Update README.md, setup.py etc. (#537)

* 1. Add .gitattributes file to force shell files to have LF line ending.
2. Add setup.cfg to build a universal wheel package.
3. Remove version information from mmdnn/__init__.py .
4. Update author and email information in setup.py .
5. Update README.md .

* Add a new line.

* Set caffe library path correctly in .

.gitattributes

@@ -0,0 +1 @@
+*.sh text eol=lf

.travis.yml

@@ -52,7 +52,7 @@ install:
   - pip install wget
 
 before_script:
-  - export LD_LIBRARY_PATH=/home/travis/virtualenv/python3.5.6/lib/python3.5/site-packages/caffe/libs:/home/travis/virtualenv/python2.7.14/lib/python2.7/site-packages/caffe/libs:${LD_LIBRARY_PATH}
+  - export LD_LIBRARY_PATH=$(python -c "import os; print(os.path.dirname(os.__file__) + '/site-packages/caffe/libs')"):${LD_LIBRARY_PATH}
 
 after_failure: true
 

README.md

@@ -32,12 +32,14 @@ Major features
 
 
 ## Related Projects
-Targeting at openness and advancing state-of-art technology, [Microsoft Research (MSR)](https://www.microsoft.com/en-us/research/group/systems-research-group-asia/) had also released few other open source projects.
+[Microsoft Research Asia (MSRA)](https://www.microsoft.com/en-us/research/group/systems-research-group-asia/)
+and Microsoft Search Technology Center Asia (STCA)
+have released some projects to advance the state-of-art technology:
+* [Open Platform for AI (OpenPAI)](https://github.com/Microsoft/pai): an open source platform that provides complete AI model training and resource management capabilities.
+It is easy to extend and supports on-premise, cloud and hybrid environments in various scale.
+* [Neural Network Intelligence (NNI)](https://github.com/Microsoft/nni): an open source AutoML toolkit for neural architecture search and hyper-parameter tuning.
 
-* [OpenPAI](https://github.com/Microsoft/pai): an open source platform that provides complete AI model training and resource management capabilities, it is easy to extend and supports on-premise, cloud and hybrid environments in various scale.
-* [NNI](https://github.com/Microsoft/nni): An open source AutoML toolkit for neural architecture search and hyper-parameter tuning.
-
-We encourage researchers and students to leverage these projects to accelerate the AI development and research.
+We encourage researchers, developers and students to leverage such projects to boost their Deep Learning / AI productivity.
 
 ## Installation
 
@@ -57,7 +59,8 @@ pip install -U git+https://github.com/Microsoft/MMdnn.git@master
 
 ### Install with docker image
 
-MMdnn provides a docker image, which packages MMdnn, deep learning frameworks we support and other dependencies in one image. You can easily get the image in several steps:
+MMdnn provides a docker image, which packages MMdnn and Deep Learning frameworks that we support as well as other dependencies.
+You can easily try the image with the following steps:
 
 1. Install Docker Community Edition(CE)
 

mmdnn/__init__.py

@@ -1 +0,0 @@
-__version__ = "0.2.2"

setup.cfg

@@ -0,0 +1,6 @@
+[metadata]
+license_files = LICENSE
+
+[bdist_wheel]
+# https://packaging.python.org/guides/distributing-packages-using-setuptools/#wheels
+universal=1

setup.py

@@ -22,8 +22,8 @@
     url='https://github.com/Microsoft/MMdnn',
 
     # Author details
-    author = 'Cheng CHEN, System Research Group, Microsoft Research Asia',
-    author_email='cncng@microsoft.com',
+    author = 'System Research Group, Microsoft Research Asia',
+    author_email='mmdnn_feedback@microsoft.com',
 
     # Choose your license
     license='MIT',