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Updating docs, fixing CSDI&LOCF&MRNN, and adding the strategy to save all models #284

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merged 11 commits into from
Dec 25, 2023

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WenjieDu
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@WenjieDu WenjieDu commented Dec 25, 2023

What does this PR do?

  1. updating docs;
  2. GP-VAE should return multiple sampling results #276;
  3. fixing CSDI Fixing CSDI, adding placeholder for epoch num in logging #280;
  4. fixing LOCF Infinite loop in LOCF when whole feature missing #281;
  5. fixing some issues in MRNN;
  6. making PyPOTS able to save all models during training;

Before submitting

  • This PR is made to fix a typo or improve the docs (you can dismiss the other checks if this is the case).
  • Was this discussed/approved via a GitHub issue? Please add a link to it if that's the case.
  • I have commented my code, particularly in hard-to-understand areas.
  • I have written necessary tests and already run them locally.

* feat: add _check_inputs() for all error metric calculation functions;

* fix: use corresponding lib to detect NaN, otherwise loss calculation during torch training will raise error...

RuntimeError: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead.

* fix: don't check shapes for CRPS calc funcs;
* feat: add assertion for CSDI and GP-VAE to ensure n_sampling_times>0 in predict();

* fix: val_set for CSDI should return X_ori for model validation;

* refactor: add placeholder for epoch number in logging;
* fix: apply zero filling if missing values still exist after applying first_step_imputation;

* refactor: adjust some logging info;

* fix: set a default value for first_step_imputation in _locf();
…nd correct the reconstruction loss on its output;
* feat: let pytest print detail logs during testing;

* docs: update the docs;

* docs: add doc text for customized_loss_func in SAITS;
@WenjieDu WenjieDu merged commit bae6dd4 into main Dec 25, 2023
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