = NDArrayFactory::create<float>('c', {2, 2, 8, 2});
+    auto b = NDArrayFactory::create<float>('c', {1, 16});
+    auto grad = NDArrayFactory::create<float>('c', {4, 16, 64, 64});
+
+    auto gradI = in.like();
+    auto gradW = w.like();
+    auto gradB = b.like();
+
+    nd4j:ops::depthwise_conv2d_bp op;
+    auto status = op.execute({&in, &w, &b, &grad}, {&gradI, &gradW, &gradB}, {}, {2, 2, 1, 1, 0, 0, 1, 1, 1, 0}, {});
+    ASSERT_EQ(Status::OK(), status);
+}
+
 TEST_F(DeclarableOpsTests15, test_matmul_bp_1) {
     auto a = NDArrayFactory::create<double>('c', {1, 3});
     auto b = NDArrayFactory::create<double>('c', {1, 4});