Shyrma reshape empty (#338)

* - start working on reshape op which operates with empty shapes

Signed-off-by: Yurii <iuriish@yahoo.com>

* - correct reshaping for empty arrays

Signed-off-by: Yurii <iuriish@yahoo.com>

* - remove unnecessary check in Loopkind

Signed-off-by: Yurii <iuriish@yahoo.com>

libnd4j/include/array/NDArray.hXX

@@ -1944,7 +1944,7 @@ void NDArray::tilei(const std::vector<Nd4jLong>& reps) {
 Nd4jLong NDArray::sizeAt(const int dim) const {
 
     if (dim >= this->rankOf() || dim < -this->rankOf())
-        throw std::runtime_error("Bad size index requested");
+        throw std::runtime_error("NDArray::sizeAt: bad size index requested");
 
     if (dim >= 0)
         return shape::shapeOf(_shapeInfo)[dim];

libnd4j/include/helpers/LoopKind.h

@@ -206,7 +206,7 @@ LoopKind::Kind LoopKind::deduceKindOfLoopTadXZ(const Nd4jLong* xShapeInfo, const
     const bool tVectorOrC = shape::isCommonVector(tadShapeInfo, temp) || tOrder == 'c';
     const bool zVectorOrC = shape::isCommonVector(zShapeInfo, temp)   || zOrder == 'c';;
 
-    if(shape::length(tadShapeInfo) * shape::length(zShapeInfo) <= Environment::getInstance()->elementwiseThreshold() && shape::rank(xShapeInfo) == 2 && xEws == 1 && xOrder == 'c' && xRank == 2 &&
+    if(shape::length(tadShapeInfo) * shape::length(zShapeInfo) <= Environment::getInstance()->elementwiseThreshold() && xEws == 1 && xOrder == 'c' && xRank == 2 &&
         tEws > 1 && zEws == 1 && (allC || (tVectorOrC && zVectorOrC)))
         return SMALLARR2DX;
     if(tEws == 1 && zEws == 1 && (allC || (tVectorOrC && zVectorOrC)))

libnd4j/include/ops/declarable/generic/shape/reshape.cpp

@@ -35,111 +35,19 @@ CUSTOM_OP_IMPL(reshape, 1, 1, false, 0, -2) {
     auto z = OUTPUT_VARIABLE(0);
 
     //Special case: empty.reshape(<other empty shape>) -> return empty
-        if (x->isEmpty()) {
+    if (x->isEmpty()) {
-            REQUIRE_TRUE(z->isEmpty(), 0, "Reshape: when input is empty, output must also be empty");
+        REQUIRE_TRUE(z->isEmpty(), 0, "Reshape: when input is empty, output must also be empty");
-            return Status::OK();    //No op
+        return Status::OK();    //No op
-        }
-
-    if (block.width() == 1) {
-
-        auto arguments = block.getIArguments();
-        int argsSize = arguments->size();
-
-
-
-        int e = 1;
-        char order = (char) -(*arguments)[0];
-        if (order != 'c' && order != 'f') {
-            order = 'c'; //x->ordering();
-            e = 0;
-        }
-
-        REQUIRE_TRUE(argsSize - e >= 1, 0, "Reshape arguments should have at least 1 dimension");
-
-        std::vector<Nd4jLong> shapeNew;
-        int e2 = e;
-        for (; e < (int) arguments->size(); e++) {
-            if (arguments->at(e) == -1){
-                Nd4jLong shapeLength = 1;
-                for(; e2 < e; e2++){
-                    shapeLength *= arguments->at(e2);
-                }
-                for(e2 = e + 1; e2 < arguments->size(); e2++){
-                    shapeLength *= arguments->at(e2);
-                }
-                Nd4jLong realShape = x->lengthOf() / shapeLength;
-                shapeNew.push_back(realShape);
-            }
-            else{
-                shapeNew.push_back(arguments->at(e));
-            }
-
-        }
-
-        auto len = shape::prodLong(shapeNew.data(), shapeNew.size());
-        REQUIRE_TRUE(len == x->lengthOf(), 0, "Reshape: lengths before and after reshape should match, but got %i vs %i", x->lengthOf(), len);
-
-        if (Environment::getInstance()->isDebugAndVerbose()) {
-            nd4j_printv("Reshape: new shape", shapeNew);
-        }
-
-        auto xr = x->reshape(order, shapeNew);
-        z->assign(xr);
-        STORE_RESULT(*z);
-
-        return Status::OK();
-
-    } else if (block.width() == 2) {
-
-        auto s = INPUT_VARIABLE(1);
-
-        char order = 'c';
-        if (block.numI() > 0)
-            order = (char) -INT_ARG(0);
-
-        std::vector<Nd4jLong> shapeNew(s->lengthOf());
-
-        for (int e = 0; e < (int) s->lengthOf(); e++) {
-            auto dim = s->e<Nd4jLong >(e);
-            if (dim == -1){
-                Nd4jLong shapeLength = 1;
-                for(int e2 = 0; e2 < e; e2++){
-                    shapeLength *= s->e<Nd4jLong>(e2);
-                }
-                for(int e2 = e + 1; e2 < (int) s->lengthOf(); e2++){
-                    REQUIRE_TRUE(s->e<Nd4jLong>(e2) != -1, 0, "Reshape : Only one unknown dimension (-1) is allowed.");
-                    shapeLength *= s->e<Nd4jLong>(e2);
-                }
-                Nd4jLong realShape = x->lengthOf() / shapeLength;
-                shapeNew[e] = realShape;
-            }
-            else{
-                shapeNew[e] = dim;
-            }
-        }
-
-        if (Environment::getInstance()->isDebugAndVerbose()) {
-            nd4j_printv("Reshape: new shape", shapeNew);
-        }
-
-        if (s->isScalar()) {
-            // just a scalar
-            z->assign(x);
-        } else {
-            // in some cases we might go away with simple memcpy call instead of assign call
-            if (x->ordering() == 'c' && z->ordering() == x->ordering() && shape::reshapeC(x->shapeInfo(), z->shapeInfo())) {
-                z->dataBuffer()->copyBufferFrom(*x->dataBuffer().get(), z->lengthOf() * DataTypeUtils::sizeOfElement(z->dataType()), 0, x->bufferOffset());
-            } else {
-                auto xr = x->reshape(order, shapeNew);
-                z->assign(xr);
-            }
-        }
-
-        return Status::OK();
-
     }
 
