chicm-ms · chicm-ms · May 25, 2020 · May 18, 2020 · May 18, 2020 · May 19, 2020
diff --git a/Makefile b/Makefile
@@ -167,6 +167,7 @@ install-dependencies: $(NNI_NODE_TARBALL) $(NNI_YARN_TARBALL)
 .PHONY: install-python-modules
 install-python-modules:
 	#$(_INFO) Installing Python SDK $(_END)
+	sed -ie 's/$(NNI_VERSION_TEMPLATE)/$(NNI_VERSION_VALUE)/' src/sdk/pynni/nni/__init__.py
 	sed -ie 's/$(NNI_VERSION_TEMPLATE)/$(NNI_VERSION_VALUE)/' setup.py && $(PIP_INSTALL) $(PIP_MODE) .
 
 .PHONY: dev-install-python-modules

diff --git a/README.md b/README.md
@@ -342,7 +342,7 @@ With authors' permission, we listed a set of NNI usage examples and relevant art
 Join IM discussion groups:
 |Gitter||WeChat|
 |----|----|----|
-|![image](https://user-images.githubusercontent.com/39592018/80665738-e0574a80-8acc-11ea-91bc-0836dc4cbf89.png)| OR |![image](https://github.com/JSong-Jia/NNI-user-group/blob/master/user%20group%20code_0512.jpg)|
+|![image](https://user-images.githubusercontent.com/39592018/80665738-e0574a80-8acc-11ea-91bc-0836dc4cbf89.png)| OR |![image](https://github.com/JSong-Jia/NNI-user-group/blob/master/user%20group%20code_0512.png)|
 
 
 ## Related Projects

diff --git a/deployment/pypi/Makefile b/deployment/pypi/Makefile
@@ -47,6 +47,7 @@ build:
 	cp $(CWD)../../src/nni_manager/package.json $(CWD)nni
 	sed -ie 's/$(NNI_VERSION_TEMPLATE)/$(NNI_VERSION_VALUE)/' $(CWD)nni/package.json
 	cd $(CWD)nni && $(NNI_YARN) --prod
+	sed -ie 's/$(NNI_VERSION_TEMPLATE)/$(NNI_VERSION_VALUE)/' $(CWD)../../src/sdk/pynni/nni/__init__.py
 	cd $(CWD) && sed -ie 's/$(NNI_VERSION_TEMPLATE)/$(NNI_VERSION_VALUE)/' setup.py && python3 setup.py bdist_wheel -p $(WHEEL_SPEC)
 	cd $(CWD)
 

diff --git a/deployment/pypi/install.ps1 b/deployment/pypi/install.ps1
@@ -60,6 +60,8 @@ Copy-Item $CWD\..\..\src\nni_manager\package.json $CWD\nni
 (Get-Content $CWD\nni\package.json).replace($NNI_VERSION_TEMPLATE, $NNI_VERSION_VALUE) | Set-Content $CWD\nni\package.json
 cd $CWD\nni
 yarn --prod
+cd $CWD\..\..\src\sdk\pynni\nni
+(Get-Content __init__.py).replace($NNI_VERSION_TEMPLATE, $NNI_VERSION_VALUE) | Set-Content __init__.py
 cd $CWD
 (Get-Content setup.py).replace($NNI_VERSION_TEMPLATE, $NNI_VERSION_VALUE) | Set-Content setup.py
 python setup.py bdist_wheel -p $WHEEL_SPEC
diff --git a/docs/en_US/TrainingService/PaiMode.md b/docs/en_US/TrainingService/PaiMode.md
@@ -7,9 +7,9 @@ Step 1. Install NNI, follow the install guide [here](../Tutorial/QuickStart.md).
 
