Release note v1.8 (#2829)

* Replace all v1.7 with v1.8

* Add v1.8 release note

* Change PAI into OpenPAI

* Update Release.md

* Refine relase note

* Update date of release
Co-authored-by: QuanluZhang <z.quanluzhang@gmail.com>

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 v1.7 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 v1.8 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**
 
@@ -246,7 +246,7 @@ 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 v1.7 https://github.com/Microsoft/nni.git
+  git clone -b v1.8 https://github.com/Microsoft/nni.git
   ```
 
 * Run the MNIST example.

docs/en_US/NAS/Benchmarks.md

@@ -25,7 +25,7 @@ To avoid storage and legality issues, we do not provide any prepared databases.
 git clone -b ${NNI_VERSION} https://github.com/microsoft/nni
 cd nni/examples/nas/benchmarks
 ```
-Replace `${NNI_VERSION}` with a released version name or branch name, e.g., `v1.7`.
+Replace `${NNI_VERSION}` with a released version name or branch name, e.g., `v1.8`.
 
 2. Install dependencies via `pip3 install -r xxx.requirements.txt`. `xxx` can be `nasbench101`, `nasbench201` or `nds`.
 3. Generate the database via `./xxx.sh`. The directory that stores the benchmark file can be configured with `NASBENCHMARK_DIR` environment variable, which defaults to `~/.nni/nasbenchmark`. Note that the NAS-Bench-201 dataset will be downloaded from a google drive.

docs/en_US/Release.md

 # ChangeLog
 
+# Release 1.8 - 8/27/2020
+
+## Major updates
+
+### Training service
+
+* Access trial log directly on WebUI (local mode only) (#2718)
+* Add OpenPAI trial job detail link (#2703)
+* Support GPU scheduler in reusable environment (#2627) (#2769)
+* Add timeout for `web_channel` in `trial_runner` (#2710)
+* Show environment error message in AzureML mode (#2724)
+* Add more log information when copying data in OpenPAI mode (#2702)
+
+### WebUI, nnictl and nnicli
+
+* Improve hyper-parameter parallel coordinates plot (#2691) (#2759)
+* Add pagination for trial job list (#2738) (#2773)
+* Enable panel close when clicking overlay region (#2734)
+* Remove support for Multiphase on WebUI (#2760)
+* Support save and restore experiments (#2750)
+* Add intermediate results in export result (#2706)
+* Add [command](https://github.com/microsoft/nni/blob/v1.8/docs/en_US/Tutorial/Nnictl.md#nnictl-trial) to list trial results with highest/lowest metrics (#2747)
+* Improve the user experience of [nnicli](https://github.com/microsoft/nni/blob/v1.8/docs/en_US/nnicli_ref.md) with [examples](https://github.com/microsoft/nni/blob/v1.8/examples/notebooks/retrieve_nni_info_with_python.ipynb) (#2713)
+
+### Neural architecture search
+
+* [Search space zoo: ENAS and DARTS](https://github.com/microsoft/nni/blob/v1.8/docs/en_US/NAS/SearchSpaceZoo.md) (#2589)
+* API to query intermediate results in NAS benchmark (#2728)
+
+### Model compression
+
+* Support the List/Tuple Construct/Unpack operation for TorchModuleGraph (#2609)
+* Model speedup improvement: Add support of DenseNet and InceptionV3 (#2719)
+* Support the multiple successive tuple unpack operations (#2768)
+* [Doc of comparing the performance of supported pruners](https://github.com/microsoft/nni/blob/v1.8/docs/en_US/CommunitySharings/ModelCompressionComparison.md) (#2742)
+* New pruners: [Sensitivity pruner](https://github.com/microsoft/nni/blob/v1.8/docs/en_US/Compressor/Pruner.md#sensitivity-pruner) (#2684) and [AMC pruner](https://github.com/microsoft/nni/blob/v1.8/docs/en_US/Compressor/Pruner.md) (#2573) (#2786)
+* TensorFlow v2 support in model compression (#2755)
+
+### Backward incompatible changes
+
+* Update the default experiment folder from `$HOME/nni/experiments` to `$HOME/nni-experiments`. If you want to view the experiments created by previous NNI releases, you can move the experiments folders from  `$HOME/nni/experiments` to `$HOME/nni-experiments` manually. (#2686) (#2753)
+* Dropped support for Python 3.5 and scikit-learn 0.20 (#2778) (#2777) (2783) (#2787) (#2788) (#2790)
+
+### Others
+
+* Upgrade TensorFlow version in Docker image (#2732) (#2735) (#2720)
+
+## Examples
+
+* Remove gpuNum in assessor examples (#2641)
+
+## Documentation
+
+* Improve customized tuner documentation (#2628)
+* Fix several typos and grammar mistakes in documentation (#2637 #2638, thanks @tomzx)
+* Improve AzureML training service documentation (#2631)
+* Improve CI of Chinese translation (#2654)
+* Improve OpenPAI training service documenation (#2685)
+* Improve documentation of community sharing (#2640)
+* Add tutorial of Colab support (#2700)
+* Improve documentation structure for model compression (#2676)
+
+## Bug fixes
+
+* Fix mkdir error in training service (#2673)
+* Fix bug when using chmod in remote training service (#2689)
+* Fix dependency issue by making `_graph_utils` imported inline (#2675)
+* Fix mask issue in `SimulatedAnnealingPruner` (#2736)
+* Fix intermediate graph zooming issue (#2738)
+* Fix issue when dict is unordered when querying NAS benchmark (#2728)
+* Fix import issue for gradient selector dataloader iterator (#2690)
+* Fix support of adding tens of machines in remote training service (#2725)
+* Fix several styling issues in WebUI (#2762 #2737)
+* Fix support of unusual types in metrics including NaN and Infinity (#2782)
+* Fix nnictl experiment delete (#2791)
+
 # Release 1.7 - 7/8/2020
 