-    return ND4J_STATUS_BAD_INPUT;
+    REQUIRE_TRUE(x->lengthOf() == z->lengthOf(), 0, "Reshape: lengths before and after reshape should match, but got %i vs %i", x->lengthOf(), z->lengthOf());
+
+    if (Environment::getInstance()->isDebugAndVerbose())
+        nd4j_printv("Reshape: new shape", z->getShapeAsVector());
+
+    z->assign(x->reshape(z->ordering(), z->getShapeAsVector()));
+
+    return Status::OK();
 }
 
 
@@ -151,117 +59,73 @@ DECLARE_TYPES(reshape) {
 }
 
 DECLARE_SHAPE_FN(reshape) {
-    auto inp = inputShape->at(0);
 
-    // we can launch op using Int arguments
+    const auto x = INPUT_VARIABLE(0);
-    if (inputShape->size() == 1) {
-        REQUIRE_TRUE(block.numI() > 0, 0, "Reshape: new shape should be provided as NDArray or int arguments, but nothing was defined");
-        std::vector<int> *arguments = block.getIArguments();
 
-        int e = 1;
+    std::vector<int> reshapeArgs;
-        char order = (char) -(*arguments)[0];
+    std::vector<Nd4jLong> shapeNew;
-        if (order != 'c' && order != 'f') {
+    char orderNew = 'c';
-            order = shape::order(inp);
+
-            e = 0;
+    if (block.width() == 1) {
+        reshapeArgs = *block.getIArguments();
+        if(!reshapeArgs.empty()) {
+            orderNew = (char) -reshapeArgs[0];
+            if(orderNew == 'c' || orderNew == 'f')
+                reshapeArgs.erase(reshapeArgs.begin());   // remove first element being order in this case
         }
-
-        std::vector<Nd4jLong> shapeNew;
-
-        int e2 = e;
-        for (; e < (int) arguments->size(); e++) {
-            if ((int) arguments->at(e) == -1){
-
-                Nd4jLong shapeLength = 1;
-                for(; e2 < e; e2 ++){
-                    shapeLength *= arguments->at(e2);
-                }
-                for(e2 = e + 1; e2 < arguments->size(); e2++){
-                    REQUIRE_TRUE(arguments->at(e2) != -1, 0, "Reshape : Only one unknown dimension (-1) is allowed.");
-                    shapeLength *= arguments->at(e2);
-                }
-
-                if(shapeLength == 0){
-                    //Edge case for empty:
-                    shapeNew.push_back(0);
-                } else {
-                    //Standard case
-                    Nd4jLong realShape = shape::length(inp) / shapeLength;
-                    shapeNew.push_back(realShape);
-                }
-            }
-            else{
-                shapeNew.push_back(arguments->at(e));
-            }
-        }
-
-        return SHAPELIST(ConstantShapeHelper::getInstance()->createShapeInfo(ShapeDescriptor(ArrayOptions::dataType(inp), order, shapeNew)));
-    } else {
-        // or, with second input "as shape"
-        auto x = INPUT_VARIABLE(0);
-        auto y = INPUT_VARIABLE(1);
-
-        // special case here
-        if (y->isEmpty()) {
-            REQUIRE_TRUE(x->lengthOf() == 1, 0, "Reshape: new length doesn't match existing array");
-            return SHAPELIST(ConstantShapeHelper::getInstance()->scalarShapeInfo(ArrayOptions::dataType(inp)));
-        }
-        //Special case: empty.reshape(-1) -> return empty
-        if (x->isEmpty()) {
-            //REQUIRE_TRUE(y->lengthOf() == 1 && y->e<Nd4jLong>(0) == -1, 0, "Reshape: when input is empty, shape must be [-1]");
-            auto shapeOf = y->getBufferAsVector<Nd4jLong>();
-            Nd4jLong prod = 1;
-            bool hasNegs = false;
-            for (auto v:shapeOf) {
-                if (v < 0) {
-                    hasNegs = true;
-                    v = 0;
-                }
-
-                prod *= v;
-            }
-
-            REQUIRE_TRUE(prod == 0, 0, "Reshape: in case of empty arrays reshape must return empty array as well");
-
-            // if there are -1s - we turn them into zeros
