midx_journal's Introduction

MIDX_Journal

This is a repo for MIDX sampler applied in other domains like NLP, Knowledge Graph, Sequential Recommendation and Extreme Classification.

RUN

python run.py -m=LSTM -d=penntreebank --sampler=midx-uni

Supported

Task	Model	Dataset
LanguageModeling	[LSTM, Transformer]	[penntreebank, wikitext-2, wikitext-103]
KnowledgeGraph	[HouseE, TransE]	[fb15k, wn18, yago3-10]
ExtremeClassification	[EcFc, ]	[AmazonCat-13k, Delicious-200k, WikiLSHTC]

Optional Sampler: [None, 'midx-uni', 'midx-pop'] (Default: None)

when sampler is None, FullSoftmax is used as loss function, otherwise sampled softmax is used.

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