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Improve ResultSet usage in libnd4j (#281) 

* libnd4j profiling DeclarableOp and Tests by replacing return ResultSet pointer by instance

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j profiling semantic change in tests cases

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j some corrections to make new ResultSet semantic works, fixed one test

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* libnd4j more tests fixes

Signed-off-by: Oleg <oleg.semeniv@gmail.com>

* - correct copy and move assignment operators of ResultSet class

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

Co-authored-by: Yurii <iuriish@yahoo.com>
Co-authored-by: raver119 <raver119@gmail.com>
master
Oleh 2020-03-10 06:42:50 +02:00 committed by GitHub
parent 57210b936c
commit c3223dbc7a
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
55 changed files with 6726 additions and 7658 deletions
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2
libnd4j/include/array/ResultSet.h
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@ -40,6 +40,8 @@ namespace sd {
Nd4jStatus _status = ND4J_STATUS_OK;
bool _removable = true;
void delContent();
public:
explicit ResultSet();

4
libnd4j/include/array/impl/NDArrayList.cpp
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@ -160,9 +160,7 @@ namespace sd {
auto result = op.evaluate(inputs);
auto array = new NDArray(result->at(0)->dup());
delete result;
auto array = new NDArray(result.at(0)->dup());
return array;
}

21
libnd4j/include/array/impl/ResultSet.cpp
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@ -77,15 +77,16 @@ namespace sd {
}
////////////////////////////////////////////////////////////////////////
// move assignment operator
// move assignment operator
ResultSet& ResultSet::operator=(ResultSet&& other) noexcept {
if (this == &other)
return *this;
this->~ResultSet();
delContent();
_content = std::move(other._content);
_status = other._status;
_removable = other._removable;
other._removable = false;
@ -98,10 +99,10 @@ namespace sd {
if (this == &other)
return *this;
this->~ResultSet();
delContent();
for (const auto v:other._content)
_content.emplace_back(v);
for (const auto v : other._content)
_content.push_back(v);
_status = other._status;
_removable = false;
@ -109,11 +110,15 @@ namespace sd {
return *this;
}
void ResultSet::delContent() {
if (_removable)
for (auto v : _content)
delete v;
}
ResultSet::~ResultSet() {
if (_removable)
for (auto v: _content)
delete v;
delContent();
}
void ResultSet::setNonRemovable() {

20
libnd4j/include/helpers/impl/GradCheck.cpp
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@ -60,7 +60,7 @@ bool GradCheck::checkGrad(ops::DeclarableOp& opFF, ops::DeclarableOp& opBP, cons
fillGradArrays(loss, std::vector<NDArray*>(&inArrsBP[numInArrsFF], &inArrsBP[numInArrsFF + numInGradArrsBP]));
// back prop pass
ResultSet* outArrsBP = opBP.execute(argsHolderBP); // number of output arrays in back prop = numInArrsFF;
ResultSet outArrsBP = opBP.execute(argsHolderBP); // number of output arrays in back prop = numInArrsFF;
NDArray tmpScalar(sd::DataType::DOUBLE, inArrsFF[0]->getContext()); // scalar = 0
@ -78,18 +78,17 @@ bool GradCheck::checkGrad(ops::DeclarableOp& opFF, ops::DeclarableOp& opBP, cons
// add epsilon, feed forward
inArrsFF[i]->p<double>(j, orig + EPSILON);
ResultSet* outArrsFF = opFF.execute(argsHolderFF);
int numOutArrs = outArrsFF->size();
ResultSet outArrsFF = opFF.execute(argsHolderFF);
int numOutArrs = outArrsFF.size();
double scorePlus = 0.;
for(int k = 0; k < numOutArrs; ++k) { // loop through output arrays
if(loss == SUM)
outArrsFF->at(k)->reduceNumber(reduce::Sum, tmpScalar);
outArrsFF.at(k)->reduceNumber(reduce::Sum, tmpScalar);
else
outArrsFF->at(k)->reduceNumber(reduce::Mean, tmpScalar);
outArrsFF.at(k)->reduceNumber(reduce::Mean, tmpScalar);
scorePlus += tmpScalar.e<double>(0);
}
delete outArrsFF;
// subtract epsilon, feed forward
inArrsFF[i]->p<double>(j, orig - EPSILON);
@ -98,12 +97,11 @@ bool GradCheck::checkGrad(ops::DeclarableOp& opFF, ops::DeclarableOp& opBP, cons
for(int k = 0; k < numOutArrs; ++k) { // loop through output arrays
if(loss == SUM)
outArrsFF->at(k)->reduceNumber(reduce::Sum, tmpScalar);
outArrsFF.at(k)->reduceNumber(reduce::Sum, tmpScalar);
else
outArrsFF->at(k)->reduceNumber(reduce::Mean, tmpScalar);
outArrsFF.at(k)->reduceNumber(reduce::Mean, tmpScalar);
scoreMinus += tmpScalar.e<double>(0);
}
delete outArrsFF;
// restore initial element value
inArrsFF[i]->p<double>(j, orig);
@ -116,7 +114,7 @@ bool GradCheck::checkGrad(ops::DeclarableOp& opFF, ops::DeclarableOp& opBP, cons
}
// get analytical gradient
const double analyticGrad = outArrsBP->at(i)->e<double>(j);
const double analyticGrad = outArrsBP.at(i)->e<double>(j);
if(std::isnan(analyticGrad) || std::isinf(analyticGrad)) {
printf("GradCheck::checkGrad: got wrong value for analytical gradient for input array # %i and its element at position %lld ! \n", i, j);
throw std::runtime_error("");
@ -138,13 +136,11 @@ bool GradCheck::checkGrad(ops::DeclarableOp& opFF, ops::DeclarableOp& opBP, cons
continue;
printf("numericalGrad = %f, analyticGrad = %f \n", numericalGrad, analyticGrad);
printf("GradCheck::checkGrad: got RELERROR = %f > MAXRELERROR(%f) for input array # %i and its element at position %lld ! \n", relError, MAXRELERR, i, j);
delete outArrsBP;
return false;
}
}
}
delete outArrsBP;
return true;
}

4
libnd4j/include/ops/declarable/DeclarableListOp.h
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@ -45,8 +45,8 @@ namespace sd {
Nd4jStatus execute(Context* block) override;
ResultSet* execute(NDArrayList* list, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs);
ResultSet* execute(NDArrayList* list, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs);
ResultSet execute(NDArrayList* list, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs);
ResultSet execute(NDArrayList* list, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs);
ShapeList* calculateOutputShape(ShapeList* inputShape, sd::graph::Context& block) override;
};

10
libnd4j/include/ops/declarable/DeclarableOp.h
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@ -176,17 +176,17 @@ namespace sd {
Nd4jStatus execute(const std::vector<NDArray*> &inputs, const std::vector<NDArray*> &outputs, const std::vector<double> &tArgs, const std::vector<Nd4jLong> &iArgs, const std::vector<bool> &bArgs = std::vector<bool>(), const std::vector<sd::DataType> &dArgs = std::vector<sd::DataType>(), bool isInplace = false);
sd::ResultSet* evaluate(const std::vector<NDArray*> &inputs);
sd::ResultSet evaluate(const std::vector<NDArray*> &inputs);
template <class T, typename = std::enable_if<DataTypeUtils::scalarTypesForExecution<T>::value>>
sd::ResultSet* evaluate(const std::vector<NDArray*> &inputs, std::initializer_list<T> args);
sd::ResultSet evaluate(const std::vector<NDArray*> &inputs, std::initializer_list<T> args);
sd::ResultSet* evaluate(const std::vector<NDArray*> &inputs, const std::vector<double> &tArgs, const std::vector<Nd4jLong> &iArgs, const std::vector<bool> &bArgs = std::vector<bool>(), const std::vector<sd::DataType> &dArgs = std::vector<sd::DataType>(), bool isInplace = false);
sd::ResultSet evaluate(const std::vector<NDArray*> &inputs, const std::vector<double> &tArgs, const std::vector<Nd4jLong> &iArgs, const std::vector<bool> &bArgs = std::vector<bool>(), const std::vector<sd::DataType> &dArgs = std::vector<sd::DataType>(), bool isInplace = false);
Nd4jStatus execute(sd::graph::RandomGenerator& rng, const std::vector<NDArray*>& inputs, const std::vector<NDArray*>& outputs, const std::vector<double>& tArgs, const std::vector<Nd4jLong>& iArgs, const std::vector<bool>& bArgs, const std::vector<sd::DataType> &dArgs = std::vector<sd::DataType>(), bool isInplace = false, sd::DataType type = sd::DataType::FLOAT32);
sd::ResultSet* execute(const sd::OpArgsHolder& holder, bool isInplace = false);
sd::ResultSet execute(const sd::OpArgsHolder& holder, bool isInplace = false);
// There methods provide various validation options
Nd4jStatus validateNonEmptyInput(Context& block);

5
libnd4j/include/ops/declarable/LegacyRandomOp.h
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@ -41,8 +41,9 @@ namespace sd {
template <typename T>
Nd4jStatus validateAndExecute_(Context &block);
sd::ResultSet* execute(sd::graph::RandomGenerator& rng, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs, bool isInplace = false);
sd::ResultSet* execute(sd::graph::RandomGenerator& rng, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs, bool isInplace = false);
sd::ResultSet execute(sd::graph::RandomGenerator& rng, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs, bool isInplace = false);
sd::ResultSet execute(sd::graph::RandomGenerator& rng, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs, bool isInplace = false);
Nd4jStatus execute(Context* block) override;
ShapeList* calculateOutputShape(ShapeList* inputShape, sd::graph::Context& block) override;

16
libnd4j/include/ops/declarable/generic/activations/crelu.cpp
View File

@ -74,10 +74,10 @@ namespace sd {
// at first step we build fwd activation
sd::ops::crelu op;
auto tmpResult = op.evaluate({input});
if (tmpResult->status() != ND4J_STATUS_OK)
return tmpResult->status();
if (tmpResult.status() != ND4J_STATUS_OK)
return tmpResult.status();
auto actv = tmpResult->at(0);
auto actv = tmpResult.at(0);
// now we do RELU backward pass
//actv->applyPairwiseTransform(pairwise::RELUDerivativeE, *epsilon, nullptr);
@ -85,17 +85,15 @@ namespace sd {
// now we split updated array into 2 chunks along last dimension
sd::ops::concat_bp opc;
auto dec = opc.evaluate({input, input, actv}, {-1});
if (dec->status() != ND4J_STATUS_OK)
return dec->status();
if (dec.status() != ND4J_STATUS_OK)
return dec.status();
// and now we subtract two parts of epsilons and pass result out
auto pos = dec->at(0);
auto neg = dec->at(1);
auto pos = dec.at(0);
auto neg = dec.at(1);
pos->applyPairwiseTransform(sd::pairwise::Subtract, *neg, *epsilon);
delete tmpResult;
delete dec;
return ND4J_STATUS_OK;
}

