v0.1.0

.gitignore

@@ -1,6 +1,10 @@
 *.DS_Store
 *.swp
 *.pyc
+version.py
 build/
 data/
+docs/src/
 docs/html/
+encoding/_ext/
+encoding.egg-info/

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2017 Hang 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

@@ -1,4 +1,12 @@
-# PyTorch-Encoding-Layer
+# PyTorch-Encoding
+
+## [Documentation](http://hangzh.com/PyTorch-Encoding/)
+
+- Please visit the [**Docs**](http://hangzh.com/PyTorch-Encoding/) for detail instructions of installation and usage. 
+
+- [**Link**](http://hangzh.com/PyTorch-Encoding/experiments/texture.html) to the Deep TEN texture classification experiments and pre-trained models.
+
+## Citation
 
 **Deep TEN: Texture Encoding Network** [[arXiv]](https://arxiv.org/pdf/1612.02844.pdf)  
   [Hang Zhang](http://hangzh.com/), [Jia Xue](http://jiaxueweb.com/), [Kristin Dana](http://eceweb1.rutgers.edu/vision/dana.html)
@@ -11,9 +19,3 @@ month = {July},
 year = {2017}
 }
 ```
-
-## [Documentation](http://hangzh.com/PyTorch-Encoding/)
-
-- Please visit the [**Docs**](http://hangzh.com/PyTorch-Encoding/) for detail instructions of installation and usage. 
-
-- [**Link**](http://hangzh.com/PyTorch-Encoding/experiments/texture.html) to the experiments and pre-trained models.

build.py

@@ -15,9 +15,13 @@
 from torch.utils.ffi import create_extension
 
 lib_path = os.path.join(os.path.dirname(torch.__file__), 'lib')
-this_file = os.path.dirname(os.path.realpath(__file__))
+cwd = os.path.dirname(os.path.realpath(__file__))
 
-# build kernel library
+# clean the build files
+clean_cmd = ['bash', 'clean.sh']
+subprocess.check_call(clean_cmd)
+
+# build CUDA library
 os.environ['TORCH_BUILD_DIR'] = lib_path
 if platform.system() == 'Darwin':
     os.environ['TH_LIBRARIES'] = os.path.join(lib_path,'libTH.1.dylib')
@@ -28,21 +32,21 @@
     os.environ['THC_LIBRARIES'] = os.path.join(lib_path,'libTHC.so.1')
     ENCODING_LIB = os.path.join(lib_path, 'libENCODING.so')
 
-clean_cmd = ['bash', 'clean.sh']
-subprocess.check_call(clean_cmd)
-
 build_all_cmd = ['bash', 'encoding/make.sh']
 subprocess.check_call(build_all_cmd, env=dict(os.environ))
 
+# build FFI
 sources = ['encoding/src/encoding_lib.cpp']
-headers = ['encoding/src/encoding_lib.h']
+headers = [
+    'encoding/src/encoding_lib.h',
+]
 defines = [('WITH_CUDA', None)]
 with_cuda = True 
 
 include_path = [os.path.join(lib_path, 'include'),
-                os.path.join(os.environ['HOME'],'pytorch/torch/lib/THC'), 
                 os.path.join(lib_path,'include/ENCODING'), 
-                os.path.join(this_file,'encoding/src/')]
+                os.path.join(cwd,'encoding/kernel/include'), 
+                os.path.join(cwd,'encoding/src/')]
 
 def make_relative_rpath(path):
     if platform.system() == 'Darwin':
@@ -58,11 +62,11 @@ def make_relative_rpath(path):
     define_macros=defines,
     relative_to=__file__,
     with_cuda=with_cuda,
-        include_dirs = include_path,
-        extra_link_args = [
-            make_relative_rpath(lib_path),
-            ENCODING_LIB,
-        ],
+    include_dirs = include_path,
+    extra_link_args = [
+        make_relative_rpath(lib_path),
+        ENCODING_LIB,
+    ],
 )
 
 if __name__ == '__main__':

docs/source/dilated.rst

@@ -6,7 +6,7 @@ Dilated Networks
 
 We provide correct dilated pre-trained ResNet and DenseNet for semantic segmentation. 
 For dilation of ResNet, we replace the stride of 2 Conv3x3 at begining of certain stage and update the dilation of the conv layers afterwards. 
-For dilation of DenseNet, we provide DilatedAvgPool2d that handles the dilation of the transition layers, then update the dilation of the conv layers afterwards. 
+For dilation of DenseNet, we provide :class:`encoding.nn.DilatedAvgPool2d` that handles the dilation of the transition layers, then update the dilation of the conv layers afterwards. 
 All provided models have been verified. 
 
 

docs/source/encoding.rst

@@ -4,6 +4,7 @@
 My NN Layers
 ============
 
+
 Modules
 -------
 
@@ -21,22 +22,16 @@ Modules
 .. autoclass:: Inspiration
     :members:
 
-:hidden:`DilatedAvgPool2d`
+:hidden:`UpsampleConv2d`
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autoclass:: DilatedAvgPool2d
-    :members:
-
-:hidden:`GramMatrix`
-~~~~~~~~~~~~~~~~~~~~
-
-.. autoclass:: GramMatrix
+.. autoclass:: UpsampleConv2d
     :members:
 
-:hidden:`Aggregate`
-~~~~~~~~~~~~~~~~~~~
+:hidden:`DilatedAvgPool2d`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-.. autoclass:: Aggregate
+.. autoclass:: DilatedAvgPool2d
     :members:
 
 Functions
@@ -54,13 +49,3 @@ Functions
 
 .. autofunction:: scaledL2
 
-:hidden:`residual`
-~~~~~~~~~~~~~~~~~~~
-
-.. autofunction:: residual
-
-
-:hidden:`assign`
-~~~~~~~~~~~~~~~~~~~
-
-.. autofunction:: assign

docs/source/experiments/style.rst

@@ -1,7 +1,7 @@
 MSG-Net Style Transfer Example
 ==============================
 
-.. image:: https://raw.githubusercontent.com/zhanghang1989/MSG-Net/master/images/figure1.jpg
+.. image:: ../_static/img/figure1.jpg
     :width: 55%
     :align: left
 
@@ -47,7 +47,7 @@ Stylize Images Using Pre-trained Model
 
     python camera_demo.py demo --model models/9styles.model
 
-.. image:: https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/myimage.gif
+.. image:: ../_static/img/myimage.gif
 
 - Test the model::
 
