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Num embeddings#200

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jrzaurin merged 29 commits intomasterjrzaurin/pytorch-widedeep:masterfrom num_embeddingsjrzaurin/pytorch-widedeep:num_embeddingsCopy head branch name to clipboardFeb 17, 2024

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Commits

Commits on Jan 11, 2024

• Added 'PiecewiseLinearContEmbeddings' as a method to encode numerical feats

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Commits on Jan 12, 2024

• Added 'PeriodicLinearContEmbeddings' as a method to encode numerical feats. Now the two changes that need to happen are: 1. add the activation funcion in the Encoding Layer itself and 2. Define the…

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• Activation function within the embedding layer added for the cont embedding layers. Needs to be added within the cat embed layers and then move to 2. Define the embedding process in the base models…

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Commits on Jan 13, 2024

• Activation function within the embedding layer added for the cat embedding layers. Now onto 2. Define the embedding process in the base models rather than the DiffSizeCatAndContEmbeddings and the S…

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Commits on Jan 15, 2024

• Set up the embeddings within the _base_tabular_model module. Now I need to test the two classes manually and then change the main models accordingly

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Commits on Jan 18, 2024

• Incorporated the continuous embeddings parameters to the main models. Now I need to 1. Adjust docs. 2. Adjust/Fix tests. 3. Redo the examples. 4. Add new examples

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Commits on Jan 19, 2024

• Adjusted the docs. Now onto adjusting the tests

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Commits on Jan 21, 2024

• Adjusted the tests. Now: 1. Re-do tab2vec and corresponding tests. 2. Just have an overall look at the code. 3. Re-do examples. 4. Have a look to the mkdocs

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Commits on Jan 22, 2024

• tests are passing. 1. Have an overall look to the code. 2. Re-do example 3. Review mkdocs

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Commits on Jan 24, 2024

• Code up to the bayesian trainer has been reviewed. From the Trainer in advanced left

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Commits on Jan 25, 2024

• Code reviewed. Now 1. Re-do examples. 2. Review the (mk)docs

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Commits on Feb 2, 2024

• All examples reviewed. Some code chanages made. Now: 1. new example notebook with num embeddings. 2. Review the docs 3. Test in all possible platforms. Nearly there...

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• removed some uneccessary/tmp files

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Commits on Feb 5, 2024

• Done reviewing docs until the models section

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Commits on Feb 7, 2024

• docs reviewed. Need to increase a bit coverage and release

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Commits on Feb 8, 2024

• Added tests to test the functioning of the continuous embedding features. I want to increase the coverage for the deeptabular_utils module and we are done

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Commits on Feb 9, 2024

• slightly increased the coverage for the label_encoder. Ready to test in multiple platforms

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• Added support for python 3.8 where pandas 2.1 and higher is not available

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• removed load from folder test data

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• removed old docs file and update setup and build.yml files

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Commits on Feb 10, 2024

• fixed the tests to tab2vec in the case of cuda available

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• fixed the tests to tab2vec in the case of cuda available

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Commits on Feb 16, 2024

• minor style changes

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• trigger actions in push for this branch

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• trigger actions in push for this branch: python version as string

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• Updated style libraries

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• Another python version that needs turning into str

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• removed this branch from actions (on push)'

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• Adjusted the python supported versions in the README and updated the version of the library

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