< Write your installation guide here >
pip install -r ./requirements.txtYou might be a little intimidated by the number of folders and classes. Try to follow this steps to gradually undestand the workflow.
- Test
hw_asr/tests/test_dataset.pyandhw_asr/tests/test_config.pyand make sure everythin works for you - Implement missing functions to fix tests in
hw_asr\tests\test_text_encoder.py - Implement missing functions to fix tests in
hw_asr\tests\test_dataloader.py - Implement functions in
hw_asr\metric\utils.py - Implement missing function to run
train.pywith a baseline model - Write your own model and try to overfit it on a single batch
Pain and sufferingImplement your own models and train them. You've mastered this template when you can tune your experimental setup just by tuningconfigs.jsonfile and runningtrain.py- Don't forget to write a report about your work
- Get hired by Google the next day
- Make sure your projects run on a new machine after complemeting installation guide
- Search project for
# TODO: your code hereand implement missing functionality - Make sure all tests work without errors
python -m unittest discover hw_asr/tests
- Make sure
test.pyworks fine and works as expected. You should create filesdefault_test_config.jsonand your installation guide should download your model checpoint and configs indefault_test_model/checkpoint.pthanddefault_test_model/config.json.python test.py \ -c default_test_config.json \ -r default_test_model/checkpoint.pth \ -t test_data \ -o test_result.json
- Use
train.pyfor training
this repository is based on a heavily modified fork of pytorch-template repository.
These barebones can use more tests. We highly encourage students to create pull requests to add more tests / new functionality. Current demands:
- Tests for beam search
- W&B logger backend
- README section to describe folders
- Notebook to show how to work with
ConfigParserandconfig_parser.init_obj(...)