- 10 2月, 2021 1 次提交
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由 jrzaurin 提交于
Added notebook on how to use custom components. Version will be still beta because I prefer to wait for V1 until I have tried it with more datasets
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- 09 2月, 2021 8 次提交
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由 jrzaurin 提交于
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由 jrzaurin 提交于
Added some text to the callbacks docs. Is not rendering well in tthe Read The Docs app, who knows why
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由 jrzaurin 提交于
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由 jrzaurin 提交于
After a gigantic mess with Sphinx, where, somehow, the docs looked entirely diff when built in the locally than with the app, I had to revert back to default themes. This was painful
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由 jrzaurin 提交于
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由 jrzaurin 提交于
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由 jrzaurin 提交于
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由 jrzaurin 提交于
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- 07 2月, 2021 1 次提交
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由 jrzaurin 提交于
Finished documentation. Adjusted Notebooks. Renamed WarmUp class to what it really is, FineTune. Alias the corresponding parameters so that the user can use both, finetune and alias params. Modified a few defaults
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- 05 2月, 2021 2 次提交
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由 jrzaurin 提交于
Added float type to metrics output and removed X_text from first set of callback tests, since it seems to cause some problems at testing time (I think, see what travis has to say)
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由 jrzaurin 提交于
Added Test. Ignored a number of typing related errors after updated to latest version of numpy (need to look into this. Ready to move on with notebooks
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- 03 2月, 2021 1 次提交
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由 jrzaurin 提交于
adjust README. Adjust 2 first notebooks and write a new one (02_2). Fixed some examples of usage. Added FullEmbeddingDropout to TabTransformer. Encapsulate alias in Classes in loss_and_obj_alias module and change some minor style text
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- 30 1月, 2021 2 次提交
- 26 1月, 2021 1 次提交
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由 jrzaurin 提交于
decoupled the model from the training process via the introduciton of a Trainer class. All seems easier now. Need to adjust all documentation. Also added a few losses and an R2 metric, as well as the possibiliy of customising virually every single component of the model
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- 24 1月, 2021 1 次提交
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由 jrzaurin 提交于
added the possibility of passing a few more loss functions and custom ones if required. Now I need to think if I want it registered as a child or not. Also, need to test all new implementation
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- 23 1月, 2021 1 次提交
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由 jrzaurin 提交于
changed the dense layer to be almost identical to that of fastai, which I really like. Changed the code accordingly. Changed the name of DeepDense and DeepDenseResnet to TabMlp and TabResnet. Change the tests acccordingly
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- 22 1月, 2021 2 次提交
- 17 1月, 2021 1 次提交
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由 jrzaurin 提交于
Mainly re-written all tests. Also, refined parameter naming and save 0 for unseen categories (as padding) for both wide and deeptabular component
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- 16 1月, 2021 1 次提交
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由 jrzaurin 提交于
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- 13 1月, 2021 1 次提交
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由 jrzaurin 提交于
first commit towards adding the TabTransformer. This will be a mix between a number of implementation (that will of course be credited in the code)
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- 22 12月, 2020 2 次提交
- 18 12月, 2020 2 次提交
- 17 12月, 2020 1 次提交
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由 jrzaurin 提交于
added inverse_transform for DeepPreprocessor. Also added NameError and AttributeError to avoid bare excepts
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- 15 12月, 2020 1 次提交
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由 jrzaurin 提交于
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- 04 12月, 2020 5 次提交
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由 Javier 提交于
Fix image format
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由 jrzaurin 提交于
Added comment for Mac users regarding the dataloaders not running in parallel for the latest torch version or python versions >= 3.8. Also, upgraded sub-version of the package to 0.4.7
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由 jrzaurin 提交于
adjusting two of the example notebooks to include comments on the possibility of using individual components in isolation
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由 jrzaurin 提交于
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由 jrzaurin 提交于
updated docs so they are consistent with new functionalities. Updated logo. Updated README and fix a typo in setup.py
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- 03 12月, 2020 2 次提交
- 01 12月, 2020 1 次提交
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由 jrzaurin 提交于
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- 28 11月, 2020 1 次提交
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由 jrzaurin 提交于
all started by trying to add a line so that the builder accepted 2D images (or in general images of dim different than 3. But it ended up by adding functionalities so that each individual component (wide, deepdense, deeptext and deepimage) can be used individually
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- 28 9月, 2020 2 次提交