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+ # Release 1.1.0
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+
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+ ## Major Features and Improvements
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+
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+ * Introduces ` nsl.tools.build_graph ` , a function for graph building.
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+
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+ * Introduces ` nsl.tools.pack_nbrs ` , a function to prepare input for
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+ graph-based NSL.
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+
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+ * Adds ` tf.estimator.Estimator ` support for NSL. In particular, this release
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+ introduces two new wrapper functions named
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+ ` nsl.estimator.add_graph_regularization ` and
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+ ` nsl.estimator.add_adversarial_regularization ` to wrap existing
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+ ` tf.estimator.Estimator ` -based models with NSL. These APIs are currently
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+ supported only for TF 1.x.
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+
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+ ## Bug Fixes and Other Changes
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+
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+ * Adds version information to the NSL package, which can be queried as
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+ ` nsl.__version__ ` .
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+
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+ * Fixes loss computation with ` Loss ` objects in ` AdversarialRegularization ` .
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+
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+ * Adds a new parameter to ` nsl.keras.adversarial_loss ` which can be used to
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+ pass additional arguments to the model.
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+
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+ * Fixes typos in documentation and notebooks.
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+
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+ * Updates notebooks to use the release version of TF 2.0.
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+
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+ ## Thanks to our Contributors
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+
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+ This release contains contributions from many people at Google.
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+
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# Release 1.0.1
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## Major Features and Improvements
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- * Adds 'make_graph_reg_config', a new API to help construct a ` nsl.configs.GraphRegConfig ` object
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+ * Adds 'make_graph_reg_config', a new API to help construct a
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+ ` nsl.configs.GraphRegConfig ` object.
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- * Updates the package description on PyPI
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+ * Updates the package description on PyPI.
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## Bug Fixes and Other Changes
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- * Fixes metric computation with ` Metric ` objects in ` AdversarialRegularization `
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+ * Fixes metric computation with ` Metric ` objects in
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+ ` AdversarialRegularization ` .
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- * Fixes typos in documentation and notebooks
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+ * Fixes typos in documentation and notebooks.
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## Thanks to our Contributors
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@@ -20,4 +56,4 @@ This release contains contributions from many people at Google, as well as:
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# Release 1.0.0
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- * Initial release of Neural Structured Learning in TensorFlow
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+ * Initial release of Neural Structured Learning in TensorFlow.
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