-            if (hasNegs) {
-                for (int e = 0; e < shapeOf.size(); e++)
-                    if (shapeOf[e] < 0)
-                        shapeOf[e] = 0;
-            }
-
-            auto newShape = ShapeBuilders::createShapeInfo(ArrayOptions::dataType(inp), shape::order(inp), y->lengthOf(), shapeOf.data());
-            return SHAPELIST(CONSTANT(newShape));
-        }
-
-        std::vector<Nd4jLong> shapeNew(y->lengthOf());
-
-        for (int e = 0; e < (int) y->lengthOf(); e++) {
-            auto dim = y->e<Nd4jLong>(e);
-            if (dim == -1){
-                Nd4jLong shapeLength = 1;
-                for(int e2 = 0; e2 < e; e2++){
-                    shapeLength *= y->e<Nd4jLong>(e2);
-                }
-                for(int e2 = e + 1; e2 < (int)y->lengthOf(); e2++){
-                    REQUIRE_TRUE(y->e<Nd4jLong>(e2) != -1, 0, "Reshape : Only one unknown dimension (-1) is allowed.");
-                    shapeLength *= y->e<Nd4jLong>(e2);
-                }
-
-                if(shapeLength == 0){
-                    //Edge case for empty:
-                    shapeNew[e] = 0;
-                } else {
-                    Nd4jLong realShape = shape::length(inp) / shapeLength;
-                    shapeNew[e] = realShape;
-                }
-            }else {
-                shapeNew[e] = dim;
-            }
-        }
-
-        return SHAPELIST(ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inp), 'c', shapeNew));
     }
+    else {
+        reshapeArgs = INPUT_VARIABLE(1)->getBufferAsVector<int>();
+        orderNew = block.numI() > 0 ? (char) -INT_ARG(0) : 'c';
+    }
+
+    REQUIRE_TRUE(!reshapeArgs.empty() || x->lengthOf() == 1, 0, "Reshape buffer should have at least 1 dimension !");
+
+    Nd4jLong xLen = x->lengthOf();
+    if(x->isEmpty()) {
+        xLen = 1;
+        for (uint i = 0; i < x->rankOf(); ++i)                            // take into account possible empty shapes
+            if(x->sizeAt(i) != 0)
+                xLen *= x->sizeAt(i);
+    }
+
+    for (uint i = 0; i < reshapeArgs.size(); ++i) {
+
+        if (reshapeArgs[i] == -1) {
+
+            uint shapeLength = 1, numOfZeros = 0;
+
+            for(uint j = 0; j < i; ++j)
+                if(reshapeArgs[j] != 0)
+                    shapeLength *= reshapeArgs[j];
+                else
+                    ++numOfZeros;
+
+            for(uint j = i + 1; j < reshapeArgs.size(); ++j) {
+                REQUIRE_TRUE(reshapeArgs[j] != -1, 0, "Reshape : Only one unknown dimension (-1) is allowed.");
+                if(reshapeArgs[j] != 0)
+                    shapeLength *= reshapeArgs[j];
+                else
+                    ++numOfZeros;
+            }
+
+            const auto dim = xLen / shapeLength;
+
+            if(x->isEmpty() && (1 == dim || 0 == numOfZeros))
+                shapeNew.push_back(0);
+            else
+                shapeNew.push_back(dim);
+        }
+        else
+            shapeNew.push_back(reshapeArgs[i]);
+    }
+
+    auto len = shape::prodLong(shapeNew.data(), shapeNew.size());
+    REQUIRE_TRUE(x->lengthOf() == len, 0, "Reshape: lengths before and after reshape should match, but got %i vs %i", x->lengthOf(), len);
+
+    return SHAPELIST(ConstantShapeHelper::getInstance()->createShapeInfo(x->dataType(), orderNew, shapeNew));
 }
+
 }
 }
 

libnd4j/tests_cpu/layers_tests/ArrayOptionsTests.cpp

@@ -46,7 +46,6 @@ TEST_F(ArrayOptionsTests, TestShape_Basic_1) {
     ASSERT_TRUE(ArrayOptions::isSparseArray(shape));
 }
 
-
 TEST_F(ArrayOptionsTests, TestShape_Basic_2) {
     shape[5] = 258;
 

libnd4j/tests_cpu/layers_tests/DeclarableOpsTests1.cpp

@@ -1676,31 +1676,6 @@ TEST_F(DeclarableOpsTests1, ReverseDivideScalarScalar1) {
     delete block;
 }
 
