Merge master into dev-retiarii (#3178)

.gitignore

@@ -81,6 +81,7 @@ typings/
 __pycache__
 build
 *.egg-info
+.eggs/
 setup.pye
 **/__init__.pye
 **/.ipynb_checkpoints

deployment/docker/Dockerfile → Dockerfile

@@ -3,12 +3,15 @@
 
 FROM nvidia/cuda:9.2-cudnn7-runtime-ubuntu18.04
 
+ARG NNI_RELEASE
+
 LABEL maintainer='Microsoft NNI Team<nni@microsoft.com>'
 
 ENV DEBIAN_FRONTEND=noninteractive 
 
-RUN apt-get -y update && \
-    apt-get -y install sudo \
+RUN apt-get -y update
+RUN apt-get -y install \
+    sudo \
     apt-utils \
     git \
     curl \
@@ -26,28 +29,27 @@ RUN apt-get -y update && \
     python3-dev \
     python3-pip \
     python3-tk \
-    libcupti-dev && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
+    libcupti-dev
+RUN apt-get clean
+RUN rm -rf /var/lib/apt/lists/*
 
 #
 # generate python script
 #
-RUN cp /usr/bin/python3 /usr/bin/python
+RUN ln -s python3 /usr/bin/python
 
 #
 # update pip
 #
-RUN python3 -m pip install --upgrade pip==20.0.2 setuptools==41.0.0
+RUN python3 -m pip install --upgrade pip==20.2.4 setuptools==50.3.2
 
 # numpy 1.14.3  scipy 1.1.0
-RUN python3 -m pip --no-cache-dir install \
-    numpy==1.14.3 scipy==1.1.0
+RUN python3 -m pip --no-cache-dir install numpy==1.14.3 scipy==1.1.0
 
 #
-# Tensorflow 1.15
+# TensorFlow
 #
-RUN python3 -m pip --no-cache-dir install tensorflow-gpu==1.15.0
+RUN python3 -m pip --no-cache-dir install tensorflow==2.3.1
 
 #
 # Keras 2.1.6
@@ -73,7 +75,8 @@ RUN python3 -m pip --no-cache-dir install pandas==0.23.4 lightgbm==2.2.2
 #
 # Install NNI
 #
-RUN python3 -m pip --no-cache-dir install nni
+COPY dist/nni-${NNI_RELEASE}-py3-none-manylinux1_x86_64.whl .
+RUN python3 -m pip install nni-${NNI_RELEASE}-py3-none-manylinux1_x86_64.whl
 
 #
 # install aml package
@@ -81,7 +84,6 @@ RUN python3 -m pip --no-cache-dir install nni
 RUN python3 -m pip --no-cache-dir install azureml
 RUN python3 -m pip --no-cache-dir install azureml-sdk
 
-
 ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/root/.local/bin:/usr/bin:/bin:/sbin
 
 WORKDIR /root

README.md

@@ -16,7 +16,7 @@
 
 **NNI (Neural Network Intelligence)** is a lightweight but powerful toolkit to help users **automate** <a href="docs/en_US/FeatureEngineering/Overview.md">Feature Engineering</a>, <a href="docs/en_US/NAS/Overview.md">Neural Architecture Search</a>, <a href="docs/en_US/Tuner/BuiltinTuner.md">Hyperparameter Tuning</a> and <a href="docs/en_US/Compression/Overview.md">Model Compression</a>.
 
-The tool manages automated machine learning (AutoML) experiments, **dispatches and runs** experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in **different training environments** like <a href="docs/en_US/TrainingService/LocalMode.md">Local Machine</a>, <a href="docs/en_US/TrainingService/RemoteMachineMode.md">Remote Servers</a>, <a href="docs/en_US/TrainingService/PaiMode.md">OpenPAI</a>, <a href="docs/en_US/TrainingService/KubeflowMode.md">Kubeflow</a>, <a href="docs/en_US/TrainingService/FrameworkControllerMode.md">FrameworkController on K8S (AKS etc.)</a>, <a href="docs/en_US/TrainingService/DLTSMode.md">DLWorkspace (aka. DLTS)</a>, <a href="docs/en_US/TrainingService/AMLMode.md">AML (Azure Machine Learning)</a> and other cloud options.
+The tool manages automated machine learning (AutoML) experiments, **dispatches and runs** experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in **different training environments** like <a href="docs/en_US/TrainingService/LocalMode.md">Local Machine</a>, <a href="docs/en_US/TrainingService/RemoteMachineMode.md">Remote Servers</a>, <a href="docs/en_US/TrainingService/PaiMode.md">OpenPAI</a>, <a href="docs/en_US/TrainingService/KubeflowMode.md">Kubeflow</a>, <a href="docs/en_US/TrainingService/FrameworkControllerMode.md">FrameworkController on K8S (AKS etc.)</a>, <a href="docs/en_US/TrainingService/DLTSMode.md">DLWorkspace (aka. DLTS)</a>, <a href="docs/en_US/TrainingService/AMLMode.md">AML (Azure Machine Learning)</a>, <a href="docs/en_US/TrainingService/AdaptDLMode.md">AdaptDL (aka. ADL)</a> and other cloud options.
 
 ## **Who should consider using NNI**
 
@@ -173,11 +173,13 @@ Within the following table, we summarized the current NNI capabilities, we are g
         <li><a href="docs/en_US/TrainingService/RemoteMachineMode.md">Remote Servers</a></li>
         <li><a href="docs/en_US/TrainingService/AMLMode.md">AML(Azure Machine Learning)</a></li>
         <li><b>Kubernetes based services</b></li>
-            <ul><li><a href="docs/en_US/TrainingService/PaiMode.md">OpenPAI</a></li>
+        <ul>
+          <li><a href="docs/en_US/TrainingService/PaiMode.md">OpenPAI</a></li>
           <li><a href="docs/en_US/TrainingService/KubeflowMode.md">Kubeflow</a></li>
           <li><a href="docs/en_US/TrainingService/FrameworkControllerMode.md">FrameworkController on K8S (AKS etc.)</a></li>
+          <li><a href="docs/en_US/TrainingService/DLTSMode.md">DLWorkspace (aka. DLTS)</a></li>
+          <li><a href="docs/en_US/TrainingService/AdaptDLMode.md">AdaptDL (aka. ADL)</a></li>
         </ul>
-            <ul><li><a href="docs/en_US/TrainingService/DLTSMode.md">DLWorkspace (aka. DLTS)</a></li>
       </ul>
       </td>
     </tr>