update version number, copyright year, class name (#3285)

docs/en_US/CommunitySharings/AutoCompletion.rst

@@ -25,7 +25,7 @@ Step 1. Download ``bash-completion``
    cd ~
    wget https://raw.githubusercontent.com/microsoft/nni/{nni-version}/tools/bash-completion
 
-Here, {nni-version} should by replaced by the version of NNI, e.g., ``master``\ , ``v1.9``. You can also check the latest ``bash-completion`` script :githublink:`here <tools/bash-completion>`.
+Here, {nni-version} should by replaced by the version of NNI, e.g., ``master``, ``v2.0``. You can also check the latest ``bash-completion`` script :githublink:`here <tools/bash-completion>`.
 
 .. cannot find :githublink:`here <tools/bash-completion>`.
 

docs/en_US/NAS/Benchmarks.rst

@@ -32,7 +32,7 @@ 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 ``${NNI_VERSION}`` with a released version name or branch name, e.g., ``v1.9``.
+   Replace ``${NNI_VERSION}`` with a released version name or branch name, e.g., ``v2.0``.
 
 #. 
    Install dependencies via ``pip3 install -r xxx.requirements.txt``. ``xxx`` can be ``nasbench101``\ , ``nasbench201`` or ``nds``.

docs/en_US/TrialExample/SquadEvolutionExamples.rst

@@ -120,7 +120,7 @@ Modify ``nni/examples/trials/ga_squad/config_pai.yml``\ , here is the default co
    #Your nni_manager ip
    nniManagerIp: 10.10.10.10
    tuner:
-     codeDir: https://github.com/Microsoft/nni/tree/v1.9/examples/tuners/ga_customer_tuner
+     codeDir: https://github.com/Microsoft/nni/tree/v2.0/examples/tuners/ga_customer_tuner
      classFileName: customer_tuner.py
      className: CustomerTuner
      classArgs:

docs/en_US/Tutorial/Contributing.rst

@@ -71,4 +71,4 @@ Our documentation is built with :githublink:`sphinx <docs>`.
 
 
   * It's an image link which needs to be formatted with embedded html grammar, please use global URL like ``https://user-images.githubusercontent.com/44491713/51381727-e3d0f780-1b4f-11e9-96ab-d26b9198ba65.png``, which can be automatically generated by dragging picture onto `Github Issue <https://github.com/Microsoft/nni/issues/new>`__ Box.
-  * It cannot be re-formatted by sphinx, such as source code, please use its global URL. For source code that links to our github repo, please use URLs rooted at ``https://github.com/Microsoft/nni/tree/v1.9/`` (:githublink:`mnist.py <examples/trials/mnist-pytorch/mnist.py>` for example).
+  * It cannot be re-formatted by sphinx, such as source code, please use its global URL. For source code that links to our github repo, please use URLs rooted at ``https://github.com/Microsoft/nni/tree/v2.0/`` (:githublink:`mnist.py <examples/trials/mnist-pytorch/mnist.py>` for example).

docs/en_US/Tutorial/InstallationWin.rst

@@ -52,7 +52,7 @@ Verify installation
 
   .. code-block:: bat
 
-       git clone -b v1.9 https://github.com/Microsoft/nni.git
+       git clone -b v2.0 https://github.com/Microsoft/nni.git
 
 * 
   Run the MNIST example.

docs/en_US/conf.py

@@ -21,13 +21,13 @@ sys.path.insert(0, os.path.abspath('../..'))
 # -- Project information ---------------------------------------------------
 
 project = 'NNI'
-copyright = '2020, Microsoft'
+copyright = '2021, Microsoft'
 author = 'Microsoft'
 
 # The short X.Y version
 version = ''
 # The full version, including alpha/beta/rc tags
-release = 'v1.9'
+release = 'v2.0'
 
 # -- General configuration ---------------------------------------------------
 

docs/en_US/nnicli_ref.rst

 NNI Client
 ==========
 
-NNI client is a python API of ``nnictl``\ , which implements the most commonly used commands. Users can use this API to control their experiments, collect experiment results and conduct advanced analyses based on experiment results in python code directly instead of using command line. Here is an example:
+NNI client is a python API of ``nnictl``, which implements the most commonly used commands. Users can use this API to control their experiments, collect experiment results and conduct advanced analyses based on experiment results in python code directly instead of using command line. Here is an example:
 
 .. code-block:: bash
 
-   from nni.experiment import Experiment
+   from nni.experiment import LegacyExperiment
 
    # create an experiment instance
-   exp = Experiment() 
+   exp = LegacyExperiment()
 
    # start an experiment, then connect the instance to this experiment
    # you can also use `resume_experiment`, `view_experiment` or `connect_experiment`