Rosario Scalise
Rosario Scalise
We intend to release versions of singular project packages - think `hydra-configs-torch` or `hydra-configs-torchvision` via release branches that get tagged for upload to PyPI. This enables users to get the...
This is low priority since much of this can be achieved by reading the documentation in this larger repo, but eventually it might be nice to make it stand alone....
Write functions of the form: `hydra_configs.torch.register()`, `hydra_configs.torch.optim.register()`, etc. Within these functions, call config store API: ```python cs = ConfigStore.instance() cs.store(name="adamconf", node=AdamConf) ``` Call these in `__init__.py` for the module.
In general, we need to discuss how to test instantiation of 'Distributed' classes. This is one class we can configure, but have not experimented with tests for yet.
This test requires improvements to hydra's `instantiate`. Namely being able to instantiate with non-keyword passthrough arguments.
Since this repository contains N packages each corresponding to a collection of configs for their corresponding libraries, we should write up a version controlled overview of the design decisions and...
https://github.com/facebookresearch/hydra-torch/blob/691a390abd2edf764f9431a56b8058ff2c12eb0c/tests/test_instantiate.py#L40 Check minimal tests. Is this the right way to confirm our configs instantiate the correct object? From previous PR discussion: > Ideally I wanted these tests to do 3...
Tests for examples from tutorial: [examples/mnist_00.py](https://github.com/pytorch/hydra-torch/blob/master/examples/mnist_00.py) and [examples/mnist_01.py](https://github.com/pytorch/hydra-torch/blob/master/examples/mnist_01.py). Something along these lines: https://github.com/facebookresearch/hydra/tree/master/tests/test_examples
Generate these confs. Write tests.
Generate these module confs, brainstorm robust testing method.