Move Jenkins test to Github action (#7342)

docker/autoscaler/Dockerfile

@@ -13,7 +13,6 @@ RUN apt update
 RUN apt install -y kubectl
 
 # We have to uninstall wrapt this way for Tensorflow compatibility
-RUN conda remove -y wrapt
 COPY requirements.txt .
 RUN pip install -r requirements.txt
 

docker/base-deps/Dockerfile

@@ -9,20 +9,24 @@ RUN apt-get update \
         build-essential \
         curl \
         unzip \
+        libgtk2.0-dev \
+        zlib1g-dev \
+        libgl1-mesa-dev \
     && apt-get clean \
     && echo 'export PATH=/opt/conda/bin:$PATH' > /etc/profile.d/conda.sh \
     && wget \
-        --quiet 'https://repo.continuum.io/archive/Anaconda3-5.2.0-Linux-x86_64.sh' \
+        --quiet "https://repo.anaconda.com/miniconda/Miniconda3-4.7.12.1-Linux-x86_64.sh" \
         -O /tmp/anaconda.sh \
     && /bin/bash /tmp/anaconda.sh -b -p /opt/conda \
     && rm /tmp/anaconda.sh \
     && /opt/conda/bin/conda install -y \
-        libgcc \
+        libgcc python=3.6.9 \
     && /opt/conda/bin/conda clean -y --all \
     && /opt/conda/bin/pip install \
         flatbuffers \
         cython==0.29.0 \
         numpy==1.15.4
+        
 
 # To avoid the following error on Jenkins:
 # AttributeError: 'numpy.ufunc' object has no attribute '__module__'

docker/examples/Dockerfile

@@ -6,8 +6,6 @@ FROM ray-project/deploy
 RUN conda install -y numpy
 # Needed to run Tune example with a 'plot' call - which does not actually render a plot, but throws an error.
 RUN apt-get install -y zlib1g-dev libgl1-mesa-dev
-# The following is needed to support TensorFlow 1.14
-RUN conda remove -y --force wrapt
 RUN pip install -U pip
 RUN pip install gym[atari] opencv-python-headless tensorflow lz4 pytest-timeout smart_open tensorflow_probability dm_tree
 RUN pip install -U h5py  # Mutes FutureWarnings
@@ -17,3 +15,4 @@ RUN pip install ConfigSpace==0.4.10
 RUN pip install --upgrade sigopt nevergrad scikit-optimize hpbandster lightgbm xgboost torch torchvision tensorboardX dragonfly-opt
 RUN pip install -U tabulate mlflow
 RUN pip install -U pytest-remotedata>=0.3.1
+RUN pip install -U matplotlib jupyter pandas 

docker/tune_test/Dockerfile

@@ -4,24 +4,16 @@ FROM ray-project/base-deps
 
 # We install ray and boto3 to enable the ray autoscaler as
 # a test runner.
-RUN conda install -y numpy
 RUN pip install -U pip
 RUN pip install -U https://ray-wheels.s3-us-west-2.amazonaws.com/latest/ray-0.9.0.dev0-cp36-cp36m-manylinux1_x86_64.whl
-RUN pip install -U boto3
+
 # We install this after the latest wheels -- this should not override the latest wheels.
 # Needed to run Tune example with a 'plot' call - which does not actually render a plot, but throws an error.
-RUN apt-get install -y zlib1g-dev libgl1-mesa-dev
-# The following is needed to support TensorFlow 1.14
-RUN conda remove -y --force wrapt
-RUN pip install gym[atari]==0.10.11 opencv-python-headless tensorflow lz4 keras pytest-timeout smart_open torch torchvision dm_tree
-RUN pip install --upgrade bayesian-optimization
-RUN pip install --upgrade hyperopt==0.1.2
-RUN pip install ConfigSpace==0.4.10
-RUN pip install --upgrade sigopt nevergrad scikit-optimize hpbandster lightgbm xgboost tensorboardX
-RUN pip install -U mlflow
-RUN pip install -U pytest-remotedata>=0.3.1
+RUN pip install torch==1.4.0+cpu torchvision==0.5.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+RUN pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.1.0-cp36-cp36m-manylinux2010_x86_64.whl
 
-# RUN mkdir -p /root/.ssh/
+COPY requirements.txt .
+RUN pip install -r requirements.txt 
 
 # We port the source code in so that we run the most up-to-date stress tests.
 ADD ray.tar /ray

docker/tune_test/requirements.txt

@@ -0,0 +1,29 @@
+ConfigSpace==0.4.10
+bayesian-optimization
+boto3
+dm_tree
+dragonfly-opt
+gym[atari]
+h5py
+hpbandster
+hyperopt==0.1.2
+jupyter
+keras
+lightgbm
+lz4
+matplotlib
+mlflow
+nevergrad
+opencv-python-headless
+pandas
+pytest-remotedata>=0.3.1
+pytest-timeout
+scikit-optimize
+sigopt
+smart_open
+tabulate
+tensorboardX
+tensorflow_probability
+torch
+torchvision
+xgboost