8
libnd4j/include/ops/declarable/generic/boolean/where_np.cpp
View File

@ -102,10 +102,12 @@ namespace sd {
REQUIRE_TRUE(block.width() == 1, 0, "Where op takes either 1 or 3 operands, But got %d operands instead", block.width());
// if (output->isEmpty())
Nd4jLong width = condition->rankOf();
sd::ops::Where op;
std::unique_ptr<ResultSet> res(op.evaluate({condition}));
REQUIRE_OK(res->status());
NDArray* whereTrue = res->at(0);
auto res(op.evaluate({condition}));
REQUIRE_OK(res.status());
NDArray* whereTrue = res.at(0);
if (whereTrue->isEmpty())
return ND4J_STATUS_OK;
for (Nd4jLong outNext = 0; outNext < width; ++outNext) {

7
libnd4j/include/ops/declarable/generic/broadcastable/floormod.cpp
View File

@ -65,11 +65,12 @@ namespace sd {
auto gradX = OUTPUT_VARIABLE(0);
auto gradY = OUTPUT_VARIABLE(1);
gradX->assign(epsNext);
sd::ops::floormod op;
std::unique_ptr<ResultSet> tmpResult(op.evaluate({x, y}));
auto tmpResult(op.evaluate({x, y}));
if (gradY->rankOf() == gradX->rankOf())
epsNext->applyPairwiseTransform(pairwise::Multiply, *tmpResult->at(0), *gradY);
epsNext->applyPairwiseTransform(pairwise::Multiply, *tmpResult.at(0), *gradY);
else // epsNext is greater than gradY
{
std::vector<Nd4jLong> dims(epsNext->rankOf() * 2);
@ -77,7 +78,7 @@ namespace sd {
for (Nd4jLong d = 0; d < gap; d++) {
dims[d * 2 + 1] = 1;
}
auto tempIn((*tmpResult->at(0))(dims));
auto tempIn((*tmpResult.at(0))(dims));
(*epsNext)(dims).applyPairwiseTransform(pairwise::Multiply, tempIn, *gradY);
}
return Status::OK();

14
libnd4j/include/ops/declarable/generic/parity_ops/dynamic_parititon.cpp
View File

@ -113,23 +113,21 @@ namespace ops {
originalIndices.linspace(0);
ops::dynamic_partition op;
auto res = op.evaluate({&originalIndices, indices}, {numPartition});
REQUIRE_TRUE(res->status() == ND4J_STATUS_OK, 0, "dynamic_partition_bp: Error with dynamic partitioning.");
REQUIRE_TRUE(res.status() == ND4J_STATUS_OK, 0, "dynamic_partition_bp: Error with dynamic partitioning.");
ops::dynamic_stitch stichOp;
std::vector<NDArray*> partitions(numPartition * 2);
for (size_t i = 0; i < res->size(); i++) {
partitions[i] = res->at(i);
for (size_t i = 0; i < res.size(); i++) {
partitions[i] = res.at(i);
partitions[i + numPartition] = gradOutList[i];
}
auto result = stichOp.evaluate(partitions, {numPartition});
REQUIRE_TRUE(result->status() == ND4J_STATUS_OK, 0, "dynamic_partition_bp: Error with dynamic partitioning.");
result->at(0)->reshapei(outputList[0]->getShapeAsVector());
REQUIRE_TRUE(result.status() == ND4J_STATUS_OK, 0, "dynamic_partition_bp: Error with dynamic partitioning.");
result.at(0)->reshapei(outputList[0]->getShapeAsVector());
outputList[1]->assign(indices);
outputList[0]->assign(result->at(0));
outputList[0]->assign(result.at(0));
// helpers::dynamicPartitionFunctorBP(block.launchContext(), input, indices, gradOutList, outputList);
delete res;
delete result;
return ND4J_STATUS_OK;
}

8
libnd4j/include/ops/declarable/generic/parity_ops/embedding_lookup.cpp
View File

@ -66,10 +66,10 @@ CUSTOM_OP_IMPL(embedding_lookup, 2, 1, false, 0, 1) {
sd::ops::gather op;
std::unique_ptr<ResultSet> result(op.evaluate({input, indeces}, {0}));
REQUIRE_TRUE(result->status() == Status::OK(), 0, "embedding_lookup: cannot retrieve results from gather op.");
REQUIRE_TRUE(result->at(0)->isSameShape(output), 0, "embedding_lookup: wrong shape of return from gather op.");
output->assign(result->at(0));
auto result(op.evaluate({input, indeces}, {0}));
REQUIRE_TRUE(result.status() == Status::OK(), 0, "embedding_lookup: cannot retrieve results from gather op.");
REQUIRE_TRUE(result.at(0)->isSameShape(output), 0, "embedding_lookup: wrong shape of return from gather op.");
output->assign(result.at(0));
}
return Status::OK();
}

25
libnd4j/include/ops/declarable/generic/recurrent/dynamicBidirectionalRNN.cpp
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@ -95,8 +95,8 @@ CUSTOM_OP_IMPL(dynamic_bidirectional_rnn, 7, 4, false, 0, 0) {
// forward steps
sd::ops::dynamic_rnn dynamicRnn;
auto resultsFW = dynamicRnn.evaluate({x, WxFW, WhFW, bFW, h0FW, maxTimeStep}, {timeMajor});
hFW->assign(resultsFW->at(0)); // [time x bS x numUnitsFW] or [bS x time x numUnitsFW]
hFWFinal->assign(resultsFW->at(1));
hFW->assign(resultsFW.at(0)); // [time x bS x numUnitsFW] or [bS x time x numUnitsFW]
hFWFinal->assign(resultsFW.at(1));
auto seqLen = maxTimeStep;
if(seqLen == nullptr) {
@ -108,22 +108,17 @@ CUSTOM_OP_IMPL(dynamic_bidirectional_rnn, 7, 4, false, 0, 0) {
// reverse x
sd::ops::reverse_sequence reverse;
auto resultsIn = timeMajor ? reverse.evaluate({x, seqLen}, {0, 1}) : reverse.evaluate({x, seqLen}, {1, 0});
REQUIRE_TRUE (resultsIn->status() == ND4J_STATUS_OK, 0, "dynamic_bidirectional_rnn: there is a problem with reverse on the sequence.");
auto revInput = resultsIn->at(0);
REQUIRE_TRUE (resultsIn.status() == ND4J_STATUS_OK, 0, "dynamic_bidirectional_rnn: there is a problem with reverse on the sequence.");
auto revInput = resultsIn.at(0);
// backward steps
auto resultsBW = dynamicRnn.evaluate({revInput, WxBW, WhBW, bBW, h0BW, maxTimeStep}, {timeMajor});
auto hBWtemp = resultsBW->at(0); // [time x bS x numUnitsBW] or [ bS x time xnumUnitsBW]
hBWFinal->assign(resultsBW->at(1));
auto hBWtemp = resultsBW.at(0); // [time x bS x numUnitsBW] or [ bS x time xnumUnitsBW]
hBWFinal->assign(resultsBW.at(1));
// reverse hBWtemp
auto resultsOut = timeMajor ? reverse.evaluate({hBWtemp, seqLen}, {0, 1}) : reverse.evaluate({hBWtemp, seqLen}, {1, 0});
hBW->assign(resultsOut->at(0));
delete resultsOut;
delete resultsBW;
delete resultsIn;
delete resultsFW;
hBW->assign(resultsOut.at(0));
if(seqLen != maxTimeStep)
delete seqLen;
@ -228,12 +223,6 @@ DECLARE_SHAPE_FN(dynamic_bidirectional_rnn) {
}
}
}

5
libnd4j/include/ops/declarable/helpers/impl/multiUnique.cpp
View File

@ -52,14 +52,13 @@ namespace helpers {
sd::ops::unique opUnique;
auto uResult = opUnique.evaluate({&arrayFull});
if (Status::OK() != uResult->status())
if (Status::OK() != uResult.status())
throw std::runtime_error("multiUnique: cannot execute unique op properly.");
auto uniqueVals = uResult->at(0);
auto uniqueVals = uResult.at(0);
bool res = uniqueVals->lengthOf() == arrayFull.lengthOf();
delete uResult;
return res;
}

12
libnd4j/include/ops/declarable/impl/DeclarableListOp.cpp
View File

@ -64,7 +64,7 @@ namespace sd {
block.pushNDArrayListToVariableSpace(block.getNodeId(), 0, arrayList);
}
ResultSet* DeclarableListOp::execute(NDArrayList* list, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs) {
ResultSet DeclarableListOp::execute(NDArrayList* list, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs) {
std::vector<NDArray*> ins(inputs);
std::vector<double> tas(tArgs);
std::vector<int> ias(iArgs);
@ -94,7 +94,7 @@ namespace sd {
return status;
}
ResultSet* DeclarableListOp::execute(NDArrayList* list, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs) {
ResultSet DeclarableListOp::execute(NDArrayList* list, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs) {
VariableSpace varSpace;
int nodeId = 119;
@ -132,8 +132,8 @@ namespace sd {
Nd4jStatus result = this->validateAndExecute(block);
auto res = new ResultSet();
res->setStatus(result);
ResultSet res;
res.setStatus(result);
for (int e = 0; e < DataTypeUtils::max<int>(); e++) {
std::pair<int,int> pair(1, e);
@ -143,10 +143,10 @@ namespace sd {
auto arr = var->getNDArray();
if (arr->isAttached()) {
auto d = arr->detach();
res->push_back(d);
res.push_back(d);
} else {
var->markRemovable(false);
res->push_back(arr);
res.push_back(arr);
}
}
} else

