Refactor Layer interface to return size of weights and biases instead of Tensor references

src/layers/activation.cpp

@@ -59,8 +59,12 @@ size_t Activation::output_size() {
 
 void Activation::set_weights(void *input) {}
 
-CUDANet::Tensor& Activation::get_weights() {}
+size_t Activation::get_weights_size() {
+    return 0;
+}
 
 void Activation::set_biases(void *input) {}
 
-CUDANet::Tensor& Activation::get_biases() {}
+size_t Activation::get_biases_size() {
+    return 0;
+}

src/layers/avg_pooling.cpp

@@ -81,11 +81,15 @@ size_t AvgPool2d::output_size() {
 
 void AvgPool2d::set_weights(void* input) {}
 
-CUDANet::Tensor& AvgPool2d::get_weights() {}
+size_t AvgPool2d::get_weights_size() {
+    return 0;
+}
 
 void AvgPool2d::set_biases(void* input) {}
 
-CUDANet::Tensor& AvgPool2d::get_biases() {}
+size_t AvgPool2d::get_biases_size() {
+    return 0;
+}
 
 
 AdaptiveAvgPool2d::AdaptiveAvgPool2d(

src/layers/batch_norm.cpp

@@ -74,16 +74,16 @@ void BatchNorm2d::set_weights(void* input) {
     weights.set_data<float>(static_cast<float*>(input));
 }
 
-CUDANet::Tensor& BatchNorm2d::get_weights() {
-    return weights;
+size_t BatchNorm2d::get_weights_size() {
+    return weights.size();
 }
 
 void BatchNorm2d::set_biases(void* input) {
     biases.set_data<float>(static_cast<float*>(input));
 }
 
-CUDANet::Tensor& BatchNorm2d::get_biases() {
-    return biases;
+size_t BatchNorm2d::get_biases_size() {
+    return biases.size();
 }
 
 void BatchNorm2d::set_running_mean(void* input) {

src/layers/conv2d.cpp

@@ -96,16 +96,16 @@ void Conv2d::set_weights(void* input) {
     weights.set_data<float>(static_cast<float*>(input));
 }
 
-CUDANet::Tensor& Conv2d::get_weights() {
-    return weights;
+size_t Conv2d::get_weights_size() {
+    return weights.size();
 }
 
 void Conv2d::set_biases(void* input) {
     biases.set_data<float>(static_cast<float*>(input));
 }
 
-CUDANet::Tensor& Conv2d::get_biases() {
-    return biases;
+size_t Conv2d::get_biases_size() {
+    return biases.size();
 }
 
 CUDANet::Shape Conv2d::get_padding_shape() {

src/layers/dense.cpp

@@ -55,14 +55,14 @@ void Dense::set_weights(void* input) {
     weights.set_data<float>(static_cast<float*>(input));
 }
 
-CUDANet::Tensor& Dense::get_weights() {
-    return weights;
+size_t Dense::get_weights_size() {
+    return weights.size();
 }
 
 void Dense::set_biases(void* input) {
     biases.set_data<float>(static_cast<float*>(input));
 }
 
-CUDANet::Tensor& Dense::get_biases() {
-    return biases;
+size_t Dense::get_biases_size() {
+    return biases.size();
 }

src/layers/max_pool.cpp

@@ -75,8 +75,12 @@ size_t MaxPool2d::output_size() {
 
 void MaxPool2d::set_weights(void* input) {}
 
-CUDANet::Tensor& MaxPool2d::get_weights() {}
+size_t MaxPool2d::get_weights_size() {
+    return 0;
+}
 
 void MaxPool2d::set_biases(void* input) {}
 
-CUDANet::Tensor& MaxPool2d::get_biases() {}
+size_t MaxPool2d::get_biases_size() {
+    return 0;
+}

src/model.cpp

@@ -128,20 +128,20 @@ void Model::load_weights(const std::string& path) {
             Layer* layer = layer_map[tensor_info.name];
 
             if (tensor_info.type == TensorType::WEIGHT) {
-                if (layer->get_weights().size() != values.size()) {
+                if (layer->get_weights_size() != values.size()) {
                     std::cerr << "Layer: " << tensor_info.name
                               << " has incorrect number of weights, expected "
-                              << layer->get_weights().size() << " but got "
+                              << layer->get_weights_size() << " but got "
                               << values.size() << ", skipping" << std::endl;
                     continue;
                 }
 
                 layer->set_weights(values.data());
             } else if (tensor_info.type == TensorType::BIAS) {
-                if (layer->get_biases().size() != values.size()) {
+                if (layer->get_biases_size() != values.size()) {
                     std::cerr << "Layer: " << tensor_info.name
                               << " has incorrect number of biases, expected "
-                              << layer->get_biases().size() << " but got "
+                              << layer->get_biases_size() << " but got "
                               << values.size() << ", skipping" << std::endl;
                     continue;
                 }