@@ -66,14 +66,14 @@ Stylize Images Using Pre-trained Model
 
 .. raw:: html
 
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/1.jpg" width="260px" /> <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/2.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/3.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/4.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/5.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/6.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/7.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/8.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/9.jpg" width="260px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/1.jpg" width="220px" /> <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/2.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/3.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/4.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/5.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/6.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/7.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/8.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/9.jpg" width="220px" />
 
 Train Your Own MSG-Net Model
 ----------------------------
@@ -96,7 +96,7 @@ Train Your Own MSG-Net Model
 
 
 Neural Style
--------------
+------------
 `Image Style Transfer Using Convolutional Neural Networks <http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Gatys_Image_Style_Transfer_CVPR_2016_paper.pdf>`_ by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge::
 
     python main.py optim --content-image images/content/venice-boat.jpg --style-image images/9styles/candy.jpg
@@ -110,12 +110,12 @@ Neural Style
 
 .. raw:: html
 
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g1.jpg" width="260px" /> <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g2.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g3.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g4.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g5.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g6.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g7.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g8.jpg" width="260px" />
-    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g9.jpg" width="260px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g1.jpg" width="220px" /> <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g2.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g3.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g4.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g5.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g6.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g7.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g8.jpg" width="220px" />
+    <img src ="https://raw.githubusercontent.com/zhanghang1989/PyTorch-Style-Transfer/master/images/g9.jpg" width="220px" />
 

docs/source/experiments/texture.rst

@@ -1,7 +1,7 @@
 Deep TEN: Deep Texture Encoding Network Example
 ===============================================
 
-.. image:: http://hangzh.com/figure/cvpr17.svg
+.. image:: ../_static/img/cvpr17.svg
         :width: 100%
         :align: left
 
@@ -39,7 +39,7 @@ Test Pre-trained Model
 Train Your Own Model
 --------------------
 
-- Example training command::
+- Example training command for training above model::
 
     python main.py --dataset minc --model encodingnet --batch-size 64 --lr 0.01 --epochs 60 
 

docs/source/functions.rst

@@ -14,3 +14,44 @@ Other Functions
 
 .. autofunction:: dilatedavgpool2d
 
+:hidden:`upsample`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: upsample
+
+
+:hidden:`dropout`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: dropout
+
+
+:hidden:`relu`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: relu
+
+
+:hidden:`view_each`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: view_each
+
+
+:hidden:`multi_each`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: multi_each
+
+
+:hidden:`sum_each`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: sum_each
+
+
+:hidden:`cat_each`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: cat_each
+

docs/source/index.rst

@@ -7,7 +7,10 @@ Encoding Documentation
 
 Created by `Hang Zhang <http://hangzh.com/>`_
 
-PyTorch-Encoding is an optimized PyTorch package with CUDA backend, including Encoding Layer, Multi-GPU Synchronized Batch Normalization and useful util functions. Example systems are also provided in `experiments section <experiments/texture.html>`_. We hope this software will accelerate your research, please cite our `papers <notes/compile.html>`_. 
+- An optimized PyTorch package with CUDA backend, including Encoding Layer :class:`encoding.nn.Encoding`, Multi-GPU Synchronized Batch Normalization :class:`encoding.nn.BatchNorm2d` and other customized modules and functions. 
+
+- **Example Systems** for Semantic Segmentation (coming), CIFAR-10 Classification, `Texture Recognition <experiments/texture.html>`_ and `Style Transfer <experiments/style.html>`_ are provided in experiments section. 
+
 
 .. toctree::
    :glob:

docs/source/nn.rst

@@ -9,6 +9,12 @@ Other NN Layers
 Customized Layers
 -----------------
 
+:hidden:`GramMatrix`
+~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: GramMatrix
+    :members:
+
 :hidden:`Normalize`
 ~~~~~~~~~~~~~~~~~~~
 