-//////////////////////////////////////////////////////////////////////
-TEST_F(DeclarableOpsTests1, Reshapeas1) {
-    const std::vector<Nd4jLong> xShape = { 5,4,3 };
-    const std::vector<Nd4jLong> yShape = { 3,5,4 };
-
-    auto x = NDArrayFactory::create_<float>('f', xShape);
-    auto y = NDArrayFactory::create_<float>('f', yShape);
-
-
-    auto variableSpace = new VariableSpace();
-    variableSpace->putVariable(-1, x);
-    variableSpace->putVariable(-2, y);
-    auto block = new Context(1, variableSpace, true);
-    block->fillInputs({ -1, -2 });
-
-    sd::ops::reshapeas reshape;
-
-    reshape.execute(block);
-
-    ASSERT_TRUE(x->isSameShape(y));
-
-    delete variableSpace;
-    delete block;
-}
-
 TEST_F(DeclarableOpsTests1, Test_Cast_1) {
     // TODO: right now there's no real cast implementation, but genera idea should be the same: arrays equality to be expected
     auto x = NDArrayFactory::create<float>('c', { 5, 5 });
@@ -1848,113 +1823,6 @@ TEST_F(DeclarableOpsTests1, TestGemv1) {
 
 #endif
 
-//////////////////////////////////////////////////////////////////////
-TEST_F(DeclarableOpsTests1, Reshape2) {
-    const std::vector<Nd4jLong> xShape = { 5,4,3 };
-    const std::vector<Nd4jLong> yShape = { 3,5,4 };
-
-    auto x = NDArrayFactory::create_<float>('c', xShape);
-    auto y = NDArrayFactory::create_<float>('c', yShape);
-
-    auto variableSpace = new VariableSpace();
-    variableSpace->putVariable(-1, x);
-    variableSpace->putVariable(1, new Variable());
-
-    auto block = new Context(1, variableSpace, false);
-    block->fillInputs({ -1 });
-    std::vector<int>* arguments = block->getIArguments();
-    arguments->push_back(-y->ordering());
-    arguments->push_back(3);
-    arguments->push_back(5);
-    arguments->push_back(4);
-
-    sd::ops::reshape reshape;
-
-    Nd4jStatus status = reshape.execute(block);
-    ASSERT_EQ(ND4J_STATUS_OK, status);
-    auto result = variableSpace->getVariable(block->getNodeId())->getNDArray();
-
-    ASSERT_TRUE(result->isSameShape(y));
-
-    delete y;
-    delete block;
-    delete variableSpace;
-}
-
-TEST_F(DeclarableOpsTests1, Reshape3) {
-    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({ &x }, {}, { -99, 3, 4, 5 });
-
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(x.isSameShape(z));
-
-    
-}
-
-TEST_F(DeclarableOpsTests1, Reshape4) {
-    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({ &x }, {}, { 3, 4, 5 });
-
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(x.isSameShape(z));
-
-    
-}
-
-TEST_F(DeclarableOpsTests1, Reshape5) {
-    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({ &x }, {}, { 5, 4, 3 });
-
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    
-}
-
-TEST_F(DeclarableOpsTests1, Reshape6) {
-    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
-    auto exp = NDArrayFactory::create<float>('c', { 4, 15 });
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({ &x }, {}, { 4, -1 });
-
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(z->isSameShape(exp));
-
-    
-
-}
-
-TEST_F(DeclarableOpsTests1, Reshape7) {
-    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
-    auto exp = NDArrayFactory::create<float>('c', { 60 });
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({ &x }, {}, { -1 });
-
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(z->isSameShape(exp));
-
-    
-
-}
 
 //////////////////////////////////////////////////////////////////////
 TEST_F(DeclarableOpsTests1, Transpose1) {
@@ -1983,7 +1851,6 @@ TEST_F(DeclarableOpsTests1, Transpose1) {
     delete variableSpace;
 }
 
-
 //////////////////////////////////////////////////////////////////////
 // not-in-place
 TEST_F(DeclarableOpsTests1, Permute1) {

libnd4j/tests_cpu/layers_tests/DeclarableOpsTests14.cpp

@@ -52,22 +52,6 @@ TEST_F(DeclarableOpsTests14, Test_Validation_Edge_1) {
     ASSERT_EQ(exp, *z);
 
 
-}
-
-TEST_F(DeclarableOpsTests14, Test_Reshape_CF_1) {
-    auto x = NDArrayFactory::create<double>('f', {2, 3}, {1.0, 4.0, 2.0, 5.0, 3.0, 6.0});
-    auto e = NDArrayFactory::create<double>('f', {3, 2}, {1.0, 3.0, 5.0, 2.0, 4.0, 6.0});
-
-    auto r = x.reshape('c', {3, 2});;
-    r.streamline('f');
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&x}, {3, 2});
-    ASSERT_EQ(Status::OK(), result.status());
-
-    auto z = result.at(0);
-
-    
 }
 
 TEST_F(DeclarableOpsTests14, Test_Inf_Comparison_1) {
@@ -2073,7 +2057,363 @@ TEST_F(DeclarableOpsTests14, Stack_21) {
 
