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This repository has been archived by the owner on Apr 3, 2020. It is now read-only.
I, for one, would also like to see easy inference/debugging built in, especially for seq2seq.
I know Catalyst already has some of that functionality, I was thinking of extending it and potentially having an interactive notebook that would allow for super easy visualization of predictions.
On the other side, this might also be a wasted effort and something like https://prodi.gy/ might be better suited for the task.
Another piece of work I had in mind was adding more meaningful metrics to the seq2seq pipeline, to move away from minimizing NLL.
There is an idea that we should integrate this repository to Catalyst. @xelibrion , what do you think about it? Just to make it easier to start a new project and create examples.
For an example, Catalyst has already examples for image classification/segmentation. There is a request from Hacktoberfest to have an example for text classification: catalyst-team/catalyst#426
To manage it, I see the following tasks:
flake8 style support (the rules are the same as for Catalyst), In progress...
generalize BertCrossEntropyLoss, BertCriterionCallback. We can add mask functionality to standard CriterionCallback/CrossEntropyLoss, In progress...
union model/modelwrapper. And generalize a unique model, In progress...
integrate the code into Catalyst framework, In progress...
How I see a possible integration with HuggingFace.
We reuse best practices for training NNs in general, which are also implemented in Catalyst:
We also built upon Catalyst training environment:
We can extend it with NLP-specific stuff:
Let's extend and elaborate.
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