base_models

Base Models

The files containing trained parameters of base models considered in this work can be downloaded by executing ./download_base_models.sh in the parent directory. Model files will be saved under the base_model_trained_files directory.

Adding a new base model

If you'd like to add a new base model for evaluation, you need to make to perform the following steps:

1. Implement the base model in PyTorch. Your base model must inherit from torch.nn.Module and must implement the __init__ and forward methods. The forward method must take just one parameter, a batch of samples over which a forward pass is performed.
2. Train your base model and save the base model's state dictionary to a file. This may be done using torch.save(my_base_model.state_dict(), "model.t7")
3. Create a new entry in train.py under get_base_model and get_parity_model. Note the following requirements:
   1. base_path: Specify the path to the state dictionary saved in step (2).
   2. class: Specify the classpath of your base model in the "class" field and any arguments required for the __init__ function in the "args" field.
   3. input_size: Specify the input dimensions expected of inputs to the forward method of your base model.