conf/readme.md

The inference_settings has a default yaml containing four keys: -sequences_path: The full path of the file containing the sequences for which their annotations are to be infered.

• model_path: the full path of the model to be used for inference.
• model_name: A model name indicating the inputs the model expects. One of seq,seq-seq,seq-struct,seq-reverse or baseline
• infere_original_testset: True/False indicating whether inference should be computed on the original test set.

model contains the skeleton of the model used, the optimizer, loss function and device. All models are built using skorch

train_model_configs contain the hyperparameters for each dataset; tcga, sncrna and premirna:

• Each file contains the model and the train config.

  • Model config: contains the model hyperparameters, sequence tokenization scheme and allows for choosing the model.

  • Train config: contains training settings such as the learning rate hyper parameters as well as dataset_path_train.

    • dataset_path_train: should point to the dataset (Anndata) used for training.