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@@ -1,22 +1,53 @@ -# GSN, zadanie 1 - -Rozpoznawanie kształtów i ich liczebności. - -## Trenowanie - -Po każdym trenowaniu wygenerowany jest raport zawierający informacje na temat -danego eksperymentu. Zawiera: - -* Opis sieci - * Warstwy - * Liczebność parametrów -* Hiperparametry - * Learning rate - * Liczba epok - * Batch size - * Momentum i inne jeśli wykorzystane -* Wykorzystane dane (w postaci opisu nałożonych augmentacji) -* Metryki - * Loss per epoka dla danych testowych - * Loss per epoka dla danych treningowych - * Accuracy dla danych treningowych +# Deep Neural Networks, Homework 1 + +Recognizing and counting shapes. + +## Running experiments + + python src/run.py configuration.yaml + +### Configuration + +We can specify various training scenarios via YAML files. This allows us to +experiment with different network architectures and hyperparameters. + +The configuration should have the following fields: + +* `type`: one of `classification`, `counting-small`, `counting-large`, depending + on which problem we're attempting to train for. This controls: + * the size of the final output layer + * final transformation applied to output layer + * transformations applied to targets, if necessary + * the loss function used + * the accuracy metric used +* `batch_norm` (defaults to `false`) +* `dropout` (defaults to `false`): `false` or `p` parameter for dropout layers +* `lr` +* `epochs` +* `batch_size` +* `augmentations`: list of augmentation specifications to expand the dataset + with: + * `rotation` (defaults to 0): integer 0-3 specifying number of 90° rotations + to apply + * `vflip` (defaults to `false`) + * `hflip` (defaults to `false`) +* `convolutions`: a list of convolution layer specifications: + * `in_channels` + * `out_channels` + * `size` (defaults to 3) + * `stride` (defaults to 1) + * `padding` (defaults to 1) + * `max_pool` (defaults to `false`): whether to apply a 2x2 max pool layer +* `linears`: a list of desnse layer specifications: + * `in_features` + * `out_features` + +### Results + +For each run, a timestamped directory is created under `outputs/` with: + +* A copy of the used configuration file +* A CSV file with train set losses, test set losses, and test set accuracies, + for each epoch +* `losses.png`: a plot of the losses +* `accuracies.png`: a plot of the accuracies |