TFGENZOO


NameTFGENZOO JSON
Version 1.2.4.post8 PyPI version JSON
download
home_pagehttps://github.com/MokkeMeguru/TFGENZOO
Summaryhelper of building generative model with Tensorflow 2.x
upload_time2020-07-11 10:43:15
maintainer
docs_urlNone
authorMokkeMeguru
requires_python
licenseMIT
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # TFGENZOO (Generative Model x Tensorflow 2.x)

![img](https://github.com/MokkeMeguru/TFGENZOO/workflows/tensorflow%20test/badge.svg?branch=master)
![img](https://img.shields.io/badge/License-MIT-yellow.svg)
![img](https://img.shields.io/badge/python-3.7-blue.svg)
![img](https://img.shields.io/badge/tensorflow-%3E%3D2.2.0-brightgreen.svg)
![img](https://badge.fury.io/py/TFGENZOO.svg)

# What’s this repository?

This is a repository for some researcher to build some Generative models using Tensorflow 2.x.

I NEED YOUR HELP(please let me know about formula, implementation and anything you worried)

![img](https://raw.githubusercontent.com/MokkeMeguru/TFGENZOO/master/docs/tfgenzoo_header.png)

# Zen of this repository

    We don't want to need flexible architectures.
    We need strict definitions for shapes, parameters, and formulas.
    We should Implement correct codes with well-documented(tested).

# How to use?

## By Install

- pipenv

      pipenv install TFGENZOO==1.2.4.post7

- pip

      pip install TFGENZOO==1.2.4.post7

## Source build for development

1.  clone this repository (If you want to do it, I will push this repository to PYPI)
2.  build this repository `docker-compose build`
3.  run the environment `sh run_script.sh`
4.  connect it via VSCode or Emacs or vi or anything.

# Examples

- [TFGENZOO_EXAMPLE](https://github.com/MokkeMeguru/TFGENZOO_EXAMPLE)

# Roadmap

- [x] Flow-based Model Architecture (RealNVP, Glow)
- [ ] i-ResNet Model Architecture (i-ResNet, i-RevNet)
- [ ] GANs Model Architecture (GANs)

# Remarkable Backlog

Whole backlog is [here](https://github.com/MokkeMeguru/TFGENZOO/wiki/Backlog)

## News [2020/6/16]

New training results [Oxford-flower102](https://www.tensorflow.org/datasets/catalog/oxford_flowers102) with only 8 hours! (Quadro P6000 x 1)

<table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides">

<colgroup>
<col  class="org-left" />

<col  class="org-right" />

<col  class="org-right" />

<col  class="org-left" />
</colgroup>
<thead>
<tr>
<th scope="col" class="org-left">data</th>
<th scope="col" class="org-right">NLL(test)</th>
<th scope="col" class="org-right">epoch</th>
<th scope="col" class="org-left">pretrained</th>
</tr>
</thead>

<tbody>
<tr>
<td class="org-left">Oxford-flower102</td>
<td class="org-right">4.590211391448975</td>
<td class="org-right">1024</td>
<td class="org-left">---</td>
</tr>
</tbody>
</table>

![img](https://raw.githubusercontent.com/MokkeMeguru/TFGENZOO/master/docs/oxford.png)

see more detail, you can see [my internship&rsquo;s report](https://docs.google.com/presentation/d/12z6MZizIsytLxUb2ly7vYorFiKruIGZ2ckQ0-By4b6s/edit?usp=sharing) (Japanese only, if you need translated version, please contact me.)

# Contact

MokkeMeguru ([@MokkeMeguru](https://twitter.com/MeguruMokke)): DM or Mention Please (in Any language).



            

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    "description": "# TFGENZOO (Generative Model x Tensorflow 2.x)\n\n![img](https://github.com/MokkeMeguru/TFGENZOO/workflows/tensorflow%20test/badge.svg?branch=master)\n![img](https://img.shields.io/badge/License-MIT-yellow.svg)\n![img](https://img.shields.io/badge/python-3.7-blue.svg)\n![img](https://img.shields.io/badge/tensorflow-%3E%3D2.2.0-brightgreen.svg)\n![img](https://badge.fury.io/py/TFGENZOO.svg)\n\n# What&rsquo;s this repository?\n\nThis is a repository for some researcher to build some Generative models using Tensorflow 2.x.\n\nI NEED YOUR HELP(please let me know about formula, implementation and anything you worried)\n\n![img](https://raw.githubusercontent.com/MokkeMeguru/TFGENZOO/master/docs/tfgenzoo_header.png)\n\n# Zen of this repository\n\n    We don't want to need flexible architectures.\n    We need strict definitions for shapes, parameters, and formulas.\n    We should Implement correct codes with well-documented(tested).\n\n# How to use?\n\n## By Install\n\n- pipenv\n\n      pipenv install TFGENZOO==1.2.4.post7\n\n- pip\n\n      pip install TFGENZOO==1.2.4.post7\n\n## Source build for development\n\n1.  clone this repository (If you want to do it, I will push this repository to PYPI)\n2.  build this repository `docker-compose build`\n3.  run the environment `sh run_script.sh`\n4.  connect it via VSCode or Emacs or vi or anything.\n\n# Examples\n\n- [TFGENZOO_EXAMPLE](https://github.com/MokkeMeguru/TFGENZOO_EXAMPLE)\n\n# Roadmap\n\n- [x] Flow-based Model Architecture (RealNVP, Glow)\n- [ ] i-ResNet Model Architecture (i-ResNet, i-RevNet)\n- [ ] GANs Model Architecture (GANs)\n\n# Remarkable Backlog\n\nWhole backlog is [here](https://github.com/MokkeMeguru/TFGENZOO/wiki/Backlog)\n\n## News [2020/6/16]\n\nNew training results [Oxford-flower102](https://www.tensorflow.org/datasets/catalog/oxford_flowers102) with only 8 hours! (Quadro P6000 x 1)\n\n<table border=\"2\" cellspacing=\"0\" cellpadding=\"6\" rules=\"groups\" frame=\"hsides\">\n\n<colgroup>\n<col  class=\"org-left\" />\n\n<col  class=\"org-right\" />\n\n<col  class=\"org-right\" />\n\n<col  class=\"org-left\" />\n</colgroup>\n<thead>\n<tr>\n<th scope=\"col\" class=\"org-left\">data</th>\n<th scope=\"col\" class=\"org-right\">NLL(test)</th>\n<th scope=\"col\" class=\"org-right\">epoch</th>\n<th scope=\"col\" class=\"org-left\">pretrained</th>\n</tr>\n</thead>\n\n<tbody>\n<tr>\n<td class=\"org-left\">Oxford-flower102</td>\n<td class=\"org-right\">4.590211391448975</td>\n<td class=\"org-right\">1024</td>\n<td class=\"org-left\">---</td>\n</tr>\n</tbody>\n</table>\n\n![img](https://raw.githubusercontent.com/MokkeMeguru/TFGENZOO/master/docs/oxford.png)\n\nsee more detail, you can see [my internship&rsquo;s report](https://docs.google.com/presentation/d/12z6MZizIsytLxUb2ly7vYorFiKruIGZ2ckQ0-By4b6s/edit?usp=sharing) (Japanese only, if you need translated version, please contact me.)\n\n# Contact\n\nMokkeMeguru ([@MokkeMeguru](https://twitter.com/MeguruMokke)): DM or Mention Please (in Any language).\n\n\n",
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