     ASSERT_TRUE(outStack->isSameShape(outConcat));
     ASSERT_TRUE(outStack->equalsTo(outConcat));
+}
+
+//////////////////////////////////////////////////////////////////////
+TEST_F(DeclarableOpsTests14, Reshape1) {
+    const std::vector<Nd4jLong> xShape = { 5,4,3 };
+    const std::vector<Nd4jLong> yShape = { 3,5,4 };
+
+    auto x = NDArrayFactory::create_<float>('f', xShape);
+    auto y = NDArrayFactory::create_<float>('f', yShape);
+
+
+    auto variableSpace = new VariableSpace();
+    variableSpace->putVariable(-1, x);
+    variableSpace->putVariable(-2, y);
+    auto block = new Context(1, variableSpace, true);
+    block->fillInputs({ -1, -2 });
+
+    sd::ops::reshapeas reshape;
+
+    reshape.execute(block);
+
+    ASSERT_TRUE(x->isSameShape(y));
+
+    delete variableSpace;
+    delete block;
+}
+
+//////////////////////////////////////////////////////////////////////
+TEST_F(DeclarableOpsTests14, Reshape2) {
+    const std::vector<Nd4jLong> xShape = { 5,4,3 };
+    const std::vector<Nd4jLong> yShape = { 3,5,4 };
+
+    auto x = NDArrayFactory::create_<float>('c', xShape);
+    auto y = NDArrayFactory::create_<float>('c', yShape);
+
+    auto variableSpace = new VariableSpace();
+    variableSpace->putVariable(-1, x);
+    variableSpace->putVariable(1, new Variable());
+
+    auto block = new Context(1, variableSpace, false);
+    block->fillInputs({ -1 });
+    std::vector<int>* arguments = block->getIArguments();
+    arguments->push_back(-y->ordering());
+    arguments->push_back(3);
+    arguments->push_back(5);
+    arguments->push_back(4);
+
+    sd::ops::reshape reshape;
+
+    Nd4jStatus status = reshape.execute(block);
+    ASSERT_EQ(ND4J_STATUS_OK, status);
+    auto result = variableSpace->getVariable(block->getNodeId())->getNDArray();
+
+    ASSERT_TRUE(result->isSameShape(y));
+
+    delete y;
+    delete block;
+    delete variableSpace;
+}
+
+TEST_F(DeclarableOpsTests14, Reshape3) {
+    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({ &x }, {}, { -99, 3, 4, 5 });
+
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(x.isSameShape(z));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape4) {
+    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({ &x }, {}, { 3, 4, 5 });
+
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(x.isSameShape(z));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape5) {
+    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({ &x }, {}, { 5, 4, 3 });
+
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+}
+
+TEST_F(DeclarableOpsTests14, Reshape6) {
+    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
+    auto exp = NDArrayFactory::create<float>('c', { 4, 15 });
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({ &x }, {}, { 4, -1 });
+
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(z->isSameShape(exp));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape7) {
+    auto x = NDArrayFactory::create<float>('c', { 3, 4, 5 });
+    auto exp = NDArrayFactory::create<float>('c', { 60 });
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({ &x }, {}, { -1 });
+
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(z->isSameShape(exp));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape8) {
+    auto x = NDArrayFactory::create<double>('f', {2, 3}, {1.0, 4.0, 2.0, 5.0, 3.0, 6.0});
+    auto e = NDArrayFactory::create<double>('f', {3, 2}, {1.0, 3.0, 5.0, 2.0, 4.0, 6.0});
+
+    auto r = x.reshape('c', {3, 2});;
+    r.streamline('f');
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&x}, {3, 2});
+    ASSERT_EQ(Status::OK(), result.status());
+
+    auto z = result.at(0);
+}
+
+TEST_F(DeclarableOpsTests14, Reshape9) {
+    auto array = NDArrayFactory::create<float>(119.f);
+    auto e = NDArrayFactory::create<float>('c', {1, 1}, {119.f});
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&array}, {}, {1, 1});
+    ASSERT_EQ(Status::OK(), result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_EQ(e, *z);
+}
+
+TEST_F(DeclarableOpsTests14, Reshape10) {
+    auto array = NDArrayFactory::create<float>(119.f);
+    auto e = NDArrayFactory::create<float>('c', {1, 1}, {119.f});
+    auto z = NDArrayFactory::create<float>('c', {1, 1});
+
+    sd::ops::reshape op;
+    auto result = op.execute({&array}, {&z}, {}, {1, 1}, {});
+    ASSERT_EQ(Status::OK(), result);
+    ASSERT_EQ(e, z);
+}
+
+TEST_F(DeclarableOpsTests14, Reshape11) {
+    auto x = NDArrayFactory::create<double>('c', {4, 3});
+    auto exp = NDArrayFactory::create<double>('c', {4, 3});
+
+    x.linspace(1);
+    exp.linspace(1);
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&x}, {-99, 4, 3});
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(exp.isSameShape(z));
+    ASSERT_TRUE(exp.equalsTo(z));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape12) {
+    auto x = NDArrayFactory::create<double>('c', {2, 2, 2}, {1, 2, 3, 4, 5, 6, 7, 8});
+    auto shape = NDArrayFactory::create<Nd4jLong>('c', {2}, {-1, 2});
+    auto exp = NDArrayFactory::create<double>('c', {4, 2}, {1, 2, 3, 4, 5, 6, 7, 8});
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&x, &shape});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(exp.isSameShape(z));
+    ASSERT_TRUE(exp.equalsTo(z));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape13) {
+    auto vector = NDArrayFactory::create<float>('c', {1}, {119.0f});
+    auto exp = NDArrayFactory::create<float>(119.f);
+    auto empty = NDArrayFactory::empty_<int>();
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&vector, empty}, {}, {});
+
+    ASSERT_EQ(Status::OK(), result.status());
+
+    ASSERT_EQ(exp, *result.at(0));
+
+    delete empty;
+}
+
+TEST_F(DeclarableOpsTests14, Reshape14) {
+    auto x = NDArrayFactory::create<float>('c', {1, 0, 0, 2});
+    auto y = NDArrayFactory::create<int>('c', {2}, {10, 0});
+    auto e = NDArrayFactory::create<float>('c', {10, 0});
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&x, &y}, {}, {});
+    ASSERT_EQ(Status::OK(), result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(e.isSameShape(z));
+    ASSERT_EQ(e, *z);
 
