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Creates a new NSL 1.3.0 release version. See RELEASE.md for details.
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RELEASE.md

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# Release 1.3.0
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## Major Features and Improvements
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* Added locality-sensitive hashing (LSH) support to the graph builder tool.
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This allows the graph builder to scale up to larger input datasets. As part
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of this change, the new `nsl.configs.GraphBuilderConfig` class was
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introduced, as well as a new `nsl.tools.build_graph_from_config` function.
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The new parameters for controlling the LSH algorithm are named `lsh_rounds`
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and `lsh_splits`.
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## Bug Fixes and Other Changes
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* Fixed a bug in `nsl.tools.read_tsv_graph` that was incrementing the edge
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count too often.
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* Changed `nsl.tools.add_edge` to return a boolean result indicating if a new
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edge was added or not; previously, this function was not returning any
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value.
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* Removed Python 2 unit tests.
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* Fixed a bug in `nsl.estimator.add_adversarial_regularization` and
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`nsl.estimator.add_graph_regularization` so that the `UPDATE_OPS` can be
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triggered correctly.
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* Updated graph-NSL tutorials not to parse neighbor features during
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evaluation.
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* Added scaled graph and adversarial loss values as scalars to the summary in
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`nsl.estimator.add_graph_regularization` and
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`nsl.estimator.add_adversarial_regularization` respectively.
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* Updated graph and adversarial regularization loss metrics in
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`nsl.keras.GraphRegularization` and `nsl.keras.AdversarialRegularization`
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respectively, to include scaled values for consistency with their respective
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loss term contributions.
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## Thanks to our Contributors
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This release contains contributions from many people at Google.
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# Release 1.2.0
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## Major Features and Improvements

neural_structured_learning/version.py

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# We follow Semantic Versioning (https://semver.org/).
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_MAJOR_VERSION = '1'
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_MINOR_VERSION = '2'
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_MINOR_VERSION = '3'
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_PATCH_VERSION = '0'
2020

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_VERSION_SUFFIX = ''

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