update (#2078)

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 experiement 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 v1.3 has been released! &nbsp;<a href="#nni-released-reminder"><img width="48" src="docs/img/release_icon.png"></a>**
+### **NNI v1.4 has been released! &nbsp;<a href="#nni-released-reminder"><img width="48" src="docs/img/release_icon.png"></a>**
 
 ## **NNI capabilities in a glance**
 NNI provides CommandLine Tool as well as an user friendly WebUI to manage training experiements. With the extensible API, you can customize your own AutoML algorithms and training services. To make it easy for new users, NNI also provides a set of build-in stat-of-the-art AutoML algorithms and out of box support for popular training platforms. 
@@ -233,7 +233,7 @@ 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 v1.3 https://github.com/Microsoft/nni.git
+  git clone -b v1.4 https://github.com/Microsoft/nni.git
   ```
 
 * Run the MNIST example.

docs/en_US/Release.md

@@ -1,5 +1,45 @@
 # ChangeLog
 
+## Release 1.4 - 2/19/2020
+
+### Major Features
+
+#### Neural Architecture Search
+* Support [C-DARTS](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/NAS/CDARTS.md) algorithm and add [the example](https://github.com/microsoft/nni/tree/v1.4/examples/nas/cdarts) using it
+* Support a preliminary version of [ProxylessNAS](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/NAS/Proxylessnas.md) and the corresponding [example](https://github.com/microsoft/nni/tree/v1.4/examples/nas/proxylessnas)
+* Add unit tests for the NAS framework
+
+#### Model Compression
+* Support DataParallel for compressing models, and provide [an example](https://github.com/microsoft/nni/blob/v1.4/examples/model_compress/multi_gpu.py) of using DataParallel
+* Support [model speedup](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/Compressor/ModelSpeedup.md) for compressed models, in Alpha version
+
+#### Training Service
+* Support complete PAI configurations by allowing users to specify PAI config file path
+* Add example config yaml files for the new PAI mode (i.e., paiK8S)
+* Support deleting experiments using sshkey in remote mode (thanks external contributor @tyusr)
+
+#### WebUI
+* WebUI refactor: adopt fabric framework
+
+#### Others
+* Support running [NNI experiment at foreground](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/Tutorial/Nnictl.md#manage-an-experiment), i.e., `--foreground` argument in `nnictl create/resume/view`
+* Support canceling the trials in UNKNOWN state
+* Support large search space whose size could be up to 50mb (thanks external contributor @Sundrops)
+
+### Documentation
+* Improve [the index structure](https://nni.readthedocs.io/en/latest/) of NNI readthedocs
+* Improve [documentation for NAS](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/NAS/NasGuide.md)
+* Improve documentation for [the new PAI mode](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/TrainingService/PaiMode.md)
+* Add QuickStart guidance for [NAS](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/NAS/QuickStart.md) and [model compression](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/Compressor/QuickStart.md)
+* Improve documentation for [the supported EfficientNet](https://github.com/microsoft/nni/blob/v1.4/docs/en_US/TrialExample/EfficientNet.md)
+
+### Bug Fixes
+* Correctly support NaN in metric data, JSON compliant
+* Fix the out-of-range bug of `randint` type in search space
+* Fix the bug of wrong tensor device when exporting onnx model in model compression
+* Fix incorrect handling of nnimanagerIP in the new PAI mode (i.e., paiK8S)
+
+
 ## Release 1.3 - 12/30/2019
 
 ### Major Features

docs/en_US/Tutorial/InstallationLinux.md

@@ -19,7 +19,7 @@ Installation on Linux and macOS follow the same instruction below.
   Prerequisites: `python 64-bit >=3.5`, `git`, `wget`
 
   ```bash
-  git clone -b v1.3 https://github.com/Microsoft/nni.git
+  git clone -b v1.4 https://github.com/Microsoft/nni.git
   cd nni
   ./install.sh
   ```
@@ -35,7 +35,7 @@ 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 v1.3 https://github.com/Microsoft/nni.git
+  git clone -b v1.4 https://github.com/Microsoft/nni.git
   ```
 
 * Run the MNIST example.

docs/en_US/Tutorial/InstallationWin.md

@@ -19,7 +19,7 @@ Anaconda or Miniconda is highly recommended to manage multiple Python environmen
   Prerequisites: `python 64-bit >=3.5`, `git`, `PowerShell`.
 
   ```bash
-  git clone -b v1.3 https://github.com/Microsoft/nni.git
+  git clone -b v1.4 https://github.com/Microsoft/nni.git
   cd nni
   powershell -ExecutionPolicy Bypass -file install.ps1
   ```
@@ -31,7 +31,7 @@ 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 v1.3 https://github.com/Microsoft/nni.git
+  git clone -b v1.4 https://github.com/Microsoft/nni.git
   ```
 
 * Run the MNIST example.

docs/en_US/conf.py

@@ -28,7 +28,7 @@
 # The short X.Y version
 version = ''
 # The full version, including alpha/beta/rc tags
-release = 'v1.3'
+release = 'v1.4'
 
 # -- General configuration ---------------------------------------------------