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Updated tests to use new constraints on unique default operations

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This commit is contained in:
Alejandro Saucedo 2020-10-18 16:04:52 +01:00
parent ba71c7ab46
commit 7679070274
3 changed files with 103 additions and 97 deletions
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108
test/TestLogisticRegression.cpp
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@ -31,38 +31,38 @@ TEST(TestLogisticRegressionAlgorithm, TestMainLogisticRegression)
{
kp::Manager mgr;
if (std::shared_ptr<kp::Sequence> sq =
mgr.getOrCreateManagedSequence("createTensors").lock()) {
std::shared_ptr<kp::Sequence> sqTensor =
mgr.createManagedSequence().lock();
sq->begin();
sqTensor->begin();
sqTensor->record<kp::OpTensorCreate>(params);
sqTensor->end();
sqTensor->eval();
sq->record<kp::OpTensorCreate>(params);
std::shared_ptr<kp::Sequence> sq =
mgr.createManagedSequence().lock();
// Record op algo base
sq->begin();
sq->record<kp::OpTensorSyncDevice>({ wIn, bIn });
sq->record<kp::OpAlgoBase<>>(
params, "test/shaders/glsl/test_logistic_regression.comp");
sq->record<kp::OpTensorSyncLocal>({ wOutI, wOutJ, bOut, lOut });
sq->end();
// Iterate across all expected iterations
for (size_t i = 0; i < ITERATIONS; i++) {
sq->end();
sq->eval();
// Record op algo base
sq->begin();
sq->record<kp::OpTensorSyncDevice>({ wIn, bIn });
sq->record<kp::OpAlgoBase<>>(
params, "test/shaders/glsl/test_logistic_regression.comp");
sq->record<kp::OpTensorSyncLocal>({ wOutI, wOutJ, bOut, lOut });
sq->end();
// Iterate across all expected iterations
for (size_t i = 0; i < ITERATIONS; i++) {
sq->eval();
for (size_t j = 0; j < bOut->size(); j++) {
wIn->data()[0] -= learningRate * wOutI->data()[j];
wIn->data()[1] -= learningRate * wOutJ->data()[j];
bIn->data()[0] -= learningRate * bOut->data()[j];
}
for (size_t j = 0; j < bOut->size(); j++) {
wIn->data()[0] -= learningRate * wOutI->data()[j];
wIn->data()[1] -= learningRate * wOutJ->data()[j];
bIn->data()[0] -= learningRate * bOut->data()[j];
}
}
}
@ -115,39 +115,39 @@ TEST(TestLogisticRegressionAlgorithm, TestMainLogisticRegressionManualCopy)
{
kp::Manager mgr;
if (std::shared_ptr<kp::Sequence> sq =
mgr.getOrCreateManagedSequence("createTensors").lock()) {
std::shared_ptr<kp::Sequence> sqTensor =
mgr.createManagedSequence().lock();
sq->begin();
sqTensor->begin();
sqTensor->record<kp::OpTensorCreate>(params);
sqTensor->end();
sqTensor->eval();
sq->record<kp::OpTensorCreate>(params);
std::shared_ptr<kp::Sequence> sq =
mgr.createManagedSequence().lock();
// Record op algo base
sq->begin();
sq->record<kp::OpAlgoBase<>>(
params, "test/shaders/glsl/test_logistic_regression.comp");
sq->record<kp::OpTensorSyncLocal>({ wOutI, wOutJ, bOut, lOut });
sq->end();
// Iterate across all expected iterations
for (size_t i = 0; i < ITERATIONS; i++) {
sq->end();
sq->eval();
// Record op algo base
sq->begin();
sq->record<kp::OpAlgoBase<>>(
params, "test/shaders/glsl/test_logistic_regression.comp");
sq->record<kp::OpTensorSyncLocal>({ wOutI, wOutJ, bOut, lOut });
sq->end();
// Iterate across all expected iterations
for (size_t i = 0; i < ITERATIONS; i++) {
sq->eval();
for (size_t j = 0; j < bOut->size(); j++) {
wIn->data()[0] -= learningRate * wOutI->data()[j];
wIn->data()[1] -= learningRate * wOutJ->data()[j];
bIn->data()[0] -= learningRate * bOut->data()[j];
}
wIn->mapDataIntoHostMemory();
bIn->mapDataIntoHostMemory();
for (size_t j = 0; j < bOut->size(); j++) {
wIn->data()[0] -= learningRate * wOutI->data()[j];
wIn->data()[1] -= learningRate * wOutJ->data()[j];
bIn->data()[0] -= learningRate * bOut->data()[j];
}
wIn->mapDataIntoHostMemory();
bIn->mapDataIntoHostMemory();
}
}