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Replace Embedding to use nn.Embedding from pytorch #428

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ravinkohli opened this issue Apr 5, 2022 · 0 comments · May be fixed by #451
Open

Replace Embedding to use nn.Embedding from pytorch #428

ravinkohli opened this issue Apr 5, 2022 · 0 comments · May be fixed by #451
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@ravinkohli
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Due to our current implementation of Embedding module, we are forced to one-hot encode all categorical columns. This leads to an explosion in the memory usage. We can avoid this by using nn.Embedding from pytorch which has the same functionality but does not need one-hot encoded columns. This will also allow us to one hot encode the columns which have number of categories less than min_categories_for_embedding.

@ravinkohli ravinkohli self-assigned this Apr 5, 2022
@ravinkohli ravinkohli added the enhancement New feature or request label Apr 5, 2022
@ravinkohli ravinkohli added this to To do in Roadmap via automation Apr 5, 2022
@ravinkohli ravinkohli linked a pull request Apr 5, 2022 that will close this issue
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@ravinkohli ravinkohli linked a pull request Aug 16, 2022 that will close this issue
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@ravinkohli ravinkohli moved this from To do to In progress in Roadmap Aug 16, 2022
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