Notes for Code Testing

The implemented testing uses pytest, consisting of the following files:

- conftest.py
- tests
  |
  - test_args.py
  - test_cli_train.py
  - test_cli_serialize.py
  - test_cli_inference.py

Constant variables that will be shared across test cases are stored as fixtures, specified in conftest.py.

The automatic testing with GitHub Actions is not enabled due to the need of GPUs in testing.

Added arguments:

model_type: the type of model to use, currently allows "latest" or "ext"
model_dir: the directory to your local model files if you have, using which can avoid the time downloading the models from Zenodo (10min+)

Note that in order to specify model_dir, you have to specify model_type. This seems to be some issue in pytest custom arguments.

Model Type	Example Execution Time
latest	13:18
ext	38:17

Added test cases:

test_args.py: tests the access to argument values as fixture
test_cli_train.py: tests if cli.py train can run on a) CPU, b) single GPU, and c) two GPUs (data parallel)
test_cli_serialize.py: tests if cli.py serialize can run
test_cli_inference.py: tests if cli.py test a) can run, and b) yields consistent predictions across two trials or two approaches (serialized model files vs. original model files)

To Run Testing...

In DeepLIIF folder, execute the following command:

pytest -v -s --model_type latest --model_dir <your local model dir>

This will use the model files you provided to run all the test cases.