mirror of
https://github.com/lordmathis/CUDANet.git
synced 2025-11-05 17:34:21 +00:00
Add layer name to vector
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@@ -11,7 +11,10 @@
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namespace CUDANet {
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namespace CUDANet {
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enum TensorType { WEIGHT, BIAS, };
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enum TensorType {
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WEIGHT,
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BIAS,
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};
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struct TensorInfo {
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struct TensorInfo {
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std::string name;
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std::string name;
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@@ -42,8 +45,8 @@ class Model {
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int outputSize;
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int outputSize;
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std::vector<Layers::SequentialLayer*> layers;
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std::vector<std::pair<std::string, Layers::SequentialLayer*>> layers;
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std::unordered_map<std::string, Layers::SequentialLayer*> layerMap;
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std::unordered_map<std::string, Layers::SequentialLayer*> layerMap;
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};
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};
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} // namespace CUDANet
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} // namespace CUDANet
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@@ -15,7 +15,7 @@ Model::Model(const int inputSize, const int inputChannels, const int outputSize)
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: inputSize(inputSize),
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: inputSize(inputSize),
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inputChannels(inputChannels),
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inputChannels(inputChannels),
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outputSize(outputSize),
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outputSize(outputSize),
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layers(std::vector<Layers::SequentialLayer*>()),
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layers(std::vector<std::pair<std::string, Layers::SequentialLayer*>>()),
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layerMap(std::unordered_map<std::string, Layers::SequentialLayer*>()) {
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layerMap(std::unordered_map<std::string, Layers::SequentialLayer*>()) {
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inputLayer = new Layers::Input(inputSize * inputSize * inputChannels);
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inputLayer = new Layers::Input(inputSize * inputSize * inputChannels);
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outputLayer = new Layers::Output(outputSize);
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outputLayer = new Layers::Output(outputSize);
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@@ -25,7 +25,7 @@ Model::Model(const Model& other)
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: inputSize(other.inputSize),
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: inputSize(other.inputSize),
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inputChannels(other.inputChannels),
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inputChannels(other.inputChannels),
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outputSize(other.outputSize),
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outputSize(other.outputSize),
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layers(std::vector<Layers::SequentialLayer*>()),
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layers(std::vector<std::pair<std::string, Layers::SequentialLayer*>>()),
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layerMap(std::unordered_map<std::string, Layers::SequentialLayer*>()) {
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layerMap(std::unordered_map<std::string, Layers::SequentialLayer*>()) {
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inputLayer = new Layers::Input(*other.inputLayer);
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inputLayer = new Layers::Input(*other.inputLayer);
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outputLayer = new Layers::Output(*other.outputLayer);
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outputLayer = new Layers::Output(*other.outputLayer);
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@@ -34,8 +34,8 @@ Model::Model(const Model& other)
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Model::~Model() {
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Model::~Model() {
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delete inputLayer;
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delete inputLayer;
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delete outputLayer;
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delete outputLayer;
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for (auto layer : layers) {
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for (const auto& layer : layers) {
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delete layer;
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delete layer.second;
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}
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}
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};
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};
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@@ -43,15 +43,15 @@ float* Model::predict(const float* input) {
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float* d_input = inputLayer->forward(input);
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float* d_input = inputLayer->forward(input);
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for (auto& layer : layers) {
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for (auto& layer : layers) {
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std::cout << layer << std::endl;
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std::cout << layer.first << std::endl;
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d_input = layer->forward(d_input);
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d_input = layer.second->forward(d_input);
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}
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}
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return outputLayer->forward(d_input);
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return outputLayer->forward(d_input);
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}
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}
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void Model::addLayer(const std::string& name, Layers::SequentialLayer* layer) {
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void Model::addLayer(const std::string& name, Layers::SequentialLayer* layer) {
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layers.push_back(layer);
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layers.push_back({ name, layer });
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layerMap[name] = layer;
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layerMap[name] = layer;
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}
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}
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