30
libnd4j/include/ops/declarable/impl/DeclarableOp.cpp
View File

@ -962,12 +962,12 @@ namespace sd {
return execute(&ctx);
}
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs) {
return evaluate(inputs, std::vector<double>(), std::vector<Nd4jLong>(), std::vector<bool>(), std::vector<sd::DataType>());
}
template <>
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<int> iArgs) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<int> iArgs) {
std::vector<Nd4jLong> realArgs;
for (auto v:iArgs)
realArgs.emplace_back(v);
@ -976,12 +976,12 @@ namespace sd {
}
template <>
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<Nd4jLong> iArgs) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<Nd4jLong> iArgs) {
return evaluate(inputs, std::vector<double>(), iArgs, std::vector<bool>(), std::vector<sd::DataType>());
}
template <>
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<float> tArgs) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<float> tArgs) {
std::vector<double> realArgs;
for (auto v:tArgs)
realArgs.emplace_back(v);
@ -990,21 +990,21 @@ namespace sd {
}
template <>
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<double> tArgs) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<double> tArgs) {
return evaluate(inputs, tArgs, std::vector<Nd4jLong>(), std::vector<bool>(), std::vector<sd::DataType>());
}
template <>
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<bool> bArgs) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<bool> bArgs) {
return evaluate(inputs, std::vector<double>(), std::vector<Nd4jLong>(), bArgs, std::vector<sd::DataType>());
}
template <>
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<sd::DataType> bArgs) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, std::initializer_list<sd::DataType> bArgs) {
return evaluate(inputs, std::vector<double>(), std::vector<Nd4jLong>(), std::vector<bool>(), bArgs);
}
sd::ResultSet *DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, const std::vector<double> &tArgs, const std::vector<Nd4jLong> &iArgs, const std::vector<bool> &bArgs, const std::vector<sd::DataType> &dArgs, bool isInplace) {
sd::ResultSet DeclarableOp::evaluate(const std::vector<NDArray *> &inputs, const std::vector<double> &tArgs, const std::vector<Nd4jLong> &iArgs, const std::vector<bool> &bArgs, const std::vector<sd::DataType> &dArgs, bool isInplace) {
VariableSpace variableSpace;
//ResultSet arrayList;
FlowPath fp;
@ -1041,11 +1041,11 @@ namespace sd {
block.getDArguments()->push_back(dArgs.at(e));
Nd4jStatus status = this->execute(&block);
auto arrayList = new ResultSet();
ResultSet arrayList;
if (isInplace)
arrayList->setNonRemovable();
arrayList.setNonRemovable();
arrayList->setStatus(status);
arrayList.setStatus(status);
if (status != ND4J_STATUS_OK)
return arrayList;
@ -1058,23 +1058,23 @@ namespace sd {
if (!arr->isAttached()) {
var->markRemovable(false);
arr->setContext(sd::LaunchContext::defaultContext());
arrayList->push_back(arr);
arrayList.push_back(arr);
} else {
arrayList->push_back(arr->detach());
arrayList.push_back(arr->detach());
}
} else
break;
}
} else {
for (auto v:inputs) {
arrayList->push_back(v);
arrayList.push_back(v);
}
}
return arrayList;
}
sd::ResultSet* sd::ops::DeclarableOp::execute(const sd::OpArgsHolder& holder, bool isInplace) {
sd::ResultSet sd::ops::DeclarableOp::execute(const sd::OpArgsHolder& holder, bool isInplace) {
// FIXME: add DArgs to OpArgsHolder
return evaluate(holder.getInArrs(), holder.getTArgs(), holder.getIArgs(), holder.getBArgs(), std::vector<sd::DataType>(), isInplace);
}

14
libnd4j/include/ops/declarable/impl/LegacyRandomOp.cpp
View File

@ -357,20 +357,20 @@ namespace sd {
return DeclarableOp::execute(block);
}
sd::ResultSet* LegacyRandomOp::execute(sd::graph::RandomGenerator& rng, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs, bool isInplace) {
sd::ResultSet LegacyRandomOp::execute(sd::graph::RandomGenerator& rng, std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<int> iArgs, bool isInplace) {
std::vector<NDArray*> ins(inputs);
std::vector<double> tas(tArgs);
std::vector<int> ias(iArgs);
return this->execute(rng, ins, tas, ias, isInplace);
}
sd::ResultSet* LegacyRandomOp::execute(sd::graph::RandomGenerator& rng, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs, bool isInplace) {
sd::ResultSet LegacyRandomOp::execute(sd::graph::RandomGenerator& rng, std::vector<NDArray*>& inputs, std::vector<double>& tArgs, std::vector<int>& iArgs, bool isInplace) {
VariableSpace variableSpace;
auto arrayList = new ResultSet();
ResultSet arrayList;
//ResultSet arrayList;
if (isInplace)
arrayList->setNonRemovable();
arrayList.setNonRemovable();
int cnt = -1;
std::vector<int> in;
@ -398,7 +398,7 @@ namespace sd {
block.getIArguments()->emplace_back(iArgs.at(e));
Nd4jStatus status = this->execute(&block);
arrayList->setStatus(status);
arrayList.setStatus(status);
if (status != ND4J_STATUS_OK)
return arrayList;
@ -410,9 +410,9 @@ namespace sd {
auto arr = var->getNDArray();
if (!arr->isAttached()) {
var->markRemovable(false);
arrayList->push_back(arr);
arrayList.push_back(arr);
} else {
arrayList->push_back(arr->detach());
arrayList.push_back(arr->detach());
}
} else
break;

24
libnd4j/tests_cpu/layers_tests/AttentionTests.cpp
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@ -44,9 +44,7 @@ TEST_F(AttentionTests, basic_dot_product_attention) {
sd::ops::dot_product_attention op;
auto result = op.evaluate({&queries, &keys, &values}, {1, 0});
ASSERT_EQ(Status::OK(), result->status());
delete result;
ASSERT_EQ(Status::OK(), result.status());
}
/*
@ -72,9 +70,7 @@ TEST_F(AttentionTests, basic_dot_product_attention_with_weights) {
sd::ops::dot_product_attention op;
auto result = op.evaluate({&queries, &keys, &values}, {1, 1});
ASSERT_EQ(Status::OK(), result->status());
delete result;
ASSERT_EQ(Status::OK(), result.status());
}
TEST_F(AttentionTests, basic_dot_product_attention_with_mask) {
@ -86,9 +82,7 @@ TEST_F(AttentionTests, basic_dot_product_attention_with_mask) {
sd::ops::dot_product_attention op;
auto result = op.evaluate({&queries, &keys, &values, &mask}, {1, 0});
ASSERT_EQ(Status::OK(), result->status());
delete result;
ASSERT_EQ(Status::OK(), result.status());
}
/*
@ -118,9 +112,7 @@ TEST_F(AttentionTests, multi_head_input_dot_product_attention_with_mask) {
sd::ops::dot_product_attention op;
auto result = op.evaluate({&queries, &keys, &values, &mask}, {1, 0});
ASSERT_EQ(Status::OK(), result->status());
delete result;
ASSERT_EQ(Status::OK(), result.status());
}
/*
@ -154,9 +146,7 @@ TEST_F(AttentionTests, basic_multi_head_dot_product_attention) {
sd::ops::multi_head_dot_product_attention op;
auto result = op.evaluate({&queries, &keys, &values, &Wk, &Wv, &Wq, &Wo}, {1, 0});
ASSERT_EQ(Status::OK(), result->status());
delete result;
ASSERT_EQ(Status::OK(), result.status());
}
/*
@ -198,9 +188,7 @@ TEST_F(AttentionTests, basic_multi_head_dot_product_attention_with_mask) {
sd::ops::multi_head_dot_product_attention op;
auto result = op.evaluate({&queries, &keys, &values, &Wk, &Wv, &Wq, &Wo, &mask}, {1, 0});
ASSERT_EQ(Status::OK(), result->status());
delete result;
ASSERT_EQ(Status::OK(), result.status());
}
/*

8
libnd4j/tests_cpu/layers_tests/BackpropTests.cpp
View File

@ -39,13 +39,11 @@ TEST_F(BackpropTests, Test_Add_1) {
sd::ops::add_bp op;
auto result = op.evaluate({&x, &y, &e});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto eps = result->at(0);
auto grad = result->at(1);
auto eps = result.at(0);
auto grad = result.at(1);
ASSERT_TRUE(x.isSameShape(eps));
ASSERT_TRUE(y.isSameShape(grad));
delete result;
}

7
libnd4j/tests_cpu/layers_tests/BooleanOpsTests.cpp
View File

@ -137,13 +137,12 @@ TEST_F(BooleanOpsTests, test_where_1) {
sd::ops::choose op;
auto result = op.evaluate({&x, &y}, {3});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
//z->printIndexedBuffer("z");
ASSERT_EQ(e, *z);
delete result;
}

92
libnd4j/tests_cpu/layers_tests/BroadcastableOpsTests.cpp
View File

@ -48,9 +48,9 @@ TEST_F(BroadcastableOpsTests, Test_Add_1) {
sd::ops::add op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
//exp.printIndexedBuffer("E A");
//z->printIndexedBuffer("Z");
@ -58,7 +58,6 @@ TEST_F(BroadcastableOpsTests, Test_Add_1) {
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -75,14 +74,12 @@ TEST_F(BroadcastableOpsTests, Test_Multiply_1) {
sd::ops::multiply op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -100,14 +97,13 @@ TEST_F(BroadcastableOpsTests, Test_SquaredSubtract_1) {
sd::ops::squaredsubtract op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -119,14 +115,12 @@ TEST_F(BroadcastableOpsTests, Test_ScalarBroadcast_1) {
sd::ops::subtract op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -138,14 +132,12 @@ TEST_F(BroadcastableOpsTests, Test_ScalarBroadcast_2) {
sd::ops::add op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -156,14 +148,12 @@ TEST_F(BroadcastableOpsTests, Test_Maximum_1) {
sd::ops::maximum op;
auto result = op.evaluate({&x, &row});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -174,15 +164,14 @@ TEST_F(BroadcastableOpsTests, Test_Minimum_1) {
sd::ops::minimum op;
auto result = op.evaluate({&x, &col});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -283,14 +272,13 @@ TEST_F(BroadcastableOpsTests, Test_Scalar_Add_1) {
sd::ops::add op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -333,11 +321,9 @@ TEST_F(BroadcastableOpsTests, Test_Subtract_2) {
sd::ops::subtract op;
auto result = op.evaluate({&x, &y});
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Subtract_3) {
@ -511,13 +497,12 @@ TEST_F(BroadcastableOpsTests, Test_Multiply_7) {
sd::ops::multiply op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Multiply_8) {
@ -527,13 +512,11 @@ TEST_F(BroadcastableOpsTests, Test_Multiply_8) {
sd::ops::multiply op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.equalsTo(z));
delete result;
}
//////////////////////////////////////////////////////////////////////
@ -606,14 +589,12 @@ TEST_F(BroadcastableOpsTests, broadcast_empty_3) {
sd::ops::maximum op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_4) {
@ -625,14 +606,13 @@ TEST_F(BroadcastableOpsTests, broadcast_empty_4) {
sd::ops::maximum op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_5) {
@ -644,14 +624,13 @@ TEST_F(BroadcastableOpsTests, broadcast_empty_5) {
sd::ops::realdiv op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_6) {
@ -663,14 +642,13 @@ TEST_F(BroadcastableOpsTests, broadcast_empty_6) {
sd::ops::realdiv op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_7) {
@ -682,14 +660,12 @@ TEST_F(BroadcastableOpsTests, broadcast_empty_7) {
sd::ops::realdiv op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
@ -718,15 +694,13 @@ TEST_F(BroadcastableOpsTests, broadcast_bool_empty_2) {
sd::ops::greater op;
auto result = op.evaluate({&x, &y});
auto z = result->at(0);
auto z = result.at(0);
// z->printShapeInfo("z");
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_bool_1) {