 Step 2. Get PAI token.   
 Click `My profile` button in the top-right side of PAI's webprotal.
-![](../../img/pai_token_button.jpg)
-Find the token management region, copy one of the token as your account token.
-![](../../img/pai_token_profile.jpg)  
+![](../../img/pai_profile.jpg)  
+Click `copy` button in the page to copy a jwt token.
+![](../../img/pai_token.jpg)  
 
 Step 3. Mount NFS storage to local machine.  
   Click `Submit job` button in PAI's webportal.
@@ -19,7 +19,7 @@ Step 3. Mount NFS storage to local machine.
 The `DEFAULT_STORAGE`field is the path to be mounted in PAI's container when a job is started. The `Preview container paths` is the NFS host and path that PAI provided, you need to mount the corresponding host and path to your local machine first, then NNI could use the PAI's NFS storage.  
 For example, use the following command:
 ```
-sudo mount nfs://gcr-openpai-infra02:/pai/data /local/mnt
+sudo mount -t nfs4 gcr-openpai-infra02:/pai/data /local/mnt
 ```
 Then the `/data` folder in container will be mounted to `/local/mnt` folder in your local machine.  
 You could use the following configuration in your NNI's config file:
@@ -66,15 +66,15 @@ trial:
   virtualCluster: default
   nniManagerNFSMountPath: /home/user/mnt
   containerNFSMountPath: /mnt/data/user
-  paiStoragePlugin: team_wise
+  paiStoragePlugin: teamwise_storage
 # Configuration to access OpenPAI Cluster
 paiConfig:
   userName: your_pai_nni_user
   token: your_pai_token
   host: 10.1.1.1
 ```
 
-Note: You should set `trainingServicePlatform: pai` in NNI config YAML file if you want to start experiment in pai mode.
+Note: You should set `trainingServicePlatform: pai` in NNI config YAML file if you want to start experiment in pai mode. The host field in configuration file is PAI's job submission page uri, like `10.10.5.1`, the default http protocol in NNI is `http`, if your PAI's cluster enabled https, please use the uri in `https://10.10.5.1` format.
 
 Compared with [LocalMode](LocalMode.md) and [RemoteMachineMode](RemoteMachineMode.md), trial configuration in pai mode have these additional keys:
 * cpuNum

diff --git a/docs/en_US/TrainingService/RemoteMachineMode.md b/docs/en_US/TrainingService/RemoteMachineMode.md
@@ -2,18 +2,54 @@
 
 NNI can run one experiment on multiple remote machines through SSH, called `remote` mode. It's like a lightweight training platform. In this mode, NNI can be started from your computer, and dispatch trials to remote machines in parallel.
 
-## Remote machine requirements
+The OS of remote machines supports `Linux`, `Windows 10`, and `Windows Server 2019`.
 
-* It only supports Linux as remote machines, and [linux part in system specification](../Tutorial/InstallationLinux.md) is same as NNI local mode.
+## Requirements
 
-* Follow [installation](../Tutorial/InstallationLinux.md) to install NNI on each machine.
-
-* Make sure remote machines meet environment requirements of your trial code. If the default environment does not meet the requirements, the setup script can be added into `command` field of NNI config.
+* Make sure the default environment of remote machines meets requirements of your trial code. If the default environment does not meet the requirements, the setup script can be added into `command` field of NNI config.
 
 * Make sure remote machines can be accessed through SSH from the machine which runs `nnictl` command. It supports both password and key authentication of SSH. For advanced usages, please refer to [machineList part of configuration](../Tutorial/ExperimentConfig.md).
 
 * Make sure the NNI version on each machine is consistent.
 
+* Make sure the command of Trial is compatible with remote OSes, if you want to use remote Linux and Windows together. For example, the default python 3.x executable called `python3` on Linux, and `python` on Windows.
+
+### Linux
+
+* Follow [installation](../Tutorial/InstallationLinux.md) to install NNI on the remote machine.
+
+### Windows
+
+* Follow [installation](../Tutorial/InstallationWin.md) to install NNI on the remote machine.
+
+* Install and start `OpenSSH Server`.
+
+  1. Open `Settings` app on Windows.
+
+  2. Click `Apps`, then click `Optional features`.
+
+  3. Click `Add a feature`, search and select `OpenSSH Server`, and then click `Install`.
+
+  4. Once it's installed, run below command to start and set to automatic start.
+
+  ```bat
+  sc config sshd start=auto
+  net start sshd
+  ```
+
+* Make sure remote account is administrator, so that it can stop running trials.
+
+* Make sure there is no welcome message more than default, since it causes ssh2 failed in NodeJs. For example, if you're using Data Science VM on Azure, it needs to remove extra echo commands in `C:\dsvm\tools\setup\welcome.bat`.
+
+  The output like below is ok, when opening a new command window.
+
+  ```text
+  Microsoft Windows [Version 10.0.17763.1192]
+  (c) 2018 Microsoft Corporation. All rights reserved.
+
+  (py37_default) C:\Users\AzureUser>
+  ```
+
 ## Run an experiment
 
 e.g. there are three machines, which can be logged in with username and password.

diff --git a/docs/en_US/Tutorial/InstallationWin.md b/docs/en_US/Tutorial/InstallationWin.md
@@ -1,46 +1,56 @@
 # Install on Windows
 
-## Installation
+## Prerequires
 
-Anaconda or Miniconda is highly recommended to manage multiple Python environments.
+* Python 3.5 (or above) 64-bit. [Anaconda](https://www.anaconda.com/products/individual) or [Miniconda](https://docs.conda.io/en/latest/miniconda.html) is highly recommended to manage multiple Python environments on Windows.
 
-### Install NNI through pip
+* If it's a newly installed Python environment, it needs to install [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) to support build NNI dependencies like `scikit-learn`.
 
-  Prerequisites: `python 64-bit >= 3.5`
+    ```bat
+    pip install cython wheel
+    ```
 
