Metadata-Version: 2.1
Name: reluble
Version: 0.1.0
Summary: Reliable deep network training, saving you hours.
Home-page: UNKNOWN
Author: Nathan Drenkow, Catalina Gomez, and Benjamin D. Killeen
Author-email: killeen@jhu.edu
License: UNKNOWN
Description: # Reluble
        
        A thin PyTorch wrapper which performs static and dynamic analysis of the computational graph to
        prevent latent errors.
        
        ## Install
        
        ```bash 
        pip install reluble
        ```
        
        ## Tests
        
        Install the testing dependencies:
        * [pytest](https://docs.pytest.org/), e.g. with `pip install pytest`.
        * [torchvision](https://pytorch.org/), e.g. with `pip install torchvision`. This is probably
          installed alongside torch.
          
        Clone the repository and change into the root:
        
        ```bash
        git clone git@github.com:arcadelab/reluble.git
        cd reluble
        ```
          
        To run all the tests, simply run `pytest`. It is recommended to disable capturing, e.g. with:
        
        ``` sh
        pytest -s
        ```
        
        These tests can take a long time, particularly if you are running on CPU. It is recommended to run
        on GPU. Some of the tests will produce output files in `./outputs/`.
        
        To show corruptions working for a good net, run:
        
        ```sh
        pytest -s tests/test_training.py::TestCorruptions::test_good_Net
        ```
        
        And for a bad net:
        
        ``` sh
        pytest -s tests/test_training.py::TestCorruptions::test_bad_Net
        ```
        In this case, the `LearningError` is the desired behavior.
        
        
Platform: UNKNOWN
Requires-Python: >=3.8
Description-Content-Type: text/markdown
