updated docker folder (#2316)

* updated docker folder

* added depth=1 option to all git commands

docker/README.md

-# Using LightGBM via Docker
+# Using LightGBM via Docker
 
-This directory contains `Dockerfile` to make it easy to build and run LightGBM via [Docker](http://www.docker.com/).
+This directory contains `Dockerfile`s to make it easy to build and run LightGBM via [Docker](https://www.docker.com/).
 
 ## Installing Docker
 
-Follow the general installation instructions
-[on the Docker site](https://docs.docker.com/installation/):
+Follow the general installation instructions [on the Docker site](https://docs.docker.com/install/):
 
-* [macOS](https://docs.docker.com/installation/mac/): [docker toolbox](https://www.docker.com/toolbox)
-* [Ubuntu](https://docs.docker.com/installation/ubuntulinux/)
+* [macOS](https://docs.docker.com/docker-for-mac/install/)
+* [Ubuntu](https://docs.docker.com/install/linux/docker-ce/ubuntu/)
+* [Windows](https://docs.docker.com/docker-for-windows/install/)
 
 ## Using CLI Version of LightGBM via Docker
 
@@ -34,7 +34,7 @@ lightgbm-cli \
 config=lgbm.conf
 ```
 
-In the above example, three volumes are [mounted](https://docs.docker.com/engine/reference/commandline/run/#mount-volume--v-read-only)
+In the above example, three volumes are [mounted](https://docs.docker.com/engine/reference/commandline/run/#mount-volume--v---read-only)
 from the host machine to the Docker container:
 
 * `lgbm.conf` - task config, for example
@@ -51,8 +51,7 @@ convert_model_language=cpp
 * `model.txt` - an input file for the task, could be training data or, in this case, a pre-trained model.
 * `out` - a directory to store the output of the task, notice that `convert_model` in the task config is using it.
 
-`config=lgbm.conf` is a command-line argument passed to the `lightgbm` executable, more arguments can
-be passed if required.
+`config=lgbm.conf` is a command-line argument passed to the `lightgbm` executable, more arguments can be passed if required.
 
 ## Running the Python-package Сontainer
 

docker/dockerfile-cli

 FROM ubuntu:16.04
 
 RUN apt-get update && \
-    apt-get install -y cmake build-essential gcc g++ git && \
+    apt-get install -y --no-install-recommends \
+        cmake \
+        build-essential \
+        gcc \
+        g++ \
+        git && \
     rm -rf /var/lib/apt/lists/*
 
-RUN git clone --recursive --branch stable https://github.com/Microsoft/LightGBM && \
+RUN git clone --recursive --branch stable --depth 1 https://github.com/Microsoft/LightGBM && \
     mkdir LightGBM/build && \
     cd LightGBM/build && \
     cmake .. && \
     make -j4 && \
     make install && \
     cd ../.. && \
-    rm -rf LightGBM 
+    rm -rf LightGBM
 
 ENTRYPOINT ["lightgbm"]

docker/dockerfile-python

 FROM ubuntu:16.04
 
 RUN apt-get update && \
-    apt-get install -y cmake build-essential gcc g++ git wget && \
+    apt-get install -y --no-install-recommends \
+        cmake \
+        build-essential \
+        gcc \
+        g++ \
+        git \
+        wget && \
 
 # python-package
     # miniconda
     wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
     /bin/bash Miniconda3-latest-Linux-x86_64.sh -f -b -p /opt/conda && \
     export PATH="/opt/conda/bin:$PATH" && \
+    conda config --set always_yes yes --set changeps1 no && \
     # lightgbm
-    conda install -y numpy scipy scikit-learn pandas && \
-    git clone --recursive https://github.com/Microsoft/LightGBM && \
+    conda install -q -y numpy scipy scikit-learn pandas && \
+    git clone --recursive --branch stable --depth 1 https://github.com/Microsoft/LightGBM && \
     cd LightGBM/python-package && python setup.py install && \
 
 # clean
     apt-get autoremove -y && apt-get clean && \
-    conda clean -i -l -t -y && \
+    conda clean -a -y && \
     rm -rf /usr/local/src/*
 
 ENV PATH /opt/conda/bin:$PATH

docker/dockerfile-r

@@ -5,6 +5,6 @@ WORKDIR /lgbm
 # R
 RUN apt-get update && \
     apt-get install -y build-essential && \
-    git clone --recursive --branch stable https://github.com/Microsoft/LightGBM && \
+    git clone --recursive --branch stable --depth 1 https://github.com/Microsoft/LightGBM && \
     cd LightGBM && \
     Rscript build_r.R

docker/gpu/README.md

 # Dockerfile for LightGBM GPU Version with Python
 
-A docker file with LightGBM utilizing nvidia-docker. The file is based on the nvidia/cuda:8.0 image. LightGBM can be utilized in GPU and CPU modes and via Python (2.7 & 3.5)
+A docker file with LightGBM utilizing nvidia-docker. The file is based on the `nvidia/cuda:8.0-cudnn5-devel` image.
+LightGBM can be utilized in GPU and CPU modes and via Python (2.7 & 3.6).
 
 ## Contents
 
 - LightGBM (cpu + gpu)
-- Python 2.7 (Conda) + scikit-learn notebooks pandas matplotlib