 }
 
+TEST_F(DeclarableOpsTests14, Reshape15) {
 
+    auto x0 = NDArrayFactory::create<float>('c', {2, 0});
+    auto x1 = NDArrayFactory::create<float>('c', {0, 1, 2});
+
+    auto shape0 = NDArrayFactory::create<Nd4jLong>('c', {3}, {2, 0, -1});
+    auto shape1 = NDArrayFactory::create<Nd4jLong>('c', {2}, {-1, 1});
+
+    auto e0 = NDArrayFactory::create<float>('c', {2, 0, 0});
+    auto e1 = NDArrayFactory::create<float>('c', {0, 1});
+
+    sd::ops::reshape op;
+    auto result0 = op.evaluate({&x0, &shape0}, {}, {});
+    ASSERT_EQ(Status::OK(), result0.status());
+    auto z0 = result0.at(0);
+    ASSERT_EQ(e0, *z0);
+
+    auto result1 = op.evaluate({&x1, &shape1}, {}, {});
+    ASSERT_EQ(Status::OK(), result1.status());
+    auto z1 = result1.at(0);
+    ASSERT_EQ(e1, *z1);
+}
+
+TEST_F(DeclarableOpsTests14, Reshape16) {
+    auto x = NDArrayFactory::create<int>('c', {2, 2}, {1, 2, 3, 4});
+    auto shape = NDArrayFactory::create<int>('c', {1, 3}, {1, 2, 2});
+
+    auto exp = NDArrayFactory::create<int>('c', {1, 2, 2}, {1, 2, 3, 4});
+
+    sd::ops::reshape op;
+
+    auto result = op.evaluate({&x, &shape}, {}, {});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(exp.isSameShape(z));
+    ASSERT_TRUE(exp.equalsTo(z));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape17) {
+    auto x = NDArrayFactory::create<float>(2.0f);
+    auto exp = NDArrayFactory::create<float>('c', {1, 1, 1}, {2.0f});
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&x}, {}, {-99, 1, 1, 1});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(exp.isSameShape(z));
+    ASSERT_TRUE(exp.equalsTo(z));
+}
+
+TEST_F(DeclarableOpsTests14, Reshape18) {
+    auto x = NDArrayFactory::create<float>('c', {1, 3}, {1, 2, 3});
+    auto exp = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&x}, {}, {-99, 3});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(exp.isSameShape(z));
+    ASSERT_TRUE(exp.equalsTo(z));
+
+
+}
+
+TEST_F(DeclarableOpsTests14, Reshape19) {
+    auto x = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});
+    auto exp = NDArrayFactory::create<float>('c', {1, 3}, {1, 2, 3});
+
+    sd::ops::reshape op;
+    auto result = op.evaluate({&x}, {}, {-99, 1, 3});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+
+    auto z = result.at(0);
+
+    ASSERT_TRUE(exp.isSameShape(z));
+    ASSERT_TRUE(exp.equalsTo(z));
+}
+
+
+TEST_F(DeclarableOpsTests14, Reshape20) {
+
+    NDArray x1('c', {2,0}, sd::DataType::FLOAT32);
+    NDArray x2('c', {10,0}, sd::DataType::FLOAT32);
+    NDArray x3('c', {2,0,0,10}, sd::DataType::FLOAT32);
+    NDArray x4('c', {0,0,10}, sd::DataType::FLOAT32);
+    NDArray x5('c', {0,2,10}, sd::DataType::FLOAT32);
+    NDArray x6('c', {0,10,0}, sd::DataType::FLOAT32);
+    NDArray x7('c', {0,1,2}, sd::DataType::FLOAT32);
+
+    sd::ops::reshape op;
+
+    auto result = op.evaluate({&x1}, {}, {2, -1});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({2,0}));
+
+    result = op.evaluate({&x2}, {}, {2, 0, -1});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({2,0,5}));
+
+    result = op.evaluate({&x2}, {}, {5, 2, -1});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({5,2,0}));
+
+    result = op.evaluate({&x2}, {}, {-1, 2, 0});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({5,2,0}));
+
+    result = op.evaluate({&x3}, {}, {2, 0, -1});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({2,0,10}));
+
+    result = op.evaluate({&x4}, {}, {2, -1, 0});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({2,5,0}));
+
+    result = op.evaluate({&x5}, {}, {2, 0, 0, 0, -1});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({2,0,0,0,10}));
+
+    result = op.evaluate({&x6}, {}, {-1, 2, 0});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({5, 2, 0}));
+
+    result = op.evaluate({&x7}, {}, {-1, 0});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({2, 0}));
+
+    result = op.evaluate({&x7}, {}, {10,0,50,100});
+    ASSERT_EQ(ND4J_STATUS_OK, result.status());
+    ASSERT_TRUE(result.at(0)->isSameShape({10,0,50,100}));
+}

libnd4j/tests_cpu/layers_tests/DeclarableOpsTests15.cpp

@@ -710,30 +710,6 @@ TEST_F(DeclarableOpsTests15, test_hashCode_2) {
     ASSERT_NE(*resultA0.at(0), *resultB0.at(0));
 }
 
