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Reliable deep network training, saving you hours.

Project description


A thin PyTorch wrapper which performs static and dynamic analysis of the computational graph to prevent latent errors.


pip install reluble


Install the testing dependencies:

  • pytest, e.g. with pip install pytest.
  • torchvision, e.g. with pip install torchvision. This is probably installed alongside torch.

Clone the repository and change into the root:

git clone
cd reluble

To run all the tests, simply run pytest. It is recommended to disable capturing, e.g. with:

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:

pytest -s tests/

And for a bad net:

pytest -s tests/

In this case, the LearningError is the desired behavior.

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