v1.6 release note

README.md

@@ -25,7 +25,7 @@ The tool manages automated machine learning (AutoML) experiments, **dispatches a
 * Researchers and data scientists who want to easily **implement and experiment new AutoML algorithms**, may it be: hyperparameter tuning algorithm, neural architect search algorithm or model compression algorithm.
 * ML Platform owners who want to **support AutoML in their platform**.
 
-### **[NNI v1.5 has been released!](https://github.com/microsoft/nni/releases) &nbsp;<a href="#nni-released-reminder"><img width="48" src="docs/img/release_icon.png"></a>**
+### **[NNI v1.6 has been released!](https://github.com/microsoft/nni/releases) &nbsp;<a href="#nni-released-reminder"><img width="48" src="docs/img/release_icon.png"></a>**
 
 ## **NNI capabilities in a glance**
 
@@ -239,7 +239,7 @@ The following example is built on TensorFlow 1.x. Make sure **TensorFlow 1.x is
 * Download the examples via clone the source code.
 
   ```bash
-  git clone -b v1.5 https://github.com/Microsoft/nni.git
+  git clone -b v1.6 https://github.com/Microsoft/nni.git
   ```
 
 * Run the MNIST example.

docs/en_US/Release.md

@@ -1,5 +1,46 @@
 # ChangeLog
 
+## Release 1.6 - 5/26/2020
+
+### Major Features
+
+#### New Features and improvement
+* Improve IPC limitation to 100W
+* improve code storage upload logic among trials in non-local platform
+* support `__version__` for SDK version
+* support windows dev intall
+
+#### Web UI
+* Show trial error message
+* finalize homepage layout
+* Refactor overview's best trials module
+* Remove multiphase from webui
+* add tooltip for trial concurrency in the overview page
+* Show top trials for hyper-parameter graph
+
+#### HPO Updates
+* Improve PBT on failure handling and support experiment resume for PBT
+
+#### NAS Updates
+* NAS support for TensorFlow 2.0 (preview) [TF2.0 NAS examples](https://github.com/microsoft/nni/tree/master/examples/nas/naive-tf)
+* Use OrderedDict for LayerChoice
+* Prettify the format of export
+* Replace layer choice with selected module after applied fixed architecture
+
+#### Model Compression Updates
+* Model compression PyTorch 1.4 support
+
+#### Training Service Updates
+* update pai yaml merge logic
+* support windows as remote machine in remote mode [Remote Mode](https://github.com/microsoft/nni/blob/master/docs/en_US/TrainingService/RemoteMachineMode.md#windows)
+
+### Bug Fix
+* fix dev install
+* SPOS example crash when the checkpoints do not have state_dict
+* Fix table sort issue when experiment had failed trial
+* Support multi python env (conda, pyenv etc)
+
+
 ## Release 1.5 - 4/13/2020
 
 ### New Features and Documentation