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libnd4j/tests_cpu/layers_tests/ConvolutionTests1.cpp
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libnd4j/tests_cpu/layers_tests/ConvolutionTests2.cpp
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libnd4j/tests_cpu/layers_tests/DataTypesValidationTests.cpp
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@ -48,9 +48,7 @@ TEST_F(DataTypesValidationTests, Basic_Test_1) {
sd::ops::conv2d op;
auto result = op.evaluate({&input, &weights}, {1, 1, 1, 1, 0, 0, 1, 1, 0, 0});
ASSERT_EQ(ND4J_STATUS_VALIDATION, result->status());
delete result;
ASSERT_EQ(ND4J_STATUS_VALIDATION, result.status());
}
TEST_F(DataTypesValidationTests, Basic_Test_2) {
@ -63,13 +61,12 @@ TEST_F(DataTypesValidationTests, Basic_Test_2) {
sd::ops::conv2d op;
auto result = op.evaluate({&input, &weights}, {1, 1, 1, 1, 0, 0, 1, 1, 0, 0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}

567
libnd4j/tests_cpu/layers_tests/DeclarableOpsTests1.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests10.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests11.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests12.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests13.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests14.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests15.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests16.cpp
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@ -47,13 +47,11 @@ TEST_F(DeclarableOpsTests16, scatter_upd_1) {
sd::ops::scatter_upd op;
auto result = op.evaluate({ &x, &y, &w });
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests16, scatter_upd_2) {
@ -67,13 +65,11 @@ TEST_F(DeclarableOpsTests16, scatter_upd_2) {
sd::ops::scatter_upd op;
auto result = op.evaluate({ &x, &indices, &updates });
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests16, scatter_upd_3) {
@ -136,13 +132,11 @@ TEST_F(DeclarableOpsTests16, test_hamming_distance_1) {
sd::ops::bits_hamming_distance op;
auto result = op.evaluate({ &x, &y });
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(DeclarableOpsTests16, test_knn_mindistance_1) {
@ -167,10 +161,8 @@ TEST_F(DeclarableOpsTests16, test_empty_cast_1) {
sd::ops::cast op;
auto result = op.evaluate({&x}, {10});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(e, *result->at(0));
delete result;
ASSERT_EQ(Status::OK(), result.status());
ASSERT_EQ(e, *result.at(0));
}
TEST_F(DeclarableOpsTests16, test_range_1) {
@ -717,8 +709,6 @@ TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_1) {
}
TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_2) {
auto rgb = NDArrayFactory::create<float>('c', { 5, 3, 4 },
@ -767,7 +757,6 @@ TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_2) {
}
TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_3) {
auto rgb = NDArrayFactory::create<float>('c', { 4, 3 },
@ -798,7 +787,6 @@ TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_3) {
}
TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_4) {
auto rgb = NDArrayFactory::create<float>('c', { 3, 4 },
@ -826,7 +814,6 @@ TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_4) {
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(expected.equalsTo(actual));
}
@ -850,7 +837,6 @@ TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_5) {
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(expected.equalsTo(actual));
}
TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_6) {
@ -891,8 +877,6 @@ TEST_F(DeclarableOpsTests16, test_rgb_to_yiq_6) {
}
TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_1) {
auto yiqs = NDArrayFactory::create<float>('c', { 5, 4, 3 }, {
@ -937,8 +921,6 @@ TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_1) {
}
TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_2) {
auto yiqs = NDArrayFactory::create<float>('c', { 5, 3, 4 }, {
@ -983,7 +965,6 @@ TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_2) {
}
TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_3) {
auto yiqs = NDArrayFactory::create<float>('c', { 4, 3 }, {
@ -1010,7 +991,6 @@ TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_3) {
}
TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_4) {
auto yiqs = NDArrayFactory::create<float>('c', { 3, 4 }, {
@ -1037,8 +1017,6 @@ TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_4) {
}
TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_5) {
auto yiqs = NDArrayFactory::create<float>('c', { 3 }, {
@ -1061,7 +1039,6 @@ TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_5) {
#endif
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(expected.equalsTo(actual));
}
TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_6) {
@ -1096,5 +1073,4 @@ TEST_F(DeclarableOpsTests16, test_yiq_to_rgb_6) {
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(expected.equalsTo(actual));
}

16
libnd4j/tests_cpu/layers_tests/DeclarableOpsTests17.cpp
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@ -49,9 +49,7 @@ TEST_F(DeclarableOpsTests17, test_sparse_to_dense_1) {
sd::ops::compat_sparse_to_dense op;
auto result = op.evaluate({&ranges, &shape, &values, &def});
ASSERT_EQ(Status::OK(), result->status());
delete result;
ASSERT_EQ(Status::OK(), result.status());
}
TEST_F(DeclarableOpsTests17, test_sparse_to_dense_2) {
@ -64,9 +62,8 @@ TEST_F(DeclarableOpsTests17, test_sparse_to_dense_2) {
sd::ops::compat_sparse_to_dense op;
auto result = op.evaluate({&ranges, &shape, &values, &def});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
delete result;
}
TEST_F(DeclarableOpsTests17, test_compat_string_split_1) {
@ -78,11 +75,11 @@ TEST_F(DeclarableOpsTests17, test_compat_string_split_1) {
sd::ops::compat_string_split op;
auto result = op.evaluate({&x, &delimiter});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(2, result->size());
ASSERT_EQ(Status::OK(), result.status());
ASSERT_EQ(2, result.size());
auto z0 = result->at(0);
auto z1 = result->at(1);
auto z0 = result.at(0);
auto z1 = result.at(1);
ASSERT_TRUE(exp0.isSameShape(z0));
ASSERT_TRUE(exp1.isSameShape(z1));
@ -90,5 +87,4 @@ TEST_F(DeclarableOpsTests17, test_compat_string_split_1) {
ASSERT_EQ(exp0, *z0);
ASSERT_EQ(exp1, *z1);
delete result;
}

4
libnd4j/tests_cpu/layers_tests/DeclarableOpsTests19.cpp
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@ -62,10 +62,8 @@ TEST_F(DeclarableOpsTests19, test_conv1d_bp_1) {
sd::ops::conv1d_bp op;
auto result = op.evaluate({&t, &u, &v}, {3, 2, 0, 1, 2,0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
delete result;
}
TEST_F(DeclarableOpsTests19, test_squeeze_1) {

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libnd4j/tests_cpu/layers_tests/DeclarableOpsTests2.cpp
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libnd4j/tests_cpu/layers_tests/DeclarableOpsTestsCuda1.cu
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@ -51,14 +51,12 @@ TEST_F(DeclarableOpsTestsCuda1, Test_CHOOSE_SCALAR_LARGE) {
sd::ops::choose op;
//greater than test
auto result = op.evaluate({&x}, {0.0},{3});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(1);
auto z = result.at(1);
ASSERT_EQ(148,z->e<double>(0));
//ASSERT_TRUE(exp.isSameShape(z));
delete result;
}
/*

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libnd4j/tests_cpu/layers_tests/EmptyTests.cpp
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@ -67,9 +67,9 @@ TEST_F(EmptyTests, Test_Concat_1) {
sd::ops::concat op;
auto result = op.evaluate({empty, vector}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printShapeInfo("z shape");
// z->printIndexedBuffer("z buffr");
@ -78,7 +78,6 @@ TEST_F(EmptyTests, Test_Concat_1) {
delete empty;
delete vector;
delete result;
}
@ -92,9 +91,9 @@ TEST_F(EmptyTests, Test_Concat_2) {
sd::ops::concat op;
auto result = op.evaluate({empty, scalar1, scalar2}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printShapeInfo("z shape");
// z->printIndexedBuffer("z buffr");
@ -104,7 +103,6 @@ TEST_F(EmptyTests, Test_Concat_2) {
delete empty;
delete scalar1;
delete scalar2;
delete result;
}
TEST_F(EmptyTests, Test_Concat_3) {
@ -117,13 +115,12 @@ TEST_F(EmptyTests, Test_Concat_3) {
sd::ops::concat op;
auto result = op.evaluate({&empty, &scalar1, &scalar2}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(exp, *z);
delete result;
}
TEST_F(EmptyTests, Test_Concat_4) {
@ -136,13 +133,11 @@ TEST_F(EmptyTests, Test_Concat_4) {
sd::ops::concat op;
auto result = op.evaluate({&scalar1, &empty, &scalar2}, {}, {0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(exp, *z);
delete result;
}
TEST_F(EmptyTests, Test_Reshape_1) {
@ -153,12 +148,11 @@ TEST_F(EmptyTests, Test_Reshape_1) {
sd::ops::reshape op;
auto result = op.evaluate({&vector, empty}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
ASSERT_EQ(exp, *result->at(0));
ASSERT_EQ(exp, *result.at(0));
delete empty;
delete result;
}
TEST_F(EmptyTests, Test_Reshape_3) {
@ -168,14 +162,13 @@ TEST_F(EmptyTests, Test_Reshape_3) {
sd::ops::reshape op;
auto result = op.evaluate({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(EmptyTests, Test_dup_1) {
@ -197,12 +190,11 @@ TEST_F(EmptyTests, test_empty_scatter_1) {
sd::ops::scatter_upd op;
auto result = op.evaluate({&x, &indices, &updates}, {}, {}, {true});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(x, *z);
delete result;
}
TEST_F(EmptyTests, test_empty_scatter_2) {
@ -288,17 +280,15 @@ TEST_F(EmptyTests, test_empty_reshape_1) {
sd::ops::reshape op;
auto result0 = op.evaluate({&x0, &shape0}, {}, {});
ASSERT_EQ(Status::OK(), result0->status());
auto z0 = result0->at(0);
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(Status::OK(), result1.status());
auto z1 = result1.at(0);
ASSERT_EQ(e1, *z1);
delete result0;
delete result1;
}
@ -309,12 +299,11 @@ TEST_F(EmptyTests, test_empty_matmul_1) {
sd::ops::matmul op;
auto result = op.evaluate({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(e, *z);
delete result;
}
TEST_F(EmptyTests, test_empty_matmul_2) {
@ -324,10 +313,8 @@ TEST_F(EmptyTests, test_empty_matmul_2) {
sd::ops::matmul op;
auto result = op.evaluate({&x, &y}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(e, *z);
delete result;
}

