Change dockerfile to support for cudnn v6 (pytorch#1135)

Dockerfile

@@ -1,13 +1,18 @@
-FROM nvidia/cuda:8.0-cudnn5-devel-ubuntu14.04 
+FROM nvidia/cuda:8.0-devel-ubuntu16.04 
 
+RUN echo "deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list
+
+ENV CUDNN_VERSION 6.0.20 
 RUN apt-get update && apt-get install -y --no-install-recommends \
          build-essential \
          cmake \
          git \
          curl \
          ca-certificates \
          libjpeg-dev \
-         libpng-dev &&\
+         libpng-dev \
+         libcudnn6=$CUDNN_VERSION-1+cuda8.0 \             
+         libcudnn6-dev=$CUDNN_VERSION-1+cuda8.0 && \
      rm -rf /var/lib/apt/lists/*
 
 RUN curl -o ~/miniconda.sh -O  https://repo.continuum.io/miniconda/Miniconda3-4.2.12-Linux-x86_64.sh  && \

README.md

@@ -190,15 +190,11 @@ python setup.py install
 
 ### Docker image
 
-Dockerfiles are supplied to build images with cuda support and cudnn v5 and cudnn v6 RC. Build them as usual
+Dockerfile is supplied to build images with cuda support and cudnn v6. Build as usual
 ```
-docker build -t pytorch-cudnnv5 .
+docker build -t pytorch-cudnnv6 .
 ```
-or 
-```
-docker build -t pytorch-cudnnv6 -f tools/docker/Dockerfile-v6 .
-```
-and run them with nvidia-docker:
+and run  with nvidia-docker:
 ```
 nvidia-docker run --rm -ti --ipc=host pytorch-cudnnv5
 ```