This epic contains all tasks related to preparing the initial model and the supporting code required to be able to train it. For the initial version, we'll be extending the training code from cle-mnist.
This will include the following tasks:
(1a) #15 Complete RiskDataset in core/dataset.py with tests/debugging
(1b) #14 Complete Risk model code in core/model.py with tests/debugging (begun in #2)
(2a) #16 Implement prepare_data function as in cle-mnist using the RiskDataset
(2b) #17 Convert cle-mnist training/inference loops to be compatible with Risk model
(3) #18 Audit of training code, model, dataset.
The tasks above are mostly blocking for all downstream tasks. The tasks below are not. They are optional, but will be extremely useful during training and tuning, and should be picked up whenever all higher-priority tasks are complete. Note I've split them out as two tasks, although they're strongly intermingled and could be completed by a single person or two people working in parallel with effective communication.
(4) #12 Modify logging from stdout to logging files in a directory.
(5) #12 Extend (4) to work with TensorboardX
This epic contains all tasks related to preparing the initial model and the supporting code required to be able to train it. For the initial version, we'll be extending the training code from
cle-mnist.This will include the following tasks: (1a) #15 Complete RiskDataset in
core/dataset.pywith tests/debugging (1b) #14 Complete Risk model code incore/model.pywith tests/debugging (begun in #2) (2a) #16 Implementprepare_datafunction as incle-mnistusing the RiskDataset (2b) #17 Convertcle-mnisttraining/inference loops to be compatible with Risk model (3) #18 Audit of training code, model, dataset.The tasks above are mostly blocking for all downstream tasks. The tasks below are not. They are optional, but will be extremely useful during training and tuning, and should be picked up whenever all higher-priority tasks are complete. Note I've split them out as two tasks, although they're strongly intermingled and could be completed by a single person or two people working in parallel with effective communication.
(4) #12 Modify logging from stdout to logging files in a directory. (5) #12 Extend (4) to work with TensorboardX