11
libnd4j/tests_cpu/layers_tests/HelpersTests1.cpp
View File

@ -1889,20 +1889,19 @@ TEST_F(HelpersTests1, OpArgsHolder_test3) {
OpArgsHolder holderFF({&input}, {}, {2, 3});
sd::ops::tile opFF; // the kind of op doesn't matter, we simply check here whether op.execute() works with OpArgsHolder correctly
auto results = opFF.execute(holderFF);
auto tiled = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
auto tiled = results.at(0);
ASSERT_EQ(Status::OK(), results.status());
ASSERT_TRUE(exp.isSameShape(tiled));
ASSERT_TRUE(exp.equalsTo(tiled));
delete results;
OpArgsHolder holderBP = holderFF.createArgsHolderForBP({&gradO}, true);
sd::ops::tile_bp opBP;
results = opBP.execute(holderBP);
auto gradI = results->at(0);
ASSERT_EQ(Status::OK(), results->status());
auto gradI = results.at(0);
ASSERT_EQ(Status::OK(), results.status());
ASSERT_TRUE(gradIExp.isSameShape(gradI));
ASSERT_TRUE(gradIExp.equalsTo(gradI));
delete results;
}

114
libnd4j/tests_cpu/layers_tests/IndexingTests.cpp
View File

@ -47,13 +47,13 @@ TEST_F(IndexingTests, StridedSlice_1) {
sd::ops::strided_slice op;
auto result = op.evaluate({&x, &begin, &end, &strides}, {}, {0,0,0,0,0}); //, 2,2,0, 3,3,3, 1,1,1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -66,14 +66,14 @@ TEST_F(IndexingTests, StridedSlice_2) {
sd::ops::strided_slice op;
auto result = op.evaluate({&x}, {}, {0,0,0,0,0, 3,2,0, 5,5,3, 1,1,1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -86,14 +86,14 @@ TEST_F(IndexingTests, StridedSlice_3) {
sd::ops::strided_slice op;
auto result = op.evaluate({&x}, {}, {0,0,0,0,0, 3,2,0, 5,5,3, 1,1,2});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -109,15 +109,15 @@ TEST_F(IndexingTests, SimpleSlice_1) {
sd::ops::slice op;
auto result = op.evaluate({&input}, {}, {1,0,0, 1,1,3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -135,15 +135,15 @@ TEST_F(IndexingTests, SimpleSlice_2) {
sd::ops::slice op;
auto result = op.evaluate({&input}, {}, {1,0,0, 1,2,3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(IndexingTests, SimpleSlice_3) {
@ -160,15 +160,15 @@ TEST_F(IndexingTests, SimpleSlice_3) {
sd::ops::slice op;
auto result = op.evaluate({&input}, {}, {1,0,0, 2,1,3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(IndexingTests, SimpleSlice_4) {
@ -180,14 +180,14 @@ TEST_F(IndexingTests, SimpleSlice_4) {
sd::ops::slice op;
auto result = op.evaluate({&input, &start, &stop});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -204,16 +204,16 @@ TEST_F(IndexingTests, MaskedSlice_0) {
sd::ops::strided_slice op;
auto result = op.evaluate({&matrix}, {}, {0,0,0,0,0, 1, 2, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printShapeInfo("z");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -230,14 +230,14 @@ TEST_F(IndexingTests, MaskedSlice_00) {
sd::ops::strided_slice op;
auto result = op.evaluate({&matrix}, {}, {0,0,0,0,0, 1, 1, 2, 3, 1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -254,16 +254,16 @@ TEST_F(IndexingTests, MaskedSlice_1) {
sd::ops::strided_slice op;
auto result = op.evaluate({&matrix}, {}, {0,0,0,0,1, 1, 2, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printShapeInfo("z");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(IndexingTests, MaskedSlice_2) {
@ -275,14 +275,14 @@ TEST_F(IndexingTests, MaskedSlice_2) {
sd::ops::strided_slice op;
auto result = op.evaluate({&matrix}, {}, {0,0,0,0,1, 1, 0, 0, 3, 3, 3, 1, 1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -295,14 +295,14 @@ TEST_F(IndexingTests, MaskedSlice_3) {
sd::ops::strided_slice op;
auto result = op.evaluate({&matrix}, {}, {0,0,0,0,2, 1, 0, 0, 3, 3, 3, 1, 1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -315,15 +315,15 @@ TEST_F(IndexingTests, MaskedSlice_4) {
sd::ops::strided_slice op;
auto result = op.evaluate({&matrix}, {}, {0,0,0,0, 3, 1, 0, 0, 3, 3, 3, 1, 1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(IndexingTests, Live_Slice_1) {
@ -338,16 +338,16 @@ TEST_F(IndexingTests, Live_Slice_1) {
sd::ops::strided_slice op;
auto result = op.evaluate({&matrix, &begin, &end, &stride}, {}, {0,0,0,0,3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printShapeInfo("z shape");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -361,14 +361,14 @@ TEST_F(IndexingTests, Test_StridedSlice_1) {
sd::ops::strided_slice op;
auto result = op.evaluate({&x, &a, &b, &c}, {}, {0, 0, 0, 0, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(IndexingTests, Test_StridedSlice_2) {
@ -381,16 +381,16 @@ TEST_F(IndexingTests, Test_StridedSlice_2) {
sd::ops::strided_slice op;
auto result = op.evaluate({&x, &a, &b, &c}, {}, {0, 0, 0, 0, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printIndexedBuffer("Z");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -404,14 +404,14 @@ TEST_F(IndexingTests, Test_StridedSlice_3) {
sd::ops::strided_slice op;
auto result = op.evaluate({&x, &a, &b, &c}, {}, {0, 0, 0, 0, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -426,16 +426,16 @@ TEST_F(IndexingTests, Test_StridedSlice_4) {
auto result = op.evaluate({&x, &a, &b, &c}, {}, {0, 0, 0, 0, 1});
// auto result = op.execute({&x, &a, &b, &c}, {}, {0, 0, 0, 0, 1, 0, 1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
//z->printIndexedBuffer("Z");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(IndexingTests, Test_Subarray_Strided_1) {
@ -458,13 +458,13 @@ TEST_F(IndexingTests, MaskedSlice_5) {
sd::ops::strided_slice<float> op;
auto result = op.execute({&matrix}, {}, {0,0,0,0,2, 1, 0, 0, 3, 3, 3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
*/

74
libnd4j/tests_cpu/layers_tests/LegacyOpsTests.cpp
View File

@ -64,13 +64,13 @@ TEST_F(LegacyOpsTests, TransformTests_2) {
sd::ops::LegacyTransformSameOp op(transform::Neg); // Neg
auto result = op.evaluate({&x}, {}, {});
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, Reciprocal_1) {
@ -121,12 +121,12 @@ TEST_F(LegacyOpsTests, PWT_Tests_2) {
sd::ops::LegacyPairwiseTransformOp op(pairwise::Multiply); // Multiply
auto result = op.evaluate({&x, &y}, {}, {});
auto z = result->at(0);
auto z = result.at(0);
//z->printBuffer("Z");
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, Scalar_Test_1) {
@ -154,10 +154,10 @@ TEST_F(LegacyOpsTests, Scalar_Test_2) {
sd::ops::LegacyScalarOp op(scalar::Add, y);
auto result = op.evaluate({&x}, {}, {});
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -169,14 +169,14 @@ TEST_F(LegacyOpsTests, ReduceTests_1) {
auto result = op.evaluate({&x}, {}, {});
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
// z->printBuffer("ReduceTest1");
ASSERT_TRUE(z->isScalar());
ASSERT_NEAR(x.sumNumber().e<float>(0), z->e<float>(0), 1e-5f);
delete result;
}
@ -188,16 +188,16 @@ TEST_F(LegacyOpsTests, ReduceTests_2) {
auto axis = NDArrayFactory::create<Nd4jLong>('c', {1}, {1});
auto result = op.evaluate({&x, &axis}, {}, {});
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
auto exp = x.reduceAlongDimension(reduce::Sum, {1});
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -209,15 +209,15 @@ TEST_F(LegacyOpsTests, ReduceTests_3) {
sd::ops::LegacyReduceSameOp op(reduce::Sum);
auto result = op.evaluate({&x, &indices}, {}, {});
auto z = result->at(0);
auto z = result.at(0);
auto exp = x.reduceAlongDimension(reduce::Sum,{1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -229,16 +229,16 @@ TEST_F(LegacyOpsTests, ReduceTests_4) {
sd::ops::LegacyReduceSameOp op(reduce::Sum);
auto result = op.evaluate({&x, &indices}, {}, {}, {true});
auto z = result->at(0);
auto z = result.at(0);
auto exp = x.reduceAlongDimension(reduce::Sum, {1}, true);
// indices.printShapeInfo("Indices shape");
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
// z->printIndexedBuffer("Output reduce 4");
// exp.printIndexedBuffer("Expected reduce 4");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, ReduceTests_5) {
@ -249,14 +249,14 @@ TEST_F(LegacyOpsTests, ReduceTests_5) {
auto result = op.evaluate({&x});
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
// z->printBuffer("ReduceTest1");
ASSERT_TRUE(z->isScalar());
ASSERT_NEAR(x.meanNumber().e<float>(0), z->e<float>(0), 1e-5f);
delete result;
}
@ -268,16 +268,16 @@ TEST_F(LegacyOpsTests, ReduceTests_6) {
auto result = op.evaluate({&x, &axis}, {}, {});
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
auto exp = x.reduceAlongDimension(reduce::Mean, {1});
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -289,15 +289,15 @@ TEST_F(LegacyOpsTests, ReduceTests_7) {
sd::ops::LegacyReduceFloatOp op(reduce::Mean);
auto result = op.evaluate({&x, &indices}, {}, {});
auto z = result->at(0);
auto z = result.at(0);
auto exp = x.reduceAlongDimension(reduce::Mean,{1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -309,17 +309,17 @@ TEST_F(LegacyOpsTests, ReduceTests_8) {
sd::ops::LegacyReduceFloatOp op(reduce::Mean);
auto result = op.evaluate({&x, &indices}, {}, {}, {true});
auto z = result->at(0);
auto z = result.at(0);
auto exp = x.reduceAlongDimension(reduce::Mean, {1}, true);
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
// z->printIndexedBuffer("Reduce8 output");
// z->printShapeInfo("Reduce8 shape");
// exp.printShapeInfo("Reduce8 expected shape");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -331,14 +331,14 @@ TEST_F(LegacyOpsTests, IndexReduceTests_1) {
auto result = op.evaluate({&x}, {}, {});
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(z->isScalar());
ASSERT_EQ(24, z->e<int>(0));
delete result;
}
@ -351,9 +351,9 @@ TEST_F(LegacyOpsTests, IndexReduceTests_2) {
auto result = op.evaluate({&x, &indices}, {}, {});
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
// z->printIndexedBuffer("Hello indexreduce2");
ASSERT_TRUE(exp.equalsTo(z));
//ASSERT_EQ(4, z->e<int>(0));
@ -362,7 +362,7 @@ TEST_F(LegacyOpsTests, IndexReduceTests_2) {
//ASSERT_EQ(4, z->e<int>(3));
//ASSERT_EQ(4, z->e<int>(4));
delete result;
}
TEST_F(LegacyOpsTests, BroadcastingTests_1) {

