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Merge pull request #78 from machine-intelligence-laboratory/release/v0-8-0
TopicNet v0.8.0
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‎.gitignore

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build/
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dist/
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topicnet/dataset_manager/*__internals
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topicnet/tests/test_data/*__internals

‎.travis.yml

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- $HOME/.ccache
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python:
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- "3.6"
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- "3.7"
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env:
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global:
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script:
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- cd topicnet
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- py.test . --timeout=60 --cov
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- py.test tests -k "not tests/test_pipeline.py" --timeout=45 --reruns 3 --reruns-delay 3 --cov
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# TODO: - py.test tests --timeout=45 --reruns 3 --reruns-delay 3 --cov
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after_success:
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- codecov
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‎README.md

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<h1 align="center">TopicNet</h2>
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<h1 align="center">TopicNet</h1>
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<img align="right" height="15%" width="15%" src="https://avatars3.githubusercontent.com/u/49844788?s=200&v=4" style="max-width:100%;">
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<div align="center">
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Consider using TopicNet if:
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* you want to explore BigARTM functionality without writing an overhead.
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* you need help with rapid solution prototyping.
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* you want to build a good topic model quickly (out-of-box, with default parameters).
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* you want to explore BigARTM functionality without writing an overhead;
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* you need help with rapid solution prototyping;
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* you want to build a good topic model quickly (out-of-box, with default parameters);
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* you have an ARTM model at hand and you want to explore it's topics.
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`TopicNet` provides an infrastructure for your prototyping with the help of `Experiment` class and helps to observe results of your actions via [`viewers`](topicnet/viewers) module.
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]
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```
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# Contribution
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If you find a bug, or if you would like the library to have some new features — you are welcome to contact us or create an issue or a pull request!
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It also worth noting that TopicNet library is always open to improvements in several areas:
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* New custom regularizers.
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* New topic model scores.
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* New topic models or recipes to train topic models for a particular task/with some special properties.
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* New datasets (so as to make them available for everyone to download and conduct experiments with topic models).
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# Citing TopicNet
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When citing `topicnet` in academic papers and theses, please use this BibTeX entry:
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```

‎docs/cooking_machine/config_parser.html

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‎docs/cooking_machine/cubes/base_cube.html

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<title>topicnet.cooking_machine.cubes.base_cube API documentation</title>
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</header>
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<section id="section-intro">
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<summary>Source code</summary>
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<summary>
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</summary>
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<span>def <span class="ident">check_experiment_existence</span></span>(<span>topic_model)</span>
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<section class="desc"><p>Checks if topic_model has experiment.</p>
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<div class="desc"><p>Checks if topic_model has experiment.</p>
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<dt><strong><code>topic_model</code></strong> :&ensp;<code>TopicModel</code></dt>
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<span>(</span><span>num_iter, action=None, reg_search='grid', strategy=None, tracked_score_function=None, verbose=False, separate_thread=True)</span>
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<pre><code class="python">class BaseCube:
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<li><a title="topicnet.cooking_machine.cubes.regularizer_cube.RegularizersModifierCube" href="regularizer_cube.html#topicnet.cooking_machine.cubes.regularizer_cube.RegularizersModifierCube">RegularizersModifierCube</a></li>
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<li><a title="topicnet.cooking_machine.cubes.regularizer_cube.RegularizersModifierCube" href="regularizer_cube.html#topicnet.cooking_machine.cubes.regularizer_cube.RegularizersModifierCube">RegularizersModifierCube</a></li>
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