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        "description": "[![GitHub license](https://img.shields.io/github/license/0h-n0/torchex.svg)](https://github.com/0h-n0/torchex)\n[![PYTHON version](https://img.shields.io/badge/python-3.5,3.6-blue.svg)](https://github.com/0h-n0/torchex)\n[![PyPI version](https://img.shields.io/pypi/v/torchex.svg)](https://badge.fury.io/py/torchex)\n[![CircleCI](https://circleci.com/gh/0h-n0/torchex.svg?style=svg&circle-token=99e93ba7bf6433d0cd33adbec2fbd042d141353d)](https://circleci.com/gh/0h-n0/torchex)\n[![Build Status](https://travis-ci.org/0h-n0/torchex.svg?branch=master)](https://travis-ci.org/0h-n0/torchex)\n[![codecov](https://codecov.io/gh/0h-n0/torchex/branch/master/graph/badge.svg)](https://codecov.io/gh/0h-n0/torchex)\n[![Documentation Status](https://readthedocs.org/projects/torchex/badge/?version=latest)](https://torchex.readthedocs.io/en/latest/?badge=latest)\n[![Maintainability](https://api.codeclimate.com/v1/badges/7cd6c99f10d22db13ee8/maintainability)](https://codeclimate.com/github/0h-n0/torchex/maintainability)\n[![Test Coverage](https://api.codeclimate.com/v1/badges/7cd6c99f10d22db13ee8/test_coverage)](https://codeclimate.com/github/0h-n0/torchex/test_coverage)\n[![BCH compliance](https://bettercodehub.com/edge/badge/0h-n0/torchex?branch=master)](https://bettercodehub.com/)\n[![Downloads](https://img.shields.io/pypi/dm/torchex.svg)](https://pypi.org/project/torchex/)\n\n# (WIP) `torchex library\n\n`torchex` library provides advanced Neural Network Layers. You can easily use them like using original pytorch.\n\n## Installation\n\n```\n$ pip install torchex\n```\n\n## Requirements\n\n* Pytorch >= 1.0\n\n## Documentation\n\n* https://torchex.readthedocs.io/en/latest/index.html\n\n## How to use\n\n### Lazy Style Model Definition\n\n```python\nimport torch\nimport torchex.nn as exnn\n\nnet = exnn.Linear(10)\n# You don't need to give the size of input for this module.\n# This network is equivalent to `nn.Linear(100, 10)`.\n\nx = troch.randn(10, 100)\n\ny = net(x)\n```\n\n### torchex.nn list\n\n* `torchex.nn.Pass`\n* `torchex.nn.Flatten`\n* `torchex.nn.Linear`\n  * Lazy style\n* `torchex.nn.Conv1d`\n  * Lazy style\n* `torchex.nn.Conv2d`\n  * Lazy style\n* `torchex.nn.Conv3d`\n  * Lazy style\n* `torchex.nn.Conv2dLocal`\n\n\n\n",
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