-  ```bash
-  python -m pip install --upgrade nni
-  ```
+* git for verifying installation.
 
-### Install NNI through source code
+## Install NNI
 
-  If you are interested in special or the latest code versions, you can install NNI through source code.
+In most cases, you can install and upgrade NNI from pip package. It's easy and fast.
 
-  Prerequisites: `python 64-bit >=3.5`, `git`, `PowerShell`.
+If you are interested in special or the latest code versions, you can install NNI through source code.
 
-  ```bash
-  git clone -b v1.5 https://github.com/Microsoft/nni.git
-  cd nni
-  powershell -ExecutionPolicy Bypass -file install.ps1
-  ```
+If you want to contribute to NNI, refer to [setup development environment](SetupNniDeveloperEnvironment.md).
+
+* From pip package
+
+    ```bat
+    python -m pip install --upgrade nni
+    ```
+
+* From source code
+
+    ```bat
+    git clone -b v1.5 https://github.com/Microsoft/nni.git
+    cd nni
+    powershell -ExecutionPolicy Bypass -file install.ps1
+    ```
 
 ## Verify installation
 
 The following example is built on TensorFlow 1.x. Make sure **TensorFlow 1.x is used** when running it.
 
-* Download the examples via clone the source code.
+* Clone examples within source code.
 
-  ```bash
-  git clone -b v1.5 https://github.com/Microsoft/nni.git
-  ```
+    ```bat
+    git clone -b v1.5 https://github.com/Microsoft/nni.git
+    ```
 
 * Run the MNIST example.
 
-  ```bash
-  nnictl create --config nni\examples\trials\mnist-tfv1\config_windows.yml
-  ```
+    ```bat
+    nnictl create --config nni\examples\trials\mnist-tfv1\config_windows.yml
+    ```
 
-  Note: for other examples you need to change trial command `python3` to `python` in each example YAML, if python3 is called through `python` on your machine.
+    Note:  If you are familiar with other frameworks, you can choose corresponding example under `examples\trials`. It needs to change trial command `python3` to `python` in each example YAML, since default installation has `python.exe`, not `python3.exe` executable.
 
 * Wait for the message `INFO: Successfully started experiment!` in the command line. This message indicates that your experiment has been successfully started. You can explore the experiment using the `Web UI url`.
 
@@ -112,18 +122,20 @@ If there is a stderr file, please check it. Two possible cases are:
 * forgetting to install experiment dependencies such as TensorFlow, Keras and so on.
 
 ### Fail to use BOHB on Windows
+
 Make sure a C++ 14.0 compiler is installed when trying to run `nnictl package install --name=BOHB` to install the dependencies.
 
 ### Not supported tuner on Windows
+
 SMAC is not supported currently; for the specific reason refer to this [GitHub issue](https://github.com/automl/SMAC3/issues/483).
 
-### Use a Windows server as a remote worker
-Currently, you can't.
+### Use Windows as a remote worker
 
-Note:
+Refer to [Remote Machine mode](../TrainingService/RemoteMachineMode.md).
 
-* If an error like `Segmentation fault` is encountered, please refer to the [FAQ](FAQ.md)
+### Segmentation fault (core dumped) when installing
 
+Refer to [FAQ](FAQ.md).
 
 ## Further reading
 

diff --git a/docs/en_US/Tutorial/SetupNniDeveloperEnvironment.md b/docs/en_US/Tutorial/SetupNniDeveloperEnvironment.md
@@ -1,76 +1,59 @@
-**Set up NNI developer environment**
+# Setup NNI development environment
 
-===
+NNI development environment supports Ubuntu 1604 (or above), and Windows 10 with Python3 64bit.
 
-## Best practice for debug NNI source code
+## Installation
 
-For debugging NNI source code, your development environment should be under Ubuntu 16.04 (or above) system with python 3 and pip 3 installed, then follow the below steps.
+The installation steps are similar with installing from source code. But the installation links to code directory, so that code changes can be applied to installation as easy as possible.
 
-### 1. Clone the source code
+### 1. Clone source code
 
-Run the command
-
-```
+```bash
 git clone https://github.com/Microsoft/nni.git
 ```
 
