Added functional optensorsyncDevice and optensorsynclocal

test/TestLogisticRegression.cpp

@@ -1,9 +1,89 @@
 
 #include "gtest/gtest.h"
 
+#include "fmt/ranges.h"
 #include "kompute/Kompute.hpp"
 
-TEST(LogisticRegressionAlgorithm, TestMainLogisticRegression) {
+TEST(TestLogisticRegressionAlgorithm, TestMainLogisticRegression) {
+
+    uint32_t ITERATIONS = 100;
+
+    std::vector<float> wInVec = { 0.001, 0.001 };
+    std::vector<float> bInVec = { 0 };
+
+    std::shared_ptr<kp::Tensor> xI{ new kp::Tensor({ 0, 1, 1, 1, 1 })};
+    std::shared_ptr<kp::Tensor> xJ{ new kp::Tensor({ 0, 0, 0, 1, 1 })};
+
+    std::shared_ptr<kp::Tensor> y{ new kp::Tensor({ 0, 0, 0, 1, 1 })};
+
+    std::shared_ptr<kp::Tensor> wIn{ 
+        new kp::Tensor(wInVec)};
+    std::shared_ptr<kp::Tensor> wOutI{ new kp::Tensor({ 0, 0, 0, 0, 0 })};
+    std::shared_ptr<kp::Tensor> wOutJ{ new kp::Tensor({ 0, 0, 0, 0, 0 })};
+
+    std::shared_ptr<kp::Tensor> bIn{ 
+        new kp::Tensor(bInVec)};
+    std::shared_ptr<kp::Tensor> bOut{ new kp::Tensor({ 0, 0, 0, 0, 0 })};
+
+    std::vector<std::shared_ptr<kp::Tensor>> params = 
+        {xI, xJ, y, wIn, wOutI, wOutJ, bIn, bOut};
+
+    {
+        kp::Manager mgr;
+
+        if (std::shared_ptr<kp::Sequence> sq = 
+                mgr.getOrCreateManagedSequence("createTensors").lock()) {
+
+            sq->begin();
+
+            sq->record<kp::OpTensorCreate>(params);
+
+            sq->end();
+            sq->eval();
+
+            // Record op algo base
+            sq->begin();
+
+            sq->record<kp::OpTensorSyncDevice>({wIn, bIn});
+
+            sq->record<kp::OpAlgoBase<>>(
+                    params, 
+                    false, // Whether to copy output from device
+                    "test/shaders/glsl/test_logistic_regression.comp");
+
+            sq->record<kp::OpTensorSyncLocal>({wOutI, wOutJ, bOut});
+
+            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] -= wOutI->data()[j];
+                    wIn->data()[1] -= wOutJ->data()[j];
+                    bIn->data()[0] -= bOut->data()[j];
+                }
+            }
+        }
+    }
+
+
+    // Based on the inputs the outputs should be at least:
+    // * wi < 0.01
+    // * wj > 1.0
+    // * b < 0
+    // TODO: Add EXPECT_DOUBLE_EQ instead
+    EXPECT_LT(wIn->data()[0], 0.01);
+    EXPECT_GT(wIn->data()[1], 1.0);
+    EXPECT_LT(bIn->data()[0], 0.0);
+
+    SPDLOG_ERROR("Result wIn: {}, bIn: {}", 
+            wIn->data(), bIn->data());
+}
+
+TEST(TestLogisticRegressionAlgorithm, TestMainLogisticRegressionManualCopy) {
 
     uint32_t ITERATIONS = 100;
 
@@ -76,6 +156,6 @@ TEST(LogisticRegressionAlgorithm, TestMainLogisticRegression) {
     EXPECT_GT(wIn->data()[1], 1.0);
     EXPECT_LT(bIn->data()[0], 0.0);
 
-    //SPDLOG_DEBUG("Result wIn: {}, bIn: {}", 
-    //        wIn->data(), bIn->data());
+    SPDLOG_ERROR("Result wIn: {}, bIn: {}", 
+            wIn->data(), bIn->data());
 }