- 19 6月, 2021 2 次提交
- 23 5月, 2021 1 次提交
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由 jrzaurin 提交于
added get and setstate methods in the EarlyStopping and ModelCheckpoint callbacks. Added the possibility of using GRUs in the deeptext component and also predict using the hidden state or the output. Fixed a small bug in the text processor. Improved the save method in the Trainer
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- 30 4月, 2021 1 次提交
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由 jrzaurin 提交于
ModelCheckpoint saves best epoch as well. Added dropout option for tabnet. Adjusted RAdam for new signatures. Adjusted the training so it can take ReduceLROnPlateau. Also so that it automatically restores the best weights after training
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- 16 4月, 2021 1 次提交
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由 jrzaurin 提交于
Modified the callbacks to accomodate the neccessity of the ReduceLROnPlateau scheduler. Replace weight by pos_weight in BCEWithLogitsLoss. Added on_eval_begin method to reset metrics
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- 09 4月, 2021 1 次提交
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由 jrzaurin 提交于
Fixed a documentation error. For the tabtransformer the input_embed is a list with tuples of 2 elements, not 3
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- 19 3月, 2021 1 次提交
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由 jrzaurin 提交于
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- 18 3月, 2021 1 次提交
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由 jrzaurin 提交于
Change tab_resnet to tab_resnet_blks. Added types to tab_net.py. Cleaned up trainer by moving some methods to tab_net_utils. Adjusted tests
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- 15 3月, 2021 1 次提交
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由 jrzaurin 提交于
Added a few types, refined the docs and added tests for tabnet and the corresponding functionalities
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- 12 3月, 2021 1 次提交
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由 jrzaurin 提交于
added an option to automatically set embed size via fastai's rule of thumb. Re-structure the preprocessing module, breaking it up in a smaller modules for better debugging and 'tractability'
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- 11 3月, 2021 1 次提交
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由 jrzaurin 提交于
added explain and compute feature importance methods to the trainer. Need to add error handling and messaging since these funcionalities are intended only for tabnet. Move the general_utils module to the training module and rename it as trainer_utils. Adapted the create_explain_matrix function to WideDeep
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- 06 3月, 2021 1 次提交
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由 jrzaurin 提交于
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- 05 3月, 2021 1 次提交
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由 jrzaurin 提交于
finished implementing TabNet encoder. Next I need to implement the interpretability methods. Also adjusted WideDeep class to be able to work with TabNet. Renamed some example scripts to be consistent with each other
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- 02 3月, 2021 1 次提交
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由 jrzaurin 提交于
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- 28 2月, 2021 1 次提交
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由 jrzaurin 提交于
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- 22 2月, 2021 1 次提交
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由 jrzaurin 提交于
fixed a naming inconsistency. The Transformer encoder blocks were named 'blks'. A more consistent name relative to the other two tab models would be 'tab_transformer_blks', and so I have changed it. This leads to a small inconsistency between pypi version and that in github, which is almost irrelevant
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- 14 2月, 2021 2 次提交
- 11 2月, 2021 2 次提交
- 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