Update python version requirements to 3.6 (#2790)

README.md

@@ -215,7 +215,7 @@ Within the following table, we summarized the current NNI capabilities, we are g
 
 ### **Install**
 
-NNI supports and is tested on Ubuntu >= 16.04, macOS >= 10.14.1, and Windows 10 >= 1809. Simply run the following `pip install` in an environment that has `python 64-bit >= 3.5`.
+NNI supports and is tested on Ubuntu >= 16.04, macOS >= 10.14.1, and Windows 10 >= 1809. Simply run the following `pip install` in an environment that has `python 64-bit >= 3.6`.
 
 Linux or macOS
 

docs/en_US/SupportedFramework_Library.md

 # Framework and Library Supports 
-With the built-in Python API, NNI naturally supports the hyper parameter tuning and neural network search for all the AI frameworks and libraries who support Python models(`version >= 3.5`). NNI had also provided a set of examples and tutorials for some of the popular scenarios to make jump start easier.
+With the built-in Python API, NNI naturally supports the hyper parameter tuning and neural network search for all the AI frameworks and libraries who support Python models(`version >= 3.6`). NNI had also provided a set of examples and tutorials for some of the popular scenarios to make jump start easier.
 
 ## Supported AI Frameworks
 

docs/en_US/Tutorial/InstallationLinux.md

@@ -6,7 +6,7 @@ Installation on Linux and macOS follow the same instructions, given below.
 
 ### Install NNI through pip
 
-  Prerequisite: `python 64-bit >= 3.5`
+  Prerequisite: `python 64-bit >= 3.6`
 
   ```bash
   python3 -m pip install --upgrade nni
@@ -16,7 +16,7 @@ Installation on Linux and macOS follow the same instructions, given below.
 
   If you are interested in special or the latest code versions, you can install NNI through source code.
 
-  Prerequisites: `python 64-bit >=3.5`, `git`, `wget`
+  Prerequisites: `python 64-bit >=3.6`, `git`, `wget`
 
   ```bash
   git clone -b v1.7 https://github.com/Microsoft/nni.git

docs/en_US/Tutorial/InstallationWin.md

@@ -2,7 +2,7 @@
 
 ## Prerequires
 
-* 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.
+* Python 3.6 (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.
 
 * 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`.
 

docs/en_US/Tutorial/QuickStart.md

@@ -2,7 +2,7 @@
 
 ## Installation
 
-We currently support Linux, macOS, and Windows. Ubuntu 16.04 or higher, macOS 10.14.1, and Windows 10.1809 are tested and supported. Simply run the following `pip install` in an environment that has `python >= 3.5`.
+We currently support Linux, macOS, and Windows. Ubuntu 16.04 or higher, macOS 10.14.1, and Windows 10.1809 are tested and supported. Simply run the following `pip install` in an environment that has `python >= 3.6`.
 
 ### Linux and macOS
 

docs/en_US/_templates/index.html

@@ -237,7 +237,7 @@
     <p>
       NNI supports and is tested on Ubuntu >= 16.04, macOS >= 10.14.1,
       and Windows 10 >= 1809. Simply run the following `pip install`
-      in an environment that has `python 64-bit >= 3.5`.
+      in an environment that has `python 64-bit >= 3.6`.
     </p>
     <div class="command-intro">Linux or macOS</div>
     <div class="command">python3 -m pip install --upgrade nni</div>

examples/tuners/customized_tuner/setup.py

@@ -8,7 +8,7 @@ setuptools.setup(
     version = '0.1',
     packages = setuptools.find_packages(exclude=['*test*']),
 
-    python_requires = '>=3.5',
+    python_requires = '>=3.6',
     classifiers = [
         'Programming Language :: Python :: 3',
         'License :: OSI Approved :: MIT License',

setup.py

@@ -27,7 +27,7 @@ setup(
         'nni_gpu_tool':'tools/nni_gpu_tool'
     },
     package_data = {'nni': ['**/requirements.txt']},
-    python_requires = '>=3.5',
+    python_requires = '>=3.6',
     install_requires = [
         'astor',
         'hyperopt==0.1.2',

src/sdk/pycli/setup.py

@@ -8,7 +8,7 @@ setuptools.setup(
     version='999.0.0-developing',
     packages=setuptools.find_packages(),
 
-    python_requires='>=3.5',
+    python_requires='>=3.6',
     install_requires=[
         'requests'
     ],

src/sdk/pynni/setup.py

@@ -12,7 +12,7 @@ setuptools.setup(
     version = '999.0.0-developing',
     packages = setuptools.find_packages(exclude=['tests']),
 
-    python_requires = '>=3.5',
+    python_requires = '>=3.6',
     install_requires = [
         'hyperopt==0.1.2',
         'json_tricks',

tools/README.md

@@ -4,7 +4,7 @@ The NNI CTL module is used to control Neural Network Intelligence, including sta
 
 ```
 Ubuntu 16.04 or other Linux OS
-python >= 3.5
+python >= 3.6
 ```
 
 ## Installation

tools/setup.py

@@ -8,7 +8,7 @@ setuptools.setup(
     version = '999.0.0-developing',
     packages = setuptools.find_packages(exclude=['*test*']),
 
-    python_requires = '>=3.5',
+    python_requires = '>=3.6',
     install_requires = [
         'requests',
         'ruamel.yaml',