Create NSL version 1.2.0. See RELEASE.md for a list of changes that are part of this release.

PiperOrigin-RevId: 315775556

Author: arjung

RELEASE.md

@@ -1,3 +1,54 @@
+# Release 1.2.0
+
+## Major Features and Improvements
+
+*   Changed `nsl.tools.build_graph(...)` to be more efficient and use far less
+    memory. In particular, the memory consumption is now proportional only to
+    the size of the input, not the size of the input plus the size of the
+    output. Since the size of the output can be quadratic in the size of the
+    input, this can lead to large memory savings. `nsl.tools.build_graph(...)`
+    now also produces a log message every 1M edges it writes to indicate
+    progress.
+*   Introduces `nsl.lib.strip_neighbor_features`, a function to remove graph
+    neighbor features from a feature dictionary.
+*   Restricts the expectation of graph neighbor features being present in the
+    input to the training mode for both the Keras and Estimator graph
+    regularization wrappers. So, during evaluation, prediction, etc, neighbor
+    features need not be fed to the model anymore.
+*   Change the default value of `keep_rank` from `False` to `True` as well as
+    flip its semantics in `nsl.keras.layers.NeighborFeatures.call` and
+    `nsl.utils.unpack_neighbor_features`
+*   Supports feature value constraints for adversarial neighbors. See
+    `clip_value_min` and `clip_value_max` in `nsl.configs.AdvNeighborConfig`.
+*   Supports adversarial regularization with PGD in Keras and estimator models.
+*   Support for generating adversarial neighbors using Projected Gradient
+    Descent (PGD) via the `nsl.lib.adversarial_neighbor.gen_adv_neighbor` API.
+
+## Bug Fixes and Other Changes
+
+*   Clarifies the meaning of the `nsl.AdvNeighborConfig.feature_mask` field.
+*   Updates notebooks to avoid invoking the `nsl.tools.build_graph` and
+    `nsl.tools.pack_nbrs` utilities as binaries.
+*   Replace deprecated API in notebooks when testing for GPU availability.
+*   Fix typos in documentation and notebooks.
+*   Improvements to example trainers.
+*   Fixed the metric string to 'acc' to be compatible with both TF1.x and 2.x.
+*   Allow passing dictionaries to sequential base models in adversarial
+    regularization.
+*   Supports input feature list in `nsl.lib.gen_adv_neighbor`.
+*   Supports input with a collection of tensors in
+    `nsl.lib.maximize_within_unit_norm`.
+*   Adds an optional parameter `base_with_labels_in_features` to
+    `nsl.keras.AdversarialRegularization` for passing label features to the base
+    model.
+*   Fixes the tensor ordering issue in `nsl.keras.AdversarialRegularization`
+    when used with a functional Keras base model.
+
+## Thanks to our Contributors
+
+This release contains contributions from many people at Google as well as
+@mzahran001.
+
 # Release 1.1.0
 
 ## Major Features and Improvements

neural_structured_learning/version.py

@@ -15,7 +15,7 @@
 
 # We follow Semantic Versioning (https://semver.org/).
 _MAJOR_VERSION = '1'
-_MINOR_VERSION = '1'
+_MINOR_VERSION = '2'
 _PATCH_VERSION = '0'
 
 _VERSION_SUFFIX = ''