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| 1 | +# Release 1.3.0 |
| 2 | + |
| 3 | +## Major Features and Improvements |
| 4 | + |
| 5 | +* Added locality-sensitive hashing (LSH) support to the graph builder tool. |
| 6 | + This allows the graph builder to scale up to larger input datasets. As part |
| 7 | + of this change, the new `nsl.configs.GraphBuilderConfig` class was |
| 8 | + introduced, as well as a new `nsl.tools.build_graph_from_config` function. |
| 9 | + The new parameters for controlling the LSH algorithm are named `lsh_rounds` |
| 10 | + and `lsh_splits`. |
| 11 | + |
| 12 | +## Bug Fixes and Other Changes |
| 13 | + |
| 14 | +* Fixed a bug in `nsl.tools.read_tsv_graph` that was incrementing the edge |
| 15 | + count too often. |
| 16 | +* Changed `nsl.tools.add_edge` to return a boolean result indicating if a new |
| 17 | + edge was added or not; previously, this function was not returning any |
| 18 | + value. |
| 19 | +* Removed Python 2 unit tests. |
| 20 | +* Fixed a bug in `nsl.estimator.add_adversarial_regularization` and |
| 21 | + `nsl.estimator.add_graph_regularization` so that the `UPDATE_OPS` can be |
| 22 | + triggered correctly. |
| 23 | +* Updated graph-NSL tutorials not to parse neighbor features during |
| 24 | + evaluation. |
| 25 | +* Added scaled graph and adversarial loss values as scalars to the summary in |
| 26 | + `nsl.estimator.add_graph_regularization` and |
| 27 | + `nsl.estimator.add_adversarial_regularization` respectively. |
| 28 | +* Updated graph and adversarial regularization loss metrics in |
| 29 | + `nsl.keras.GraphRegularization` and `nsl.keras.AdversarialRegularization` |
| 30 | + respectively, to include scaled values for consistency with their respective |
| 31 | + loss term contributions. |
| 32 | + |
| 33 | +## Thanks to our Contributors |
| 34 | + |
| 35 | +This release contains contributions from many people at Google. |
| 36 | + |
1 | 37 | # Release 1.2.0
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2 | 38 |
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3 | 39 | ## Major Features and Improvements
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