Implemented evaluator for link-prediction in retrieval setting #667
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wangz10
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zheng-da
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Nov 30, 2023
| @@ -872,6 +872,33 @@ def save_full_node_embeddings(g, save_embed_path, | |||
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| save_shuffled_node_embeddings(shuffled_embs, save_embed_path, save_embed_format) | |||
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| def load_gsgnn_embeddings(emb_path, g): | |||
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we didn't have a function to load GNN embeddings saved by GraphStorm? @classicsong
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Issue #, if available:
Description of changes:
lp_infer.pyto evaluate a trained link-prediction model in retrieval setting, where all nodes of the target type are used as negative samples. To perform this evaluation:--eval-negative-sampler fulltopython3 -m graphstorm.run.gs_link_prediction --inference--restore-model-path) and saved GNN embeddings (--restore-embed-path)GSgnnLinkPredictionRetrievalDataLoader: a data loader yielding pos pairs onlyload_gsgnn_embeddingsutil function to load GNN embeddings from diskLinkPredictDotDecoder.calc_retrieval_scores: method to compute dot product scores with pos pairs and all embs as neg pairsBy submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.