https://github.com/srush/pydecode
A dynamic programming toolkit.
https://github.com/srush/pydecode
Last synced: about 1 year ago
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A dynamic programming toolkit.
- Host: GitHub
- URL: https://github.com/srush/pydecode
- Owner: srush
- Created: 2013-09-18T17:40:23.000Z (over 12 years ago)
- Default Branch: master
- Last Pushed: 2014-10-17T18:50:33.000Z (over 11 years ago)
- Last Synced: 2025-04-12T15:12:23.696Z (about 1 year ago)
- Language: C++
- Homepage: http://www.pydecode.org
- Size: 115 MB
- Stars: 39
- Watchers: 11
- Forks: 7
- Open Issues: 2
-
Metadata Files:
- Readme: README.rst
Awesome Lists containing this project
README
PyDecode is a dynamic programming toolkit developed for research in natural langauge processing. Its aim is to be simple enough for fast prototyping, but efficient enough for research use.
.. _documentation: http://pydecode.readthedocs.org/
.. image:: _images/parsing_9_0.png
:width: 500 px
:align: center
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Features
--------
* **Simple specifications.** Dynamic programming algorithms specified through pseudo-code. ::
# Viterbi algorithm.
...
c.init(items[0, :])
for i in range(1, n):
for t in range(len(tags)):
c.set(items[i, t],
items[i-1, :],
labels=labels[i, t, :])
graph = c.finish()
* **Efficient implementation.** Core code in C++, python interfaces through numpy. ::
# Compute path.
label_weights = numpy.random.random(graph.label_size)
weights = pydecode.transform_label_array(graph, label_weights)
path = pydecode.best_path(graph, weights)
* **High-level algorithms.** Includes a set of widely-used algorithms. ::
# Inside probabilities.
inside = pydecode.inside(graph, weights, kind=pydecode.LogProb)
# (Max)-marginals.
marginals = pydecode.marginals(graph, weights)
# Pruning
mask = marginals > threshold
pruned_graph = pydecode.filter(graph, mask)
* **Integration with machine learning toolkits.** Train structured models. ::
# Train a discriminative tagger.
perceptron_tagger = StructuredPerceptron(tagger)
perceptron_tagger.fit(X, Y)
Y_test = perceptron_tagger.predict(X_test)
* **Visualization tools.** IPython integrated tools for debugging and teaching. ::
pydecode.draw(graph, paths=paths)
.. image:: _images/hmm.png
:width: 500 px
:align: center
.. Documentation, Tutorial and Gallery
.. ----------------------
.. .. hlist::
.. :columns: 2
.. * documentation_
.. * tutorial_
.. * gallery_
.. * api_
.. Features
.. -------------
.. Currently the toolkit is in development. It includes the following features:
.. * Simple construction of dynamic programs.
.. * Customizable GraphViz output for debugging.
.. * Algorithms for best path, inside scores, outside scores, and oracle scores.
.. * Several types of pruning.
.. * Integration with an (I)LP solver for constrained problems.
.. * Lagrangian Relaxation optimization tools.
.. * Semiring operations over hypergraph structures.
.. * Hooks into PyStruct for structured training.
.. * Fast k-best algorithms.
.. .. image:: https://travis-ci.org/srush/PyDecode.png?branch=master
.. :target: https://travis-ci.org/srush/PyDecode
.. _gallery: http://pydecode.readthedocs.org/en/latest/notebooks/index.html
.. _tutorial: http://pydecode.readthedocs.org/en/latest/notebooks/index.html
.. _api: http://pydecode.readthedocs.org/en/latest/api.html