-TEST_F(DeclarableOpsTests15, test_reshape_to_scalar_1) {
-    auto array = NDArrayFactory::create<float>(119.f);
-    auto e = NDArrayFactory::create<float>('c', {1, 1}, {119.f});
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&array}, {}, {1, 1});
-    ASSERT_EQ(Status::OK(), result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_EQ(e, *z);
-}
-
-TEST_F(DeclarableOpsTests15, test_reshape_to_scalar_2) {
-    auto array = NDArrayFactory::create<float>(119.f);
-    auto e = NDArrayFactory::create<float>('c', {1, 1}, {119.f});
-    auto z = NDArrayFactory::create<float>('c', {1, 1});
-
-    sd::ops::reshape op;
-    auto result = op.execute({&array}, {&z}, {}, {1, 1}, {});
-    ASSERT_EQ(Status::OK(), result);
-    ASSERT_EQ(e, z);
-}
-
 TEST_F(DeclarableOpsTests15, test_rank_1) {
     auto array = NDArrayFactory::create<float>('c', {4, 64});
     auto e = NDArrayFactory::create<int>('c', {}, {2});

libnd4j/tests_cpu/layers_tests/DeclarableOpsTests4.cpp

@@ -789,24 +789,6 @@ TEST_F(DeclarableOpsTests4, Test_FloorTests_1) {
     ASSERT_TRUE(exp.equalsTo(z));
 
 
-}
-
-TEST_F(DeclarableOpsTests4, Test_Reshape_Again) {
-    auto x = NDArrayFactory::create<double>('c', {4, 3});
-    auto exp = NDArrayFactory::create<double>('c', {4, 3});
-
-    x.linspace(1);
-    exp.linspace(1);
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&x}, {-99, 4, 3});
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(exp.isSameShape(z));
-    ASSERT_TRUE(exp.equalsTo(z));
-
-
 }
 
 TEST_F(DeclarableOpsTests4, Test_Split_1) {
@@ -1209,23 +1191,6 @@ TEST_F(DeclarableOpsTests4, Test_Add_119) {
     ASSERT_TRUE(exp.equalsTo(z));
 
 
-}
-
-TEST_F(DeclarableOpsTests4, Test_Reshape_Negative_1) {
-    auto x = NDArrayFactory::create<double>('c', {2, 2, 2}, {1, 2, 3, 4, 5, 6, 7, 8});
-    auto shape = NDArrayFactory::create<Nd4jLong>('c', {2}, {-1, 2});
-    auto exp = NDArrayFactory::create<double>('c', {4, 2}, {1, 2, 3, 4, 5, 6, 7, 8});
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&x, &shape});
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(exp.isSameShape(z));
-    ASSERT_TRUE(exp.equalsTo(z));
-
-
 }
 
 TEST_F(DeclarableOpsTests4, Test_TileToShape_1) {

libnd4j/tests_cpu/layers_tests/EmptyTests.cpp

@@ -140,37 +140,6 @@ TEST_F(EmptyTests, Test_Concat_4) {
     ASSERT_EQ(exp, *z);
 }
 
-TEST_F(EmptyTests, Test_Reshape_1) {
-    auto vector = NDArrayFactory::create<float>('c', {1}, {119.0f});
-    auto exp = NDArrayFactory::create<float>(119.f);
-    auto empty = NDArrayFactory::empty_<int>();
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&vector, empty}, {}, {});
-
-    ASSERT_EQ(Status::OK(), result.status());
-
-    ASSERT_EQ(exp, *result.at(0));
-
-    delete empty;
-}
-
-TEST_F(EmptyTests, Test_Reshape_3) {
-    auto x = NDArrayFactory::create<float>('c', {1, 0, 0, 2});
-    auto y = NDArrayFactory::create<int>('c', {2}, {10, 0});
-    auto e = NDArrayFactory::create<float>('c', {10, 0});
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&x, &y}, {}, {});
-    ASSERT_EQ(Status::OK(), result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(e.isSameShape(z));
-    ASSERT_EQ(e, *z);
-
-}
-
 TEST_F(EmptyTests, Test_dup_1) {
     auto empty = NDArrayFactory::empty<int>();
     auto dup = new NDArray(empty.dup());
@@ -256,41 +225,6 @@ TEST_F(EmptyTests, test_shaped_empty_4) {
     ASSERT_EQ(shapeOf, array.getShapeAsVector());
 }
 