-to clone the source code
+Note, if you want to contribute code back, it needs to fork your own NNI repo, and clone from there.
 
-### 2. Prepare the debug environment and install dependencies
+### 2. Install from source code
 
-Change directory to the source code folder, then run the command
+#### Ubuntu
 
+```bash
+make dev-easy-install
 ```
-make install-dependencies
-```
-
-to install the dependent tools for the environment
-
-### 3. Build source code
 
-Run the command
+#### Windows
 
+```bat
+powershell -ExecutionPolicy Bypass -file install.ps1 -Development
 ```
-make build
-```
-
-to build the source code
 
-### 4. Install NNI to development environment
-
-Run the command
-
-```
-make dev-install
-```
-
-to install the distribution content to development environment, and create cli scripts
-
-### 5. Check if the environment is ready
+### 3. Check if the environment is ready
 
 Now, you can try to start an experiment to check if your environment is ready.
 For example, run the command
 
-```
-nnictl create --config ~/nni/examples/trials/mnist-tfv1/config.yml
+```bash
+nnictl create --config examples/trials/mnist-tfv1/config.yml
 ```
 
 And open WebUI to check if everything is OK
 
-### 6. Redeploy
-
-After the code changes, it may need to redeploy. It depends on what kind of code changed. 
+### 4. Reload changes
 
 #### Python
 
-It doesn't need to redeploy, but the nnictl may need to be restarted.
+Nothing to do, the code is already linked to package folders.
 
 #### TypeScript
 
-* If `src/nni_manager` is changed, run `yarn watch` continually under this folder. It will rebuild code instantly. The nnictl may need to be restarted to reload NNI manager.
+* If `src/nni_manager` is changed, run `yarn watch` under this folder. It will watch and build code continually. The `nnictl` need to be restarted to reload NNI manager.
 * If `src/webui` or `src/nasui` are changed, run `yarn start` under the corresponding folder. The web UI will refresh automatically if code is changed.
 
+### 5. Submit Pull Request
+
+All changes are merged to master branch from your forked repo. The description of Pull Request must be meaningful, and useful.
+
+We will review the changes as soon as possible. Once it passes review, we will merge it to master branch.
 
----
-At last, wish you have a wonderful day.
-For more contribution guidelines on making PR's or issues to NNI source code, you can refer to our [Contributing](Contributing.md) document.
+For more contribution guidelines and coding styles, you can refer to the [contributing document](Contributing.md).
diff --git a/docs/img/pai_job_submission_page.jpg b/docs/img/pai_job_submission_page.jpg
diff --git a/docs/img/pai_profile.jpg b/docs/img/pai_profile.jpg
diff --git a/docs/img/pai_token.jpg b/docs/img/pai_token.jpg
diff --git a/docs/img/pai_token_profile.jpg b/docs/img/pai_token_profile.jpg
diff --git a/examples/nas/enas-tf/datasets.py b/examples/nas/enas-tf/datasets.py
@@ -0,0 +1,12 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT license.
+
+import tensorflow as tf
+from tensorflow.data import Dataset
+
+def get_dataset():
+    (x_train, y_train), (x_valid, y_valid) = tf.keras.datasets.cifar10.load_data()
+    x_train, x_valid = x_train / 255.0, x_valid / 255.0
+    train_set = (x_train, y_train)
+    valid_set = (x_valid, y_valid)
+    return train_set, valid_set