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Topicnet 0.5.0 prerelease
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Evgeny-Egorov-Projects authored Dec 27, 2019
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2 changes: 1 addition & 1 deletion .travis.yml
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script:
- cd ../TopicNet/topicnet
- py.test . --timeout=20 --cov
- py.test . --timeout=40 --cov

after_success:
- codecov
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# TopicNet
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/TopicNet)
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[Русская версия](README-rus.md)

---
### What is TopicNet?
TopicNet is a high-level interface running on top of [BigARTM](https://github.com/bigartm/bigartm) developed in [Machine Intelligence Laboratory](https://mipt.ai/en).
TopicNet is a high-level interface developed by [Machine Intelligence Laboratory](https://mipt.ai/en) for [BigARTM](https://github.com/bigartm/bigartm) library.

```TopicNet``` library was created to assist in the task of building topic models. It aims at automating model training routine freeing more time for artistic process of constructing a target functional for the task at hand.

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```TopicNet``` provides an infrastructure for your prototyping (```Experiment``` class) and helps to observe results of your actions via ```viewers``` module.

![GitHub contributors](https://img.shields.io/github/contributors/machine-intelligence-laboratory/TopicNet)
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[![GitHub last commit](https://img.shields.io/github/last-commit/machine-intelligence-laboratory/TopicNet)](https://github.com/machine-intelligence-laboratory/TopicNet/commits/master)
### How to start?
Define `TopicModel` from an ARTM model at hand or with help from `model_constructor` module, where you can set models main parameters. Then create an `Experiment`, assigning a root position to this model and path to store your experiment. Further, you can define a set of training stages by the functionality provided by the `cooking_machine.cubes` module.

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ignore:
- "test_*.py" # ignore tests
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</head>
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<header>
<h1 class="title">Module <code>topicnet.cooking_machine.cubes</code></h1>
</header>
<h1 id="cubes-and-their-strategies">Cubes and their Strategies</h1>
<p>&lt;&lt;&lt;&lt;&lt;&lt;&lt; HEAD # Cubes and their Strategies</p>
<p>Cube types:</p>
<ul>
<li><code>BaseCube</code> — a parent class for all the Cubes</li>
Expand Down Expand Up @@ -54,6 +55,18 @@ <h2 id="what-do-you-need-to-create-a-new-cube">What do you need to create a new
<li><p><code>get_jsonable_from_parameters()[i]</code> corresponds to the same cube step as <code>parameters[i]</code>.</p></li>
</ol>
<section id="section-intro">
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">from .base_cube import BaseCube, retrieve_score_for_strategy
from .regularizer_cube import RegularizersModifierCube
from .controller_cube import RegularizationControllerCube
from .cube_creator import CubeCreator
from .perplexity_strategy import PerplexityStrategy
from .greedy_strategy import GreedyStrategy
from .strategy import BaseStrategy</code></pre>
</details>
</section>
<section>
<h2 class="section-title" id="header-submodules">Sub-modules</h2>
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</section>
</article>
<nav id="sidebar">
<h1><code>Topicnet</code> library documentation </h1>
<h1><code>TopicNet</code> library documentation </h1>
<div class="toc">
<ul></ul>
</div>
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