Feature/unsupervised training #29
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…pervised_training
dead-end as function design is not ready
fix typo in epoch_shift
add random_obfuscator() fix unsupervised_loss()
fix y has one column in tabnet_train_unsupervised()
lower data size in secondary tests
fix typo in subseting dataset in test
…/unsupervised_training
add train_batch_un() and valid_batch_un() fix epoch_shift value missing
Merge branch 'main' of https://github.com/mlverse/tabnet into feature/unsupervised_training # Conflicts: # R/model.R
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Hey @cregouby ! This looks awesome!! It's almost there! I think the problem was that the decoder was returning only the combined steps output instead of the intermediate ones. We now get to a |
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Thanks a lot for this push @dfalbel ! I'll definitively continue with the model serialization. |
…ll fails to pipe unsupervised to supervised.
Still need to convert network from one to the other
still failing saveRDS serialisation and val-split
remove duplicate function
move some tests to -scenarios
…/unsupervised_training
relaxed tolerance between two training epoch
fix typo add few more explainations
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Thanks a lot, @dfalbel ! |
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Hello,
Unsupervised training is working now, and can be part of training scenario ( see test-hardhat-scenarios.R)
except for CUDA where I can't get
torch_bernoulli()work on GPU (see mlverse/torch#480)Fix #18