initial commit

Author: litcoderr

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.idea
+.idea/

LICENSE.txt

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+MIT License
+Copyright (c) 2018 YOUR NAME
+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

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 # ComplexCNN
 pytorch implementation of complex convolutional neural network
+Reference: [https://arxiv.org/pdf/1705.09792.pdf](https://arxiv.org/pdf/1705.09792.pdf)
+
+## Usage

__init__.py

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+# -*- coding: utf-8 -*-
+

modules.py

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+# -*- coding: utf-8 -*-
+import torch
+import torch.nn as nn
+import numpy as np
+
+class ComplexConv(nn.Module):
+    def __init__(self, in_channel, out_channel, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True):
+        super(ComplexConv,self).__init__()
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        self.padding = padding
+
+        ## Model components
+        self.conv_re = nn.Conv2d(in_channel, out_channel, kernel_size, stride=stride, padding=padding, dilation=dilation, groups=groups, bias=bias)
+        self.conv_im = nn.Conv2d(in_channel, out_channel, kernel_size, stride=stride, padding=padding, dilation=dilation, groups=groups, bias=bias)
+        
+    def forward(self, x): # shpae of x : [batch,2,channel,axis1,axis2]
+        real = self.conv_re(x[:,0]) - self.conv_im(x[:,1])
+        imaginary = self.conv_re(x[:,1]) + self.conv_im(x[:,0])
+        output = torch.stack((real,imaginary),dim=1)
+        return output
+        
+#%%
+if __name__ == "__main__":
+    ## Random Tensor for Input
+    ## shape : [batchsize,2,channel,axis1_size,axis2_size]
+    ## Below dimensions are totally random
+    x = torch.randn((10,2,3,100,100))
+    
+    # 1. Make ComplexConv Object
+    ## (in_channel, out_channel, kernel_size) parameter is required
+    complexConv = ComplexConv(3,10,(5,5))
+    
+    # 2. compute
+    y = complexConv(x)
+

setup.cfg

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+# Inside of setup.cfg
+[metadata]
+description-file = README.md

setup.py

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+# -*- coding: utf-8 -*-
+
+from distutils.core import setup
+setup(
+  name = 'complexcnn',         # How you named your package folder (MyLib)
+  packages = ['complexcnn'],   # Chose the same as "name"
+  version = '0.1',      # Start with a small number and increase it with every change you make
+  license='MIT',        # Chose a license from here: https://help.github.com/articles/licensing-a-repository
+  description = 'pytorch implementation of complex convolutional neural network',   # Give a short description about your library
+  author = 'James Yougchae Chee',                   # Type in your name
+  author_email = '[email protected]',      # Type in your E-Mail
+  url = 'https://github.com/litcoderr/ComplexCNN',   # Provide either the link to your github or to your website
+  download_url = 'https://github.com/litcoderr/ComplexCNN/archive/v_0.1.tar.gz',    # I explain this later on
+  keywords = ['deeplearning', 'pytorch', 'machinelearning'],   # Keywords that define your package best
+  install_requires=[            # I get to this in a second
+          'pytorch',
+          'numpy',
+      ],
+  classifiers=[
+    'Development Status :: 3 - Alpha',      # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package
+    'Intended Audience :: Developers',      # Define that your audience are developers
+    'Topic :: Software Development :: Build Tools',
+    'License :: OSI Approved :: MIT License',   # Again, pick a license
+    'Programming Language :: Python :: 3',      #Specify which pyhton versions that you want to support
+    'Programming Language :: Python :: 3.4',
+    'Programming Language :: Python :: 3.5',
+    'Programming Language :: Python :: 3.6',
+  ],
+)