[docker] Mirror Functionality of CI scripts & Fix docs (#10349)

* first-pass

* add back build examples

* remove unnecessary test

* add gcc and more formatting

* doc fixing

* small fixes

docker/development/Dockerfile

@@ -1,9 +1,11 @@
-# The deploy Docker image build a self-contained Ray instance suitable
-# for end users.
+# The development Docker image build a self-contained Ray instance suitable
+# for developers that need the source code to actively modify.
 
-FROM ray-project/base-deps
+FROM rayproject/ray-deps:latest
 ADD ray.tar /ray
 ADD git-rev /ray/git-rev
+# Install dependencies needed to build ray
+RUN apt-get update && apt-get install -y curl unzip cmake gcc && apt-get clean
 RUN cd /ray && git init && ./ci/travis/install-bazel.sh --system
 ENV PATH=$PATH:/root/bin
 RUN echo 'build --remote_cache="https://storage.googleapis.com/ray-bazel-cache"' >> $HOME/.bazelrc 

docker/examples/Dockerfile

@@ -1,17 +1,36 @@
 # The examples Docker image adds dependencies needed to run the examples
 
-FROM ray-project/deploy
+FROM rayproject/ray:latest
 
-# This updates numpy to 1.14 and mutes errors from other libraries
-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 libgtk2.0-dev
-RUN pip install -U pip
-RUN pip install gym[atari] opencv-python-headless==4.3.0.36 tensorflow lz4 pytest-timeout smart_open tensorflow_probability dm_tree
-RUN pip install -U h5py  # Mutes FutureWarnings
-RUN pip install --upgrade bayesian-optimization hyperopt
-RUN pip install ConfigSpace==0.4.10
-RUN pip install --upgrade sigopt nevergrad scikit-optimize hpbandster lightgbm xgboost torch torchvision tensorboardX dragonfly-opt zoopt
-RUN pip install -U tabulate mlflow
-RUN pip install -U pytest-remotedata>=0.3.1
-RUN pip install -U matplotlib jupyter pandas
+RUN apt-get update && install -y zlib1g-dev libgl1-mesa-dev libgtk2.0-dev && apt-get clean
+RUN pip install --no-cache-dir -U pip \
+    gym[atari] \
+    opencv-python-headless==4.3.0.36 \
+    tensorflow \
+    lz4 \
+    pytest-timeout \
+    smart_open \
+    tensorflow_probability \
+    dm_tree \
+    h5py   # Mutes FutureWarnings \
+    bayesian-optimization \
+    hyperopt \
+    ConfigSpace==0.4.10 \
+    sigopt \ 
+    nevergrad \
+    scikit-optimize \
+    hpbandster \
+    lightgbm \
+    xgboost \
+    torch \
+    torchvision \
+    tensorboardX \
+    dragonfly-opt \
+    zoopt \
+    tabulate \ 
+    mlflow \
+    pytest-remotedata>=0.3.1 \
+    matplotlib \
+    jupyter \
+    pandas

docker/stress_test/Dockerfile

@@ -1,13 +0,0 @@
-# The stress_test Docker image build a self-contained Ray instance for launching Ray.
-
-FROM ray-project/base-deps
-
-# We install ray and boto3 to enable the ray autoscaler as
-# a test runner.
-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 boto3
-RUN mkdir -p /root/.ssh/
-
-# We port the source code in so that we run the most up-to-date stress tests.
-ADD ray.tar /ray
-ADD git-rev /ray/git-rev
-WORKDIR /ray