clean examples.

Author: Tiiiger

.gitignore

@@ -15,3 +15,5 @@ build
 *.egg-info
 dist
 **/.ipynb_checkpoints
+**/data
+docs/source/examples

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2019 Tianyi Zhang
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -32,11 +32,11 @@ pip install qtorch
 See our [read the docs](www.google.com)
 
 ## Tutorials
-- [An overview of QPyTorch's features](https://github.com/Tiiiger/QPyTorch/blob/master/examples/Functionality_Overview.ipynb)
-- [CIFAR-10 Low-Precision Training Tutorial](https://github.com/Tiiiger/QPyTorch/blob/master/examples/CIFAR10_Low_Precision_Training_Example.ipynb)
+- [An overview of QPyTorch's features](https://github.com/Tiiiger/QPyTorch/blob/master/examples/tutorial/Functionality_Overview.ipynb)
+- [CIFAR-10 Low-Precision Training Tutorial](https://github.com/Tiiiger/QPyTorch/blob/master/examples/tutorial/CIFAR10_Low_Precision_Training_Example.ipynb)
 
 ## Examples
-- Low-Precision VGGs and ResNets using fixed point, block floating point. [Examples](https://github.com/Tiiiger/QPyTorch/blob/master/examples)
+- Low-Precision VGGs and ResNets using fixed point, block floating point on CIFAR and ImageNet. [lp_train](https://github.com/Tiiiger/QPyTorch/blob/master/examples/lp_train)
 - Reproduction of WAGE in QPyTorch. [WAGE.qpytorch](https://github.com/Tiiiger/QPyTorch/blob/master/examples)
 - Reproduction of 8-bit Floating Point Training in QPyTorch. [IBM8.qpytorch](https://github.com/Tiiiger/QPyTorch/blob/master/examples)
 

docs/source/conf.py

@@ -69,8 +69,8 @@
 
 # General information about the project.
 project = 'QPyTorch'
-copyright = '2019, Tianyi Zhang, Zhiqiu Lin, Christopher De Sa'
-author = 'Tianyi Zhang, Zhiqiu Lin, Christopher De Sa'
+copyright = '2019, Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa'
+author = 'Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa'
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the
@@ -179,6 +179,3 @@
      author, 'QPyTorch', 'One line description of project.',
      'Miscellaneous'),
 ]
-
-
-

docs/source/examples/CIFAR10_Low_Precision_Training_Example.ipynb

@@ -12,9 +12,8 @@ QPyTorch's documentation
    :maxdepth: 1
    :caption: Guides and Tutorials:
 
-   examples/Low_Precision_Quick_Intro
-   examples/Functionality_Overview
-   examples/CIFAR10_Low_Precision_Training_Example
+   examples/tutorial/Functionality_Overview
+   examples/tutorial/CIFAR10_Low_Precision_Training_Example
 
 .. toctree::
    :maxdepth: 1