66
libnd4j/tests_cpu/layers_tests/ListOperationsTests.cpp
View File

@ -39,7 +39,7 @@ TEST_F(ListOperationsTests, BasicTest_Write_1) {
auto result = op.execute(&list, {&x}, {}, {1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
ASSERT_EQ(1, list.elements());
@ -47,8 +47,8 @@ TEST_F(ListOperationsTests, BasicTest_Write_1) {
ASSERT_EQ(2, list.elements());
delete result;
delete result2;
}
TEST_F(ListOperationsTests, BasicTest_Stack_1) {
@ -66,15 +66,15 @@ TEST_F(ListOperationsTests, BasicTest_Stack_1) {
auto result = op.execute(&list, {}, {}, {1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printShapeInfo();
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ListOperationsTests, BasicTest_UnStackList_1) {
@ -93,10 +93,10 @@ TEST_F(ListOperationsTests, BasicTest_UnStackList_1) {
auto result = op.execute(&list, {&x}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
ASSERT_EQ(list.elements(), 10);
// auto z = result->at(0);
// auto z = result.at(0);
// z->printShapeInfo("The first of");
// ASSERT_TRUE(exp.isSameShape(z));
// ASSERT_TRUE(exp.equalsTo(z));
@ -107,7 +107,7 @@ TEST_F(ListOperationsTests, BasicTest_UnStackList_1) {
delete row;
}
delete result;
}
//TEST_F(ListOperationsTests, BasicTest_UnStackList_2) {
@ -126,20 +126,20 @@ TEST_F(ListOperationsTests, BasicTest_UnStackList_1) {
//
// auto result = op.execute(nullptr, {&x}, {}, {0});
//
// ASSERT_EQ(ND4J_STATUS_OK, result->status());
// ASSERT_EQ(ND4J_STATUS_OK, result.status());
// ASSERT_EQ(result->size(), 10);
//
// // auto z = result->at(0);
// // auto z = result.at(0);
//// z->printShapeInfo("The first of");
//// ASSERT_TRUE(exp.isSameShape(z));
//// ASSERT_TRUE(exp.equalsTo(z));
// for (int e = 0; e < 10; e++) {
// auto row = result->at(e);
// auto row = result.at(e);
// ASSERT_TRUE(row->equalsTo(tads->at(e)));
// //list.write(e, row);
// }
//
// delete result;
//
// delete tads;
//}
@ -160,14 +160,14 @@ TEST_F(ListOperationsTests, BasicTest_Read_1) {
auto result = op.execute(&list, {}, {}, {4});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ListOperationsTests, BasicTest_Pick_1) {
@ -192,14 +192,14 @@ TEST_F(ListOperationsTests, BasicTest_Pick_1) {
sd::ops::pick_list op;
auto result = op.execute(&list, {}, {}, {1, 1, 3, 3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ListOperationsTests, BasicTest_Size_1) {
@ -217,14 +217,14 @@ TEST_F(ListOperationsTests, BasicTest_Size_1) {
auto result = op.execute(&list, {}, {}, {1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ListOperationsTests, BasicTest_Create_1) {
@ -235,12 +235,12 @@ TEST_F(ListOperationsTests, BasicTest_Create_1) {
auto result = op.execute(nullptr, {&matrix}, {}, {1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
// we return flow as well
ASSERT_EQ(1, result->size());
ASSERT_EQ(1, result.size());
delete result;
}
TEST_F(ListOperationsTests, BasicTest_Split_1) {
@ -283,7 +283,7 @@ TEST_F(ListOperationsTests, BasicTest_Split_1) {
sd::ops::split_list op;
auto result = op.execute(&list, {&matrix, &lengths}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
ASSERT_EQ(3, list.height());
@ -296,7 +296,7 @@ TEST_F(ListOperationsTests, BasicTest_Split_1) {
ASSERT_TRUE(exp2.isSameShape(list.readRaw(2)));
ASSERT_TRUE(exp2.equalsTo(list.readRaw(2)));
delete result;
}
TEST_F(ListOperationsTests, BasicTest_Scatter_1) {
@ -319,7 +319,7 @@ TEST_F(ListOperationsTests, BasicTest_Scatter_1) {
sd::ops::scatter_list op;
auto result = op.execute(&list, {&indices, &matrix, &s}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
for (int e = 0; e < 10; e++) {
auto row = tads.at(9 - e);
@ -329,7 +329,7 @@ TEST_F(ListOperationsTests, BasicTest_Scatter_1) {
ASSERT_TRUE(chunk->equalsTo(row));
}
delete result;
}
TEST_F(ListOperationsTests, BasicTest_Clone_1) {
@ -385,10 +385,10 @@ TEST_F(ListOperationsTests, BasicTest_Gather_1) {
sd::ops::gather_list op;
auto result = op.execute(&list, {&indices}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(1, result->size());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
ASSERT_EQ(1, result.size());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
@ -397,7 +397,7 @@ TEST_F(ListOperationsTests, BasicTest_Gather_1) {
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ListOperationsTests, GraphTests_Sequential_1) {

6
libnd4j/tests_cpu/layers_tests/MultiDataTypeTests.cpp
View File

@ -134,13 +134,11 @@ TEST_F(MultiDataTypeTests, Basic_Test_7) {
sd::ops::add op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(e, *z);
delete result;
}
////////////////////////////////////////////////////////////////////////////////