-TEST_F(EmptyTests, test_empty_reshape_1) {
-    /*
-    INDArray arr0 = Nd4j.create(DataType.FLOAT, 2, 0);
-    INDArray arr1 = Nd4j.create(DataType.FLOAT, 0, 1, 2);
-
-    INDArray out0 = Nd4j.exec(new Reshape(arr0, Nd4j.createFromArray(2, 0, -1), Nd4j.create(DataType.FLOAT, 2, 0, 0)))[0];
-    INDArray out1 = Nd4j.exec(new Reshape(arr1, Nd4j.createFromArray(-1, 1), Nd4j.create(DataType.FLOAT, 0, 1)))[0];
-    INDArray out2 = Nd4j.exec(new Reshape(arr1, Nd4j.createFromArray(10, -1), Nd4j.create(DataType.FLOAT, 10, 0)))[0];
-
-    assertArrayEquals(new long[]{2, 0, 0}, out0.shape());
-    assertArrayEquals(new long[]{0, 1}, out1.shape());
-    assertArrayEquals(new long[]{10, 0}, out2.shape());
-     */
-    auto x0 = NDArrayFactory::create<float>('c', {2, 0});
-    auto x1 = NDArrayFactory::create<float>('c', {0, 1, 2});
-
-    auto shape0 = NDArrayFactory::create<Nd4jLong>('c', {3}, {2, 0, -1});
-    auto shape1 = NDArrayFactory::create<Nd4jLong>('c', {2}, {-1, 1});
-
-    auto e0 = NDArrayFactory::create<float>('c', {2, 0, 0});
-    auto e1 = NDArrayFactory::create<float>('c', {0, 1});
-
-    sd::ops::reshape op;
-    auto result0 = op.evaluate({&x0, &shape0}, {}, {});
-    ASSERT_EQ(Status::OK(), result0.status());
-    auto z0 = result0.at(0);
-    ASSERT_EQ(e0, *z0);
-
-    auto result1 = op.evaluate({&x1, &shape1}, {}, {});
-    ASSERT_EQ(Status::OK(), result1.status());
-    auto z1 = result1.at(0);
-    ASSERT_EQ(e1, *z1);
-
-}
-
 
 TEST_F(EmptyTests, test_empty_matmul_1) {
     auto x = NDArrayFactory::create<float>('c', {0, 1});

libnd4j/tests_cpu/layers_tests/ParityOpsTests.cpp

@@ -669,24 +669,6 @@ TEST_F(ParityOpsTests, Test_Select_3) {
 
 }
 
-TEST_F(ParityOpsTests, Test_Reshape_TF_1) {
-    auto x = NDArrayFactory::create<int>('c', {2, 2}, {1, 2, 3, 4});
-    auto shape = NDArrayFactory::create<int>('c', {1, 3}, {1, 2, 2});
-
-    auto exp = NDArrayFactory::create<int>('c', {1, 2, 2}, {1, 2, 3, 4});
-
-    sd::ops::reshape op;
-
-    auto result = op.evaluate({&x, &shape}, {}, {});
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(exp.isSameShape(z));
-    ASSERT_TRUE(exp.equalsTo(z));
-    
-}
-
 TEST_F(ParityOpsTests, Test_Bias_Add_1) {
     auto x = NDArrayFactory::create<float>('c', {10, 5});
     x.assign(0.0);

libnd4j/tests_cpu/layers_tests/ScalarTests.cpp

@@ -182,24 +182,6 @@ TEST_F(ScalarTests, Test_Squeeze_1) {
 
 }
 
-
-TEST_F(ScalarTests, Test_Reshape_1) {
-    auto x = NDArrayFactory::create<float>(2.0f);
-    auto exp = NDArrayFactory::create<float>('c', {1, 1, 1}, {2.0f});
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&x}, {}, {-99, 1, 1, 1});
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(exp.isSameShape(z));
-    ASSERT_TRUE(exp.equalsTo(z));
-
-    
-}
-
-
 TEST_F(ScalarTests, Test_Permute_1) {
     auto x = NDArrayFactory::create<float>(3.0f);
     auto exp = NDArrayFactory::create<float>(3.0f);

libnd4j/tests_cpu/layers_tests/SingleDimTests.cpp

@@ -168,39 +168,6 @@ TEST_F(SingleDimTests, Test_Squeeze_2) {
 
 }
 
-TEST_F(SingleDimTests, Test_Reshape_1) {
-    auto x = NDArrayFactory::create<float>('c', {1, 3}, {1, 2, 3});
-    auto exp = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&x}, {}, {-99, 3});
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(exp.isSameShape(z));
-    ASSERT_TRUE(exp.equalsTo(z));
-
-    
-}
-
-TEST_F(SingleDimTests, Test_Reshape_2) {
-    auto x = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});
-    auto exp = NDArrayFactory::create<float>('c', {1, 3}, {1, 2, 3});
-
-    sd::ops::reshape op;
-    auto result = op.evaluate({&x}, {}, {-99, 1, 3});
-    ASSERT_EQ(ND4J_STATUS_OK, result.status());
-
-    auto z = result.at(0);
-
-    ASSERT_TRUE(exp.isSameShape(z));
-    ASSERT_TRUE(exp.equalsTo(z));
-
-    
-}
-
-
 TEST_F(SingleDimTests, Test_Permute_1) {
     auto x = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});
     auto exp = NDArrayFactory::create<float>('c', {3}, {1, 2, 3});