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added support for tb projector word embeddings #2853

Merged
merged 2 commits into from
Oct 6, 2020
Merged

added support for tb projector word embeddings #2853

merged 2 commits into from
Oct 6, 2020

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floleuerer
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Added support for exporting word embeddings for Tensorboard projector (function tensorboard_word_embeddings) and updated tests and documentation.

tensorboard_word_embeddings will automatically get the correct layer and vocab for a fast.ai model - for transformers or other models the embedding layer and vocab can be passed as parameters.

@floleuerer floleuerer requested a review from jph00 as a code owner October 3, 2020 11:43
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@floleuerer
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I've added feat['vec'].squeeze() to support unflattend layers for image models (e.g. pooling layers). Changed docs and tests to show the different options how to pass the callback (fit_one_cycle(5, cbs=cbs), get_preds(dl=dl, cbs=cbs)).

@jph00 jph00 merged commit 5b14964 into fastai:master Oct 6, 2020
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