pull code

azure-pipelines.yml

@@ -21,6 +21,9 @@ jobs:
       set -e
       cd src/nni_manager
       yarn eslint
+      # uncomment following 2 lines to enable webui eslint
+      # cd ../webui
+      # yarn eslint
     displayName: 'Run eslint'
   - script: |
       python3 -m pip install torch==0.4.1 --user
@@ -43,7 +46,7 @@ jobs:
     displayName: 'Run pylint'
   - script: |
       python3 -m pip install flake8 --user
-      EXCLUDES=./src/nni_manager/,./tools/nni_annotation/testcase/,./examples/trials/mnist-nas/*/mnist*.py,./examples/trials/nas_cifar10/src/cifar10/general_child.py
+      EXCLUDES=./src/nni_manager/,./src/webui,./tools/nni_annotation/testcase/,./examples/trials/mnist-nas/*/mnist*.py,./examples/trials/nas_cifar10/src/cifar10/general_child.py
       python3 -m flake8 . --count --exclude=$EXCLUDES --select=E9,F63,F72,F82 --show-source --statistics
     displayName: 'Run flake8 tests to find Python syntax errors and undefined names'
   - script: |

docs/en_US/TrainingService/RemoteMachineMode.md

@@ -16,9 +16,9 @@ Install NNI on each of your machines following the install guide [here](../Tutor
 
 ## Run an experiment
 
-Install NNI on another machine which has network accessibility to those three machines above, or you can just use any machine above to run nnictl command line tool.
+Install NNI on another machine which has network accessibility to those three machines above, or you can just run `nnictl` on any one of the three to launch the experiment.
 
-We use `examples/trials/mnist-annotation` as an example here. `cat ~/nni/examples/trials/mnist-annotation/config_remote.yml` to see the detailed configuration file:
+We use `examples/trials/mnist-annotation` as an example here. Shown here is `examples/trials/mnist-annotation/config_remote.yml`:
 
 ```yaml
 authorName: default
@@ -57,24 +57,15 @@ machineList:
     username: bob
     passwd: bob123
 ```
-You can use different systems to run experiments on the remote machine.
-#### Linux and MacOS
-Simply filling the `machineList` section and then run:
 
-```bash
-nnictl create --config ~/nni/examples/trials/mnist-annotation/config_remote.yml
-```
-
-to start the experiment.
-
-#### Windows
-Simply filling the `machineList` section and then run:
+Files in `codeDir` will be automatically uploaded to the remote machine. You can run NNI on different operating systems (Windows, Linux, MacOS) to spawn experiments on the remote machines (only Linux allowed):
 
 ```bash
-nnictl create --config %userprofile%\nni\examples\trials\mnist-annotation\config_remote.yml
+nnictl create --config examples/trials/mnist-annotation/config_remote.yml
 ```
 
-to start the experiment.
+You can also use public/private key pairs instead of username/password for authentication. For advanced usages, please refer to [Experiment Config Reference](../Tutorial/ExperimentConfig.md).
+
+## Version check
 
-## version check
-NNI support version check feature in since version 0.6, [refer](PaiMode.md)
+NNI support version check feature in since version 0.6, [reference](PaiMode.md).

docs/en_US/TrialExample/SquadEvolutionExamples.md

@@ -112,10 +112,6 @@ trial:
   memoryMB: 32869
   #The docker image to run nni job on OpenPAI
   image: msranni/nni:latest
-  #The hdfs directory to store data on OpenPAI, format 'hdfs://host:port/directory'
-  dataDir: hdfs://10.10.10.10:9000/username/nni
-  #The hdfs directory to store output data generated by nni, format 'hdfs://host:port/directory'
-  outputDir: hdfs://10.10.10.10:9000/username/nni
 paiConfig:
   #The username to login OpenPAI
   userName: username
@@ -125,7 +121,7 @@ paiConfig:
   host: 10.10.10.10
 ```
 
-Please change the default value to your personal account and machine information. Including `nniManagerIp`, `dataDir`, `outputDir`, `userName`, `passWord` and `host`.
+Please change the default value to your personal account and machine information. Including `nniManagerIp`, `userName`, `passWord` and `host`.
 
 In the "trial" part, if you want to use GPU to perform the architecture search, change `gpuNum` from `0` to `1`. You need to increase the `maxTrialNum` and `maxExecDuration`, according to how long you want to wait for the search result.