Remove const from layer input

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;
 

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;
 

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;
 

src/backends/cuda/layers/conv2d.cu

@@ -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
-
-}

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,

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;
 }