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geoffreyQiu
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apply_inference_embedding implementation
shijieliu
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Feb 11, 2026
| for idx, embc in enumerate(embc_modulelist): | ||
| emb_backend = embc_configs[idx].backend | ||
| create_embedding_collection = select_embedding(emb_backend) | ||
| embc_modulelist[idx] = create_embedding_collection( |
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do we need to uset setattr here? like reference
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the overall arch looks good to me. I think you can create a |
shijieliu
reviewed
Feb 11, 2026
| embedding_configs, | ||
| embedding_backend, | ||
| sparse_shareables, | ||
| def create_torchrec_embedding( |
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maybe we dont need to support this.
| ) | ||
| model_state_dict = torch.load(model_state_dict_path)["model_state_dict"] | ||
| self.load_state_dict(model_state_dict, strict=False) | ||
| pass |
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for load dump, we can reuse DynamicEmbLoad/DynamicEmbDump for dynamicemb checkpoint
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Description
Support Torch Cpp Runtime for HSTU
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