Release notes on 0.25.1

doc/sphinx/source/conf.py

@@ -73,11 +73,11 @@ author = 'Intel Corporation'
 # built documents.
 #
 # The short X.Y version.
-version = '0.26'
+version = '0.25.1'
 
 # The Documentation full version, including alpha/beta/rc tags. Some features
 # available in the latest code will not necessarily be documented first
-release = '0.26.0'
+release = '0.25.1-rc.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

doc/sphinx/source/project/release-notes.rst

@@ -13,32 +13,18 @@ https://github.com/NervanaSystems/ngraph/releases.
 
 This page includes additional documentation updates.
 
-We are pleased to announce the release of version |version|-doc.
+We are pleased to announce the release of version |version|.
 
 
 Core updates for |version|
 --------------------------
 
-+ Better PlaidML support
-+ Double-buffering support
-+ Constant folding
-+ Support for static linking
-+ Additional ops
-+ Preliminary static linking support
-
-Known issues
-~~~~~~~~~~~~
-
-• No training support
-• 5 functional TensorFlow models and 4 functional ONNX models may experience performance degradations if upgraded from a previous version.
+Allow DLLs that link nGraph statically to load backends
 
 
 Latest doc updates |version|-doc
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-+ Instructions how to build ``NGRAPH_PLAIDML`` backend added to :doc:`../buildlb`. 
-+ Publishing interim version of doc navigation for updates at ngraph.ai
-
 
 
 .. important:: Pre-releases (``-rc-0.*``) have newer features, and are less stable.  
@@ -47,6 +33,23 @@ Latest doc updates |version|-doc
 Changelog on Previous Releases
 ==============================
 
+
+0.25.0
+------
+
++ Better PlaidML support
++ Double-buffering support
++ Constant folding
++ Support for static linking
++ Additional ops
++ Preliminary static linking support
++ Known issue: No training support
++ Instructions how to build NGRAPH_PLAIDML backend
++ Publishing interim version of doc navigation for updates at ngraph.ai
++ GPU validations: added 5 functional TensorFlow workloads and 4 functional 
+  ONNX workloads
+
+
 0.24
 ----