 ## Major Features

docs/en_US/TrainingService/AMLMode.md

@@ -89,4 +89,4 @@ cd nni/examples/trials/mnist-tfv1
 
 nnictl create --config config_aml.yml
 ```
-Replace `${NNI_VERSION}` with a released version name or branch name, e.g., `v1.7`.
+Replace `${NNI_VERSION}` with a released version name or branch name, e.g., `v1.8`.

docs/en_US/Tutorial/InstallationLinux.md

@@ -19,7 +19,7 @@ Installation on Linux and macOS follow the same instructions, given below.
   Prerequisites: `python 64-bit >=3.6`, `git`, `wget`
 
   ```bash
-  git clone -b v1.7 https://github.com/Microsoft/nni.git
+  git clone -b v1.8 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 cloning the source code.
 
   ```bash
-  git clone -b v1.7 https://github.com/Microsoft/nni.git
+  git clone -b v1.8 https://github.com/Microsoft/nni.git
   ```
 
 * Run the MNIST example.

docs/en_US/Tutorial/InstallationWin.md

@@ -29,7 +29,7 @@ If you want to contribute to NNI, refer to [setup development environment](Setup
 * From source code
 
     ```bat
-    git clone -b v1.7 https://github.com/Microsoft/nni.git
+    git clone -b v1.8 https://github.com/Microsoft/nni.git
     cd nni
     powershell -ExecutionPolicy Bypass -file install.ps1
     ```
@@ -41,7 +41,7 @@ The following example is built on TensorFlow 1.x. Make sure **TensorFlow 1.x is
 * Clone examples within source code.
 
     ```bat
-    git clone -b v1.7 https://github.com/Microsoft/nni.git
+    git clone -b v1.8 https://github.com/Microsoft/nni.git
     ```
 
 * Run the MNIST example.

docs/en_US/conf.py

@@ -29,7 +29,7 @@ author = 'Microsoft'
 # The short X.Y version
 version = ''
 # The full version, including alpha/beta/rc tags
-release = 'v1.7'
+release = 'v1.8'
 
 # -- General configuration ---------------------------------------------------