-- Python 3.5 (Conda) + scikit-learn notebooks pandas matplotlib
+- Python 2.7 (conda) + scikit-learn, notebooks, pandas, matplotlib
+- Python 3.6 (conda) + scikit-learn, notebooks, pandas, matplotlib
 
-Running the container starts a jupyter notebook at localhost:8888
+Running the container starts a Jupyter Notebook at `localhost:8888`.
 
-jupyter password: keras
+Jupyter password: `keras`.
 
 ## Requirements
 

docker/gpu/dockerfile.gpu

@@ -31,11 +31,11 @@ RUN chmod +x /tini
 #################################################################################################################
 #           SYSTEM
 #################################################################################################################
-# update: downloads the package lists from the repositories and "updates" them to get information on the newest versions of packages and their 
-# dependencies. It will do this for all repositories and PPAs. 
+# update: downloads the package lists from the repositories and "updates" them to get information on the newest versions of packages and their
+# dependencies. It will do this for all repositories and PPAs.
 
 RUN apt-get update && \
-apt-get install -y \
+apt-get install -y --no-install-recommends \
 build-essential \
 curl \
 wget \
@@ -70,44 +70,45 @@ ENV PATH $CONDA_DIR/bin:$PATH
 
 # Install miniconda
 RUN echo 'export PATH=/opt/conda/bin:$PATH' > /etc/profile.d/conda.sh && \
-    wget --quiet https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O ~/miniconda.sh && \
+    wget --quiet https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh && \
     /bin/bash ~/miniconda.sh -b -p /opt/conda && \
     rm ~/miniconda.sh
 
-RUN conda create -q -n py2 python=2.7 mkl numpy scipy scikit-learn jupyter notebook ipython pandas matplotlib
-RUN conda create -q -n py3 python=3.5 mkl numpy scipy scikit-learn jupyter notebook ipython pandas matplotlib
+RUN conda config --set always_yes yes --set changeps1 no && \
+    conda create -y -q -n py2 python=2.7 mkl numpy scipy scikit-learn jupyter notebook ipython pandas matplotlib && \
+    conda create -y -q -n py3 python=3.6 mkl numpy scipy scikit-learn jupyter notebook ipython pandas matplotlib
 
 #################################################################################################################
 #           LightGBM
 #################################################################################################################
 
 RUN cd /usr/local/src && mkdir lightgbm && cd lightgbm && \
-    git clone --recursive https://github.com/microsoft/LightGBM && \
+    git clone --recursive --branch stable --depth 1 https://github.com/microsoft/LightGBM && \
     cd LightGBM && mkdir build && cd build && \
-    cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ .. && \ 
+    cmake -DUSE_GPU=1 -DOpenCL_LIBRARY=/usr/local/cuda/lib64/libOpenCL.so -DOpenCL_INCLUDE_DIR=/usr/local/cuda/include/ .. && \
     make OPENCL_HEADERS=/usr/local/cuda-8.0/targets/x86_64-linux/include LIBOPENCL=/usr/local/cuda-8.0/targets/x86_64-linux/lib
 
 ENV PATH /usr/local/src/lightgbm/LightGBM:${PATH}
 
 RUN /bin/bash -c "source activate py2 && cd /usr/local/src/lightgbm/LightGBM/python-package && python setup.py install --precompile && source deactivate"
 RUN /bin/bash -c "source activate py3 && cd /usr/local/src/lightgbm/LightGBM/python-package && python setup.py install --precompile && source deactivate"
-    
+
 #################################################################################################################
 #           System CleanUp
 #################################################################################################################
 # apt-get autoremove: used to remove packages that were automatically installed to satisfy dependencies for some package and that are no more needed.
-# apt-get clean: removes the aptitude cache in /var/cache/apt/archives. You'd be amazed how much is in there! the only drawback is that the packages 
+# apt-get clean: removes the aptitude cache in /var/cache/apt/archives. You'd be amazed how much is in there! the only drawback is that the packages
 # have to be downloaded again if you reinstall them.
 
 RUN apt-get autoremove -y && apt-get clean && \
     rm -rf /var/lib/apt/lists/* && \
-    conda clean -i -l -t -y
+    conda clean -a -y
 
 #################################################################################################################
-#           JUPYTER 
+#           JUPYTER
 #################################################################################################################
 
-# password: keras 
+# password: keras
 # password key: --NotebookApp.password='sha1:98b767162d34:8da1bc3c75a0f29145769edc977375a373407824'
 
 # Add a notebook profile.