40
libnd4j/tests_cpu/layers_tests/NlpTests.cpp
View File

@ -66,7 +66,7 @@ TEST_F(NlpTests, basic_sg_hs_test_1) {
sd::ops::skipgram op;
auto result = op.evaluate({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto row0 = syn0({0,1, 0,0}, true);
auto row1 = syn1({1,2, 0,0}, true);
@ -74,7 +74,7 @@ TEST_F(NlpTests, basic_sg_hs_test_1) {
ASSERT_EQ(exp0, row0);
ASSERT_EQ(exp1, row1);
delete result;
}
TEST_F(NlpTests, basic_sg_hs_test_2) {
@ -107,7 +107,7 @@ TEST_F(NlpTests, basic_sg_hs_test_2) {
sd::ops::skipgram op;
auto result = op.evaluate({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto row0 = syn0({0,1, 0,0}, true);
auto row1 = syn1({1,2, 0,0}, true);
@ -117,7 +117,7 @@ TEST_F(NlpTests, basic_sg_hs_test_2) {
ASSERT_EQ(exp1, row1);
ASSERT_EQ(exp2, row2);
delete result;
}
TEST_F(NlpTests, basic_sg_hs_test_3) {
@ -159,7 +159,7 @@ TEST_F(NlpTests, basic_sg_hs_test_3) {
sd::ops::skipgram op;
auto result0 = op.evaluate({&target, &ngStarter, &indices0, &codes00, &syn00, &syn10, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, {}, true);
auto result1 = op.evaluate({&target, &ngStarter, &indices1, &codes01, &syn01, &syn11, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, {}, true);
ASSERT_EQ(Status::OK(), result0->status());
ASSERT_EQ(Status::OK(), result0.status());
auto row00 = syn00({0,1, 0,0}, true);
auto row01 = syn01({0,1, 0,0}, true);
@ -168,9 +168,6 @@ TEST_F(NlpTests, basic_sg_hs_test_3) {
ASSERT_EQ(row2, row1);
ASSERT_EQ(row00, row01);
delete result0;
delete result1;
}
TEST_F(NlpTests, basic_sg_hs_ns_test_1) {
@ -192,9 +189,9 @@ TEST_F(NlpTests, basic_sg_hs_ns_test_1) {
sd::ops::skipgram op;
auto result = op.evaluate({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {3}, {false}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
delete result;
}
TEST_F(NlpTests, basic_sg_ns_test_1) {
@ -227,14 +224,14 @@ TEST_F(NlpTests, basic_sg_ns_test_1) {
sd::ops::skipgram op;
auto result = op.evaluate({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {1, 1}, {false}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto row0 = syn0({1,2, 0,0}, true);
ASSERT_EQ(exp0, row0);
ASSERT_FALSE(syn1Neg2.equalsTo(syn1Neg, 1e-6));
delete result;
}
TEST_F(NlpTests, basic_cb_hs_test_1) {
@ -269,7 +266,7 @@ TEST_F(NlpTests, basic_cb_hs_test_1) {
sd::ops::cbow op;
auto result = op.evaluate({&target, &ngStarter, &context, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &numWords, &locked, &inferenceVector}, {}, {}, {true}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto row_s0_0 = syn0({0,1, 0,0}, true);
auto row_s0_1 = syn0({1,2, 0,0}, true);
@ -287,7 +284,7 @@ TEST_F(NlpTests, basic_cb_hs_test_1) {
ASSERT_EQ(exp1, row_s1_5);
ASSERT_EQ(exp2, row_s1_6);
delete result;
}
TEST_F(NlpTests, basic_cb_ns_test_1) {
@ -323,7 +320,7 @@ TEST_F(NlpTests, basic_cb_ns_test_1) {
sd::ops::cbow op;
auto result = op.evaluate({&target, &ngStarter, &context, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &numWords, &locked, &inferenceVector}, {}, {1, 2, 0}, {true}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto row_s0_0 = syn0({0,1, 0,0}, true);
auto row_s0_1 = syn0({1,2, 0,0}, true);
@ -339,7 +336,7 @@ TEST_F(NlpTests, basic_cb_ns_test_1) {
ASSERT_EQ(exp0, row_s0_2);
ASSERT_EQ(exp2, row_s1_6);
delete result;
}
TEST_F(NlpTests, test_sg_hs_batch_1) {
@ -372,7 +369,7 @@ TEST_F(NlpTests, test_sg_hs_batch_1) {
sd::ops::skipgram op;
auto result = op.evaluate({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false, true}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto row0 = syn0({0,1, 0,0}, true);
auto row1 = syn1({1,2, 0,0}, true);
@ -382,7 +379,7 @@ TEST_F(NlpTests, test_sg_hs_batch_1) {
ASSERT_TRUE(exp1.equalsTo(row1, 1e-6));
ASSERT_TRUE(exp2.equalsTo(row2, 1e-6));
delete result;
}
TEST_F(NlpTests, test_sg_ns_batch_1) {
@ -416,9 +413,9 @@ TEST_F(NlpTests, test_sg_ns_batch_1) {
sd::ops::skipgram op;
auto result = op.evaluate({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {4, 5}, {false, true}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
delete result;
}
TEST_F(NlpTests, test_cbow_hs_batch_1) {
@ -449,7 +446,7 @@ TEST_F(NlpTests, test_cbow_hs_batch_1) {
sd::ops::cbow op;
auto result = op.evaluate({&target, &ngStarter, &context, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &numWords, &locked, &inferenceVector}, {}, {}, {true}, {}, true);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
@ -474,5 +471,4 @@ TEST_F(NlpTests, test_cbow_hs_batch_1) {
ASSERT_EQ(exp1, row_s1_5);
ASSERT_EQ(exp2, row_s1_6);
delete result;
}

462
libnd4j/tests_cpu/layers_tests/ParityOpsTests.cpp
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File diff suppressed because it is too large Load Diff

145
libnd4j/tests_cpu/layers_tests/RNGTests.cpp
View File

@ -260,9 +260,9 @@ TEST_F(RNGTests, Test_Gaussian_21) {
auto result = op.evaluate({&x0}, {}, {});
//x0.printIndexedBuffer("X0 Normal");
//x1.printIndexedBuffer("X1 Normal");
ASSERT_TRUE(result->status() == Status::OK());
auto mean = result->at(0);
auto variance = result->at(1);
ASSERT_TRUE(result.status() == Status::OK());
auto mean = result.at(0);
auto variance = result.at(1);
// mean->printIndexedBuffer("Mean");
// variance->printIndexedBuffer("Variance");
@ -270,7 +270,7 @@ TEST_F(RNGTests, Test_Gaussian_21) {
ASSERT_NEAR(sd::math::nd4j_abs(mean->e<float>(0)), 0.f, 0.2f);
ASSERT_NEAR(variance->e<float>(0), 1.0f, 0.2f);
delete result;
}
#ifdef DEBUG_BUILD
@ -292,15 +292,15 @@ TEST_F(RNGTests, Test_Gaussian_22) {
auto result = op.evaluate({&x0}, {}, {});
//x0.printIndexedBuffer("X0 Normal");
//x1.printIndexedBuffer("X1 Normal");
ASSERT_TRUE(result->status() == Status::OK());
auto mean0 = result->at(0);
auto variance0 = result->at(1);
ASSERT_TRUE(result.status() == Status::OK());
auto mean0 = result.at(0);
auto variance0 = result.at(1);
//mean0->printIndexedBuffer("Mean");
//variance0->printIndexedBuffer("Variance");
ASSERT_NEAR(sd::math::nd4j_abs(mean0->e<float>(0)), 0.f, 1.0e-3f);
ASSERT_NEAR(variance0->e<float>(0), 1.0f, 1.e-3f);
delete result;
}
TEST_F(RNGTests, Test_Gaussian_3) {
@ -413,18 +413,17 @@ TEST_F(RNGTests, Test_Truncated_21) {
ASSERT_NEAR(deviation.e<float>(0), 2.f, 0.5);
sd::ops::moments op;
auto result = op.evaluate({&x0}, {}, {}, {}, {}, false);
// result->at(0)->printBuffer("MEAN");
// result->at(1)->printBuffer("VARIANCE");
delete result;
// result.at(0)->printBuffer("MEAN");
// result.at(1)->printBuffer("VARIANCE");
sd::ops::reduce_min minOp;
sd::ops::reduce_max maxOp;
auto minRes = minOp.evaluate({&x1}, {}, {}, {});
auto maxRes = maxOp.evaluate({&x0}, {}, {}, {});
// minRes->at(0)->printBuffer("MIN for Truncated");
// maxRes->at(0)->printBuffer("MAX for Truncated");
delete minRes;
delete maxRes;
}
TEST_F(RNGTests, Test_Truncated_22) {
@ -460,18 +459,15 @@ TEST_F(RNGTests, Test_Truncated_22) {
ASSERT_NEAR(deviation.e<float>(0), 4.f, 0.52);
sd::ops::moments op;
auto result = op.evaluate({&x0}, {}, {}, {}, {}, false);
// result->at(0)->printBuffer("MEAN");
// result->at(1)->printBuffer("VARIANCE");
delete result;
sd::ops::reduce_min minOp;
sd::ops::reduce_max maxOp;
auto minRes = minOp.evaluate({&x1}, {}, {}, {});
auto maxRes = maxOp.evaluate({&x0}, {}, {}, {});
// minRes->at(0)->printBuffer("MIN for Truncated2");
// maxRes->at(0)->printBuffer("MAX for Truncated2");
delete minRes;
delete maxRes;
}
TEST_F(RNGTests, Test_Truncated_23) {
@ -509,16 +505,14 @@ TEST_F(RNGTests, Test_Truncated_23) {
auto result = op.evaluate({&x0});
// result->at(0)->printBuffer("MEAN");
// result->at(1)->printBuffer("VARIANCE");
delete result;
sd::ops::reduce_min minOp;
sd::ops::reduce_max maxOp;
auto minRes = minOp.evaluate({&x1}, {}, {}, {});
auto maxRes = maxOp.evaluate({&x0}, {}, {}, {});
// minRes->at(0)->printBuffer("MIN for Truncated3");
// maxRes->at(0)->printBuffer("MAX for Truncated3");
delete minRes;
delete maxRes;
}
TEST_F(RNGTests, Test_Truncated_3) {
@ -568,15 +562,15 @@ TEST_F(RNGTests, Test_Uniform_2) {
auto op = new sd::ops::LegacyRandomOp(0);
auto result = op->execute(_rngA, {&input}, {1.0f, 2.0f}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(x1.isSameShape(z));
ASSERT_TRUE(x1.equalsTo(z));
delete op;
delete result;
}
TEST_F(RNGTests, Test_Gaussian_2) {
@ -588,15 +582,15 @@ TEST_F(RNGTests, Test_Gaussian_2) {
auto op = new sd::ops::LegacyRandomOp(random::GaussianDistribution);
auto result = op->execute(_rngA, {&input}, {1.0f, 2.0f}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(x1.isSameShape(z));
ASSERT_TRUE(x1.equalsTo(z));
delete op;
delete result;
}
TEST_F(RNGTests, Test_LogNorm_2) {
@ -608,15 +602,15 @@ TEST_F(RNGTests, Test_LogNorm_2) {
auto op = new sd::ops::LegacyRandomOp(random::LogNormalDistribution);
auto result = op->execute(_rngA, {&input}, {1.0f, 2.0f}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(x1.isSameShape(z));
ASSERT_TRUE(x1.equalsTo(z));
delete op;
delete result;
}
TEST_F(RNGTests, Test_TruncatedNorm_2) {
@ -628,14 +622,14 @@ TEST_F(RNGTests, Test_TruncatedNorm_2) {
auto op = new sd::ops::LegacyRandomOp(random::TruncatedNormalDistribution);
auto result = op->execute(_rngA, {&input}, {1.0f, 2.0f}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(x1.isSameShape(z));
ASSERT_TRUE(x1.equalsTo(z));
delete op;
delete result;
}
@ -648,15 +642,15 @@ TEST_F(RNGTests, Test_Binomial_2) {
auto op = new sd::ops::LegacyRandomOp(random::BinomialDistributionEx);
auto result = op->execute(_rngA, {&input}, {0.5f}, {3});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(x1.isSameShape(z));
ASSERT_TRUE(x1.equalsTo(z));
delete op;
delete result;
}
@ -669,15 +663,15 @@ TEST_F(RNGTests, Test_Bernoulli_2) {
auto op = new sd::ops::LegacyRandomOp(random::BernoulliDistribution);
auto result = op->execute(_rngA, {&input}, {0.5f}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(x1.isSameShape(z));
ASSERT_TRUE(x1.equalsTo(z));
delete op;
delete result;
}
TEST_F(RNGTests, Test_GaussianDistribution_1) {
@ -687,9 +681,9 @@ TEST_F(RNGTests, Test_GaussianDistribution_1) {
sd::ops::random_normal op;
auto result = op.evaluate({&x}, {0.0, 1.0f}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
@ -698,7 +692,7 @@ TEST_F(RNGTests, Test_GaussianDistribution_1) {
ASSERT_FALSE(nexp1->equalsTo(z));
ASSERT_FALSE(nexp2->equalsTo(z));
delete result;
}
TEST_F(RNGTests, Test_BernoulliDistribution_1) {
@ -708,9 +702,9 @@ TEST_F(RNGTests, Test_BernoulliDistribution_1) {
sd::ops::random_bernoulli op;
auto result = op.evaluate({&x}, {0.5f}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_FALSE(exp0.equalsTo(z));
@ -718,7 +712,7 @@ TEST_F(RNGTests, Test_BernoulliDistribution_1) {
ASSERT_FALSE(nexp1->equalsTo(z));
ASSERT_FALSE(nexp2->equalsTo(z));
delete result;
}
@ -729,9 +723,9 @@ TEST_F(RNGTests, Test_ExponentialDistribution_1) {
sd::ops::random_exponential op;
auto result = op.evaluate({&x}, {0.25f}, {0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
@ -740,7 +734,7 @@ TEST_F(RNGTests, Test_ExponentialDistribution_1) {
ASSERT_FALSE(nexp1->equalsTo(z));
ASSERT_FALSE(nexp2->equalsTo(z));
delete result;
}
TEST_F(RNGTests, Test_ExponentialDistribution_2) {
@ -753,9 +747,9 @@ TEST_F(RNGTests, Test_ExponentialDistribution_2) {
sd::ops::random_exponential op;
auto result = op.evaluate({&x, &y}, {0.25f}, {0});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
@ -764,7 +758,7 @@ TEST_F(RNGTests, Test_ExponentialDistribution_2) {
ASSERT_FALSE(nexp1->equalsTo(z));
ASSERT_FALSE(nexp2->equalsTo(z));
delete result;
}
TEST_F(RNGTests, Test_PoissonDistribution_1) {
@ -777,14 +771,14 @@ TEST_F(RNGTests, Test_PoissonDistribution_1) {
sd::ops::random_poisson op;
auto result = op.evaluate({&x, &la}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printIndexedBuffer("Poisson distribution");
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
delete result;
}
TEST_F(RNGTests, Test_GammaDistribution_1) {
@ -797,14 +791,14 @@ TEST_F(RNGTests, Test_GammaDistribution_1) {
sd::ops::random_gamma op;
auto result = op.evaluate({&x, &al}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printIndexedBuffer("Gamma distribution");
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
delete result;
}
TEST_F(RNGTests, Test_GammaDistribution_2) {
@ -818,14 +812,14 @@ TEST_F(RNGTests, Test_GammaDistribution_2) {
sd::ops::random_gamma op;
auto result = op.evaluate({&x, &al, &be}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printIndexedBuffer("Gamma distribution");
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
delete result;
}
TEST_F(RNGTests, Test_GammaDistribution_3) {
@ -839,14 +833,14 @@ TEST_F(RNGTests, Test_GammaDistribution_3) {
sd::ops::random_gamma op;
auto result = op.evaluate({&x, &al, &be}, {}, {});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printIndexedBuffer("Gamma distribution");
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
delete result;
}
TEST_F(RNGTests, Test_UniformDistribution_04) {
@ -858,13 +852,13 @@ TEST_F(RNGTests, Test_UniformDistribution_04) {
sd::ops::randomuniform op;
auto result = op.evaluate({&x, &al, &be}, {}, {DataType::INT32});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp0.isSameShape(z));
ASSERT_FALSE(exp0.equalsTo(z));
delete result;
}
namespace sd {
@ -1021,12 +1015,12 @@ TEST_F(RNGTests, test_multinomial_1) {
NDArray expectedZ('c', { 3, 3 }, { 0., 0, 0, 0, 0, 0, 0, 0, 0 }, sd::DataType::INT64);
auto result = op.evaluate({ &probsZ, &samples }, { }, { 1, INT64 });
auto outputZ = result->at(0);
auto outputZ = result.at(0);
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
ASSERT_TRUE(expectedZ.isSameShape(outputZ));
ASSERT_TRUE(expectedZ.equalsTo(outputZ));
delete result;
}
TEST_F(RNGTests, test_multinomial_2) {
@ -1117,8 +1111,8 @@ TEST_F(RNGTests, test_multinomial_5) {
}
auto resultR = op.evaluate({ &probs, &samples }, { }, { 1 });
auto outputR = resultR->at(0);
ASSERT_EQ(Status::OK(), resultR->status());
auto outputR = resultR.at(0);
ASSERT_EQ(Status::OK(), resultR.status());
deviation = outputR->varianceNumber(variance::SummaryStatsStandardDeviation, false);
mean = outputR->meanNumber();
@ -1131,7 +1125,6 @@ TEST_F(RNGTests, test_multinomial_5) {
ASSERT_TRUE(value >= 0 && value < ClassValue);
}
delete resultR;
}
@ -1150,8 +1143,8 @@ TEST_F(RNGTests, test_multinomial_6) {
NDArray probsR('c', { batchValue, ClassValue }, { 1., 1.5, 2., 2.5, 3. }, sd::DataType::FLOAT32);
auto resultR = op.evaluate({ &probsR, &samples }, { }, { 0 });
auto outputR = resultR->at(0);
ASSERT_EQ(Status::OK(), resultR->status());
auto outputR = resultR.at(0);
ASSERT_EQ(Status::OK(), resultR.status());
NDArray countsR('c', { ClassValue }, { 0., 0, 0, 0, 0 }, sd::DataType::DOUBLE);
@ -1175,7 +1168,7 @@ TEST_F(RNGTests, test_multinomial_6) {
ASSERT_NEAR(1.2175, deviation.e<double>(0), 45e-3); // 1000000 35e-3);
ASSERT_NEAR(2.906, mean.e<double>(0), 45e-3); // 1000000 35e-3);
delete resultR;
RandomGenerator rng(1234, 1234);
NDArray probs('c', { batchValue, ClassValue }, { 1., 1.5, 2., 2.5, 3. }, sd::DataType::FLOAT32);