docs/source/notes/compile.rst

@@ -1,26 +1,30 @@
-Install PyTorch-Encoding
-========================
+Installing PyTorch-Encoding
+===========================
 
-- Install PyTorch from Source to the ``$HOME`` directory:
-    * Please follow the `PyTorch instructions <https://github.com/pytorch/pytorch#from-source>`_ (recommended).
-    * Or you can simply clone a copy to ``$HOME`` directory::
+
+Install from Source
+-------------------
+
+    * Please follow the `PyTorch instructions <https://github.com/pytorch/pytorch#from-source>`_ to install PyTorch from Source to the ``$HOME`` directory (recommended). Or you can simply clone a copy to ``$HOME`` directory::
 
         git clone https://github.com/pytorch/pytorch $HOME/pytorch
 
-- Install this package:
-    * Clone the repo::
+    * Install this package
+
+        - Clone the repo::
 
-        git clone https://github.com/zhanghang1989/PyTorch-Encoding && cd PyTorch-Encoding-Layer
+            git clone https://github.com/zhanghang1989/PyTorch-Encoding && cd PyTorch-Encoding
 
-    * On Linux::
+        - On Linux::
 
-        python setup.py install
+            python setup.py install
 
-    * On Mac OSX::
+        - On Mac OSX::
 
-         MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py install
+             MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py install
 
-- Reference:
+Reference
+---------
 
     .. note::
         If using the code in your research, please cite our paper.