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+.. xnmt documentation master file, created by
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+eXtensible Neural Machine Translation (xnmt)
+============================================
+
+This is a repository for the extensible neural machine translation toolkit ``xnmt``.
+It is coded in Python based on `DyNet <http://github.com/clab/dynet>`.
+
+Usage Directions
+----------------
+
+If you want to try to run an experiment, you can do so using sample configurations in the ``examples``
+directory. For example, if you wnat to try the default configuration file,
+which trains an attentional encoder-decoder model, you can do so by running
+
+    python xnmt/xnmt_run_experiments.py examples/standard.yaml
+
+There are other examples here:
+
+* ``examples/standard.yaml``: An attentional encoder-decoder model
+* ``examples/debug.yaml``: A simple debugging configuration that should run super-fast
+* ``examples/speech.yaml``: An example of speech-to-text translation
+
+See ``experiments.md`` for more details about writing experiment configuration files.
+
+Programming Style
+-----------------
+
+The over-arching goal of ``xnmt`` is that it be easy to use for research. When implementing a new
+method, it should require only minimal changes (e.g. ideally the changes will be limited to a
+single file, over-riding an existing class). Obviously this ideal will not be realizable all the
+time, but when designing new functionality, try to think of this goal.
+
+There are also a minimal of coding style conventions:
+* Follow Python conventions, and be Python2/3 compatible.
+* Functions should be snake case.
+* Indentation should be two whitespace characters.
+
+We will aim to write unit tests to make sure things don't break, but these are not implemented yet.
+
+In variable names, common words should be abbreviated as:
+* source -> src
+* target -> trg
+* sentence -> sent
+* hypothesis -> hyp