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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10197 Support generic feature in DPER2 For now since we only have one generic type 1, we are directly adding the parsed feature record to embedding feature. For new feature types with specific structure, there should also be corresponding coding changes expected. Reviewed By: itomatik Differential Revision: D8788177 fbshipit-source-id: 9aaa6f35ece382acb4072ec5e57061bb0727f184 |
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| .. | ||
| __init__.py | ||
| adaptive_weight.py | ||
| add_bias.py | ||
| arc_cosine_feature_map.py | ||
| batch_distill_lr_loss.py | ||
| batch_lr_loss.py | ||
| batch_mse_loss.py | ||
| batch_normalization.py | ||
| batch_sigmoid_cross_entropy_loss.py | ||
| batch_softmax_loss.py | ||
| blob_weighted_sum.py | ||
| build_index.py | ||
| concat.py | ||
| constant_weight.py | ||
| conv.py | ||
| dropout.py | ||
| fc.py | ||
| fc_without_bias.py | ||
| feature_sparse_to_dense.py | ||
| functional.py | ||
| gather_record.py | ||
| homotopy_weight.py | ||
| label_smooth.py | ||
| last_n_window_collector.py | ||
| layer_normalization.py | ||
| layers.py | ||
| margin_rank_loss.py | ||
| merge_id_lists.py | ||
| pairwise_similarity.py | ||
| position_weighted.py | ||
| random_fourier_features.py | ||
| reservoir_sampling.py | ||
| sampling_train.py | ||
| sampling_trainable_mixin.py | ||
| select_record_by_context.py | ||
| semi_random_features.py | ||
| sparse_feature_hash.py | ||
| sparse_lookup.py | ||
| split.py | ||
| tags.py | ||
| uniform_sampling.py | ||