forward working, not working backward

Author: kemsig

.vscode/c_cpp_properties.json

@@ -0,0 +1,16 @@
+{
+    "configurations": [
+        {
+            "name": "Linux",
+            "includePath": [
+                "${workspaceFolder}/**"
+            ],
+            "defines": [],
+            "compilerPath": "/usr/bin/gcc",
+            "cStandard": "c17",
+            "cppStandard": "gnu++17",
+            "intelliSenseMode": "linux-gcc-x64"
+        }
+    ],
+    "version": 4
+}

include/TensorSANN/activations/ReLU.hpp

@@ -7,7 +7,7 @@
 
 namespace TensorSANN {
 
-class ReLU : Layer{
+class ReLU : public Layer{
 public:
     Tensor forward(const Tensor &input) override;
 

include/TensorSANN/activations/Softmax.hpp

@@ -7,7 +7,7 @@
 
 namespace TensorSANN {
 
-class Softmax : Layer{
+class Softmax : public Layer{
 public:
 
     Tensor forward(const Tensor &input) override;

src/model_main.cpp

@@ -1,21 +1,55 @@
 #include <iostream>
+#include <vector>
+#include <memory>
+
 #include "TensorSANN/utils/Tensor.hpp"
 #include "TensorSANN/layers/DenseLayer.hpp"
+#include "TensorSANN/layers/Layer.hpp"
 
 #include "TensorSANN/activations/Softmax.hpp"
 #include "TensorSANN/activations/ReLU.hpp"
 #include "TensorSANN/optimizers/SGD.hpp"
 
 int main() {
     std::cout << "MODEL MAIN CPP ==========" << std::endl;
-    TensorSANN::SGD optimizer = TensorSANN::SGD(0.01f);
-
+    
 
     std::vector<size_t> shape2 = {4,2};  // 2x3 tensor
     std::vector<float> data = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0};  // Initialize with values
     TensorSANN::Tensor input_tensor(shape2, data);
 
     TensorSANN::DenseLayer dense1(4, 2);
+    TensorSANN::ReLU relu;
+    TensorSANN::DenseLayer dense2(2, 1);
+    TensorSANN::Softmax smax;
+
+    std::vector<std::shared_ptr<TensorSANN::Layer>> layers;
+    layers.push_back(std::make_shared<TensorSANN::DenseLayer>(4, 2));
+    layers.push_back(std::make_shared<TensorSANN::ReLU>());
+    layers.push_back(std::make_shared<TensorSANN::DenseLayer>(2, 1));
+    layers.push_back(std::make_shared<TensorSANN::Softmax>());
+    
+    TensorSANN::Tensor fwd_op = input_tensor.transpose();
+
+    // fwd
+    for (auto &layer : layers){
+        fwd_op = layer->forward(fwd_op);
+        std::cout << "LOOP FWD==" << fwd_op.to_string() << std::endl;
+    }
+
+    TensorSANN::SGD optimizer = TensorSANN::SGD(0.01f);
+
+    // calculate loss
+    TensorSANN::Tensor loss_grad = fwd_op - 1;
+
+    // bkwd
+    for (int i = layers.size(); i >= 0; --i){
+        std::cout << i << std::endl;
+        layers[i]->backward(loss_grad);
+    }
+    
+
+    
     const TensorSANN::Tensor d1w = dense1.weights();
     const TensorSANN::Tensor d1b = dense1.biases();
 
@@ -25,14 +59,18 @@ int main() {
 
     TensorSANN::Tensor f1 = dense1.forward(input_tensor.transpose());
     std::cout << f1.to_string() << std::endl;
+
+    
+    TensorSANN::Tensor r1 = relu.forward(f1);
+    std::cout << r1.to_string() << std::endl;
+
 
-    TensorSANN::Softmax smax;
 
-    TensorSANN::Tensor f2 = smax.forward(f1);
+    TensorSANN::Tensor f2 = dense2.forward(r1);
     std::cout << f2.to_string() << std::endl;
 
-    TensorSANN::Tensor b2 = smax.backward(f2);
-    std::cout << b2.to_string() << std::endl;
+    TensorSANN::Tensor s1 = smax.forward(f2);
+    std::cout << (s1 - 1).to_string() << std::endl;
 
     return 0;