52
libnd4j/tests_cpu/layers_tests/ScalarTests.cpp
View File

@ -96,14 +96,14 @@ TEST_F(ScalarTests, Test_Concat_1) {
sd::ops::concat op;
auto result = op.evaluate({&t, &u, &v}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -116,15 +116,15 @@ TEST_F(ScalarTests, Test_Concat_2) {
sd::ops::concat op;
auto result = op.evaluate({&t, &u, &v}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
// z->printIndexedBuffer();
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -137,16 +137,16 @@ TEST_F(ScalarTests, Test_Concat_3) {
sd::ops::concat op;
auto result = op.evaluate({&t, &u, &v}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
//z->printShapeInfo("z");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ScalarTests, Test_ExpandDims_1) {
@ -156,14 +156,14 @@ TEST_F(ScalarTests, Test_ExpandDims_1) {
sd::ops::expand_dims op;
auto result = op.evaluate({&x}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ScalarTests, Test_Squeeze_1) {
@ -172,14 +172,14 @@ TEST_F(ScalarTests, Test_Squeeze_1) {
sd::ops::squeeze op;
auto result = op.evaluate({&x}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -189,14 +189,14 @@ TEST_F(ScalarTests, Test_Reshape_1) {
sd::ops::reshape op;
auto result = op.evaluate({&x}, {}, {-99, 1, 1, 1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -206,14 +206,14 @@ TEST_F(ScalarTests, Test_Permute_1) {
sd::ops::permute op;
auto result = op.evaluate({&x}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ScalarTests, Test_Concat_Scalar_1) {
@ -225,14 +225,13 @@ TEST_F(ScalarTests, Test_Concat_Scalar_1) {
sd::ops::concat op;
auto result = op.evaluate({&t, &u, &v, &w}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -245,12 +244,11 @@ TEST_F(ScalarTests, Test_Concat_Scalar_2) {
sd::ops::concat op;
auto result = op.evaluate({&t, &u, &v, &w}, {}, {1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}

5
libnd4j/tests_cpu/layers_tests/ShapeTests.cpp
View File

@ -308,14 +308,13 @@ TEST_F(ShapeTests, Tests_Transpose_119_2) {
sd::ops::transpose op;
auto result = op.evaluate({&x});
ASSERT_EQ(Status::OK(), result->status());
ASSERT_EQ(Status::OK(), result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(ShapeTests, Tests_Transpose_119_3) {

48
libnd4j/tests_cpu/layers_tests/SingleDimTests.cpp
View File

@ -70,14 +70,14 @@ TEST_F(SingleDimTests, Test_Concat_1) {
sd::ops::concat op;
auto result = op.evaluate({&x, &y}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(SingleDimTests, Test_Reduce_1) {
@ -104,14 +104,14 @@ TEST_F(SingleDimTests, Test_ExpandDims_1) {
sd::ops::expand_dims op;
auto result = op.evaluate({&x}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -122,14 +122,14 @@ TEST_F(SingleDimTests, Test_ExpandDims_2) {
sd::ops::expand_dims op;
auto result = op.evaluate({&x}, {}, {1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -142,14 +142,14 @@ TEST_F(SingleDimTests, Test_Squeeze_1) {
sd::ops::squeeze op;
auto result = op.evaluate({&x}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_EQ(exp.rankOf(), z->rankOf());
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(SingleDimTests, Test_Squeeze_2) {
@ -158,14 +158,14 @@ TEST_F(SingleDimTests, Test_Squeeze_2) {
sd::ops::squeeze op;
auto result = op.evaluate({&x}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(SingleDimTests, Test_Reshape_1) {
@ -174,14 +174,14 @@ TEST_F(SingleDimTests, Test_Reshape_1) {
sd::ops::reshape op;
auto result = op.evaluate({&x}, {}, {-99, 3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(SingleDimTests, Test_Reshape_2) {
@ -190,14 +190,14 @@ TEST_F(SingleDimTests, Test_Reshape_2) {
sd::ops::reshape op;
auto result = op.evaluate({&x}, {}, {-99, 1, 3});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
@ -207,12 +207,12 @@ TEST_F(SingleDimTests, Test_Permute_1) {
sd::ops::permute op;
auto result = op.evaluate({&x}, {}, {0});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_EQ(ND4J_STATUS_OK, result.status());
auto z = result->at(0);
auto z = result.at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}