From 7896ff0e24c37c26ea1889fe4a6ec451132b0b3b Mon Sep 17 00:00:00 2001
From: LordMathis <matus@namesny.com>
Date: Wed, 19 Nov 2025 20:37:41 +0100
Subject: [PATCH] Remove const from layer input

---
 include/layer.hpp                  |  2 +-
 include/layers/conv2d.hpp          |  2 +-
 include/layers/dense.hpp           |  2 +-
 src/backends/cuda/layers/conv2d.cu | 53 ------------------------------
 src/layers/conv2d.cpp              |  2 +-
 src/layers/dense.cpp               |  2 +-
 6 files changed, 5 insertions(+), 58 deletions(-)
 delete mode 100644 src/backends/cuda/layers/conv2d.cu

diff --git a/include/layer.hpp b/include/layer.hpp
index 77d50de..5b02346 100644
--- a/include/layer.hpp
+++ b/include/layer.hpp
@@ -20,7 +20,7 @@ class Layer {
 
     virtual ~Layer(){};
 
-    virtual CUDANet::Tensor& forward(const CUDANet::Tensor &input) = 0;
+    virtual CUDANet::Tensor& forward(CUDANet::Tensor &input) = 0;
     
     virtual CUDANet::Shape input_shape() = 0;
 
diff --git a/include/layers/conv2d.hpp b/include/layers/conv2d.hpp
index 6c2f6ba..e3c4954 100644
--- a/include/layers/conv2d.hpp
+++ b/include/layers/conv2d.hpp
@@ -23,7 +23,7 @@ class Conv2d : public Layer {
 
     ~Conv2d() {};
 
-    CUDANet::Tensor& forward(const CUDANet::Tensor& input) override;
+    CUDANet::Tensor& forward(CUDANet::Tensor& input) override;
 
     CUDANet::Shape input_shape() override;
 
diff --git a/include/layers/dense.hpp b/include/layers/dense.hpp
index 5046d8f..41d53f2 100644
--- a/include/layers/dense.hpp
+++ b/include/layers/dense.hpp
@@ -18,7 +18,7 @@ class Dense : public Layer {
 
     ~Dense();
 
-    CUDANet::Tensor& forward(const CUDANet::Tensor &input) override;
+    CUDANet::Tensor& forward(CUDANet::Tensor &input) override;
 
     CUDANet::Shape input_shape() override;
 
diff --git a/src/backends/cuda/layers/conv2d.cu b/src/backends/cuda/layers/conv2d.cu
deleted file mode 100644
index ba66fd7..0000000
--- a/src/backends/cuda/layers/conv2d.cu
+++ /dev/null
@@ -1,53 +0,0 @@
-#include <vector>
-
-#include "activation.hpp"
-#include "conv2d.hpp"
-#include "convolution.cuh"
-#include "cuda_helper.cuh"
-#include "layer.hpp"
-#include "matmul.cuh"
-#include "vector.cuh"
-
-using namespace CUDANet::Layers;
-
-void Conv2d::initCUDA() {
-    d_output = nullptr;
-    CUDA_CHECK(cudaMalloc(
-        (void**)&d_output,
-        sizeof(float) * outputSize.first * outputSize.second * numFilters
-    ));
-
-    d_weights = nullptr;
-    CUDA_CHECK(cudaMalloc(
-        (void**)&d_weights, sizeof(float) * kernelSize.first *
-                                kernelSize.second * inputChannels * numFilters
-    ));
-
-    d_biases = nullptr;
-    CUDA_CHECK(cudaMalloc((void**)&d_biases, sizeof(float) * numFilters));
-}
-
-void Conv2d::delCUDA() {
-    cudaFree(d_output);
-    cudaFree(d_weights);
-    cudaFree(d_biases);
-}
-
-void Conv2d::toCuda() {
-    CUDA_CHECK(cudaMemcpy(
-        d_weights, weights.data(),
-        sizeof(float) * kernelSize.first * kernelSize.second * inputChannels *
-            numFilters,
-        cudaMemcpyHostToDevice
-    ));
-
-    CUDA_CHECK(cudaMemcpy(
-        d_biases, biases.data(), sizeof(float) * numFilters,
-        cudaMemcpyHostToDevice
-    ));
-}
-
-float* Conv2d::forwardCUDA(const float* d_input) {
-    // Convolve
-
-}
diff --git a/src/layers/conv2d.cpp b/src/layers/conv2d.cpp
index 5172188..d3e8f6d 100644
--- a/src/layers/conv2d.cpp
+++ b/src/layers/conv2d.cpp
@@ -83,7 +83,7 @@ Conv2d::Conv2d(
 
 Conv2d::~Conv2d() {}
 
-CUDANet::Tensor& Conv2d::forward(const CUDANet::Tensor& input) {
+CUDANet::Tensor& Conv2d::forward(CUDANet::Tensor& input) {
     output.zero();
     backend->conv2d(
         weights,
diff --git a/src/layers/dense.cpp b/src/layers/dense.cpp
index d0aa6a3..57cf5e2 100644
--- a/src/layers/dense.cpp
+++ b/src/layers/dense.cpp
@@ -33,7 +33,7 @@ Dense::Dense(CUDANet::Shape in, CUDANet::Shape out, CUDANet::Backend* backend)
 
 Dense::~Dense() {}
 
-CUDANet::Tensor& Dense::forward(const CUDANet::Tensor& input) {
+CUDANet::Tensor& Dense::forward(CUDANet::Tensor& input) {
     backend->dense(weights, biases, input, output, in_shape[0], out_shape[0]);
     return output;
 }