PyTorch Punctuator

----A basic template for punctuation prediction implemented by PyTorch

1. File Description

data

• raw_data: the directory to store raw data for training, validation, and testing, containing train.txt, valid.txt, and test.txt, respectively.
• processed_data: the directory to store the processed data of raw_data by preprocessing.py, containing train.npy, valid.npy and test.npy, respectively.
• preprocessing.py: python script to split inputs and labels, convert input sentences to indexes, pad index list to the same length, and save the processed data as .npy format.
• dataset.py: python script to build pytorch Dataset and DataLoader.

models

• BaseModel.py: the father class implementing the network building, setup input, forward computation, backpropagation, network saving and loading, learning rate schedulers, and visualization of losses and metrics.
• **Model.py: the implementaion that extends BaseModel of specific models (methods), such as LstmModel, Seq2SeqModel etc.
• **Net.py: the code of network achitectures, such as LstmNet.py, Seq2SeqNet.py etc.

run

• trainer.py: a basic template python file for training from scratch, or resuming training, and validation the **Model.
• tester.py: a basic template python file for testing the **Model.

utils

• configs.py: the python file can be used to store and modify the hyper-parameters for training, validation and testing process.
• help_functions.py: the python file can be used to store and modify the model initilization strategies and optimizer scheduler settings.
• metrics.py: the python file can be used to store and modify the evaluation metrics, such as Precsion, Recall, F1-score etc.
• visualizer.py: the python file can be used for visualization of the losses and images.

main.py: the script for running the code.

• if you want to train the model from scratch, run python main.py --mode train --start_epoch 1 in the command line of your python environment.
• if you want to resume the training process, run python main.py --mode train --start_epoch epoch_you_want_to_resume in the command line of your python environment.
• if you want to test the model, run python main.py --mode test --load_epoch parameters_epoch_you_want_to_test in the command line of your python environment.

2. Train and test your own model

if you want to train and test your own model using this template, your just need to:

• create a YourOwnNet.py file in directory models and implement every details of your own networks.
• create a YourOwnModel.py that extends the father class BaseModel and only implement the forward() function and backward() function
• import YourOwnModel in trainer.py and tester.py as well as modify the MODEL NAME with `YourOwnModel'.

3. Future works

• implement more **Models for punctuation prediction.
• try to do punctuation restoration.
• try different kinds of Language materials, such as Chinese etc.

4. Contacts

if you have any questions, please email to: tsmotlp or sakura.