Merge pull request #29 from Az-r-ow/callbacks

fix: wrapping up callbacks on early exit training

src/NeuralNet/Network.cpp

@@ -57,6 +57,7 @@ double Network::train(std::vector<std::vector<double>> inputs,
   try {
     return onlineTraining(inputs, labels, epochs, callbacks);
   } catch (const std::exception &e) {
+    trainingCheckpoint("onTrainEnd", callbacks);
     std::cerr << "Training Interrupted : " << e.what() << '\n';
     return loss;
   }
@@ -68,6 +69,7 @@ double Network::train(std::vector<std::vector<std::vector<double>>> inputs,
   try {
     return onlineTraining(inputs, labels, epochs, callbacks);
   } catch (const std::exception &e) {
+    trainingCheckpoint("onTrainEnd", callbacks);  // wrap up callbacks
     std::cerr << "Training Interrupted : " << e.what() << '\n';
     return loss;
   }
@@ -81,6 +83,7 @@ double Network::train(
   try {
     return this->trainer(trainingData, epochs, callbacks);
   } catch (const std::exception &e) {
+    trainingCheckpoint("onTrainEnd", callbacks);
     std::cerr << "Training Interrupted : " << e.what() << '\n';
     return loss;
   }
@@ -94,6 +97,7 @@ double Network::train(
   try {
     return this->trainer(trainingData, epochs, callbacks);
   } catch (const std::exception &e) {
+    trainingCheckpoint("onTrainEnd", callbacks);
     std::cerr << "Training Interrupted : " << e.what() << '\n';
     return loss;
   }

src/NeuralNet/Network.hpp

@@ -246,7 +246,8 @@ class Network : public Model {
    * @param epochs An integer specifying the number of times the training
    * algorithm should iterate over the dataset.
    * @param callbacks A vector of `Callback` that will be called during training
-   * stages     * @return A double value that represents the average loss of the
+   * stages
+   * @return A double value that represents the average loss of the
    * training process. This can be used to gauge the effectiveness of the
    * process.
    *