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        "author": "Sean Robertson",
        "author_email": "sdrobert@cs.toronto.edu",
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        "classifiers": [
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            "License :: OSI Approved :: Apache Software License",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
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        "description": "===============\npydrobert-kaldi\n===============\n\n|travis| |appveyor| |readthedocs|\n\n`Read the latest docs <http://pydrobert-kaldi.readthedocs.io/en/latest>`_\n\n**This is student-driven code, so don't expect a stable API. I'll try to use\nsemantic versioning, but the best way to keep functionality stable is by\nforking.**\n\nWhat is it?\n-----------\n\nSome Kaldi_ SWIG_ bindings for Python. I started this project because I wanted\nto seamlessly incorporate Kaldi's I/O mechanism into the gamut of Python-based\ndata science packages (e.g. Theano, Tensorflow, CNTK, PyTorch, etc.). The code\nbase is expanding to wrap more of Kaldi's feature processing and mathematical\nfunctions, but is unlikely to include modelling or decoding.\n\nEventually, I plan on adding hooks for Kaldi audio features and pre-/post-\nprocessing. However, I have no plans on porting any code involving modelling or\ndecoding.\n\nInput/Output\n------------\n\nMost I/O can be performed with the ``pydrobert.kaldi.io.open`` function:\n\n>>> from pydrobert.kaldi import io\n>>> with io.open('scp:foo.scp', 'bm') as f:\n>>>     for matrix in f:\n>>>         pass # do something\n\n``open`` is a factory function that determines the appropriate underlying\nstream to open, much like Python's built-in ``open``. The data types we can\nread (here, a ``BaseMatrix``) are listed in\n``pydrobert.kaldi.io.enums.KaldiDataType``. Big data types, like matrices and\nvectors, are piped into Numpy_ arrays. Passing an extended filename  (e.g.\npaths to files on discs, ``'-'`` for stdin/stdout, ``'gzip -c a.ark.gz |'``,\netc.) opens a stream from which data types can be read one-by-one and in the\norder they were written. Alternatively, prepending the extended filename with\n``'ark[,[option_a[,option_b...]]:'`` or ``'scp[,...]:'`` and specifying a data\ntype allows one to open a Kaldi table for iterator-like sequential reading\n(``mode='r'``), dict-like random access reading (``mode='r+'``), or writing\n(``mode='w'``). For more information on the open function, consult the\ndocstring. Information on `Kaldi I/O`_ can be found on their website.\n\nThe submodule ``pydrobert.kaldi.io.corpus`` contains useful wrappers around\nKaldi I/O to serve up batches of data to, say, a neural network:\n\n>>> train = ShuffledData('scp:feats.scp', 'scp:labels.scp', batch_size=10)\n>>> for feat_batch, label_batch in train:\n>>>     pass  # do something\n\nLogging and CLI\n---------------\n\nBy default, Kaldi error, warning, and critical messages are piped to standard\nerror. The ``pydrobert.kaldi.logging`` submodule provides hooks into python's\nnative logging interface: the ``logging`` module. The ``KaldiLogger`` can\nhandle stack traces from Kaldi C++ code, and there are a variety of decorators\nto finagle the kaldi logging patterns to python logging patterns, or vice\nversa.\n\nYou'd likely want to explicitly handle logging when creating new kaldi-style\ncommands for command line. ``pydrobert.kaldi.io.argparse`` provides\n``KaldiParser``, an ``ArgumentParser`` tailored to Kaldi inputs/outputs. It is\nused by a few command-line entry points added by this package. They are:\n\nwrite-table-to-pickle\n  Write the contents of a kaldi table to a pickle file(s). Good for late night\n  attempts at reaching a paper deadline.\nwrite-pickle-to-table\n  Write the contents of of a pickle file(s) to a kaldi table.\nwrite-table-to-torch-dir\n  Write the contents of a kaldi table into a directory as a series of PyTorch\n  tensor files. Suitable for PyTorch data loaders with multiprocessing.\n  Requires PyTorch_.\nwrite-torch-dir-to-table\n  Write the contents of a directory of tensor files back to a Kaldi table.\n  Requires PyTorch_.\nnormalize-feat-lens\n  Ensure that features have the same length as some reference by truncating\n  or appending frames.\ncompute-error-rate\n  Compute an error rate between reference and hypothesis texts, such as a WER\n  or PER.\nnormalize-feat-lens\n  Ensure features match some reference length, either by padding or clipping\n  the end.\n\nInstallation\n------------\n\nCheck the following compatibility table to see if you can get a PyPI_ or Conda_\ninstall going:\n\n+----------+------+--------+--------+-------+\n| Platform | Arch | Python | Conda? | PyPI? |\n+==========+======+========+========+=======+\n| Windows  | 32   | 2.7    | No     | No    |\n+----------+------+--------+--------+-------+\n| Windows  | 32   | 3.5    | Yes    | No    |\n+----------+------+--------+--------+-------+\n| Windows  | 32   | 3.6    | Yes    | No    |\n+----------+------+--------+--------+-------+\n| Windows  | 32   | 3.7    | Yes    | No    |\n+----------+------+--------+--------+-------+\n| Windows  | 64   | 2.7    | No     | No    |\n+----------+------+--------+--------+-------+\n| Windows  | 64   | 3.5    | Yes    | No    |\n+----------+------+--------+--------+-------+\n| Windows  | 64   | 3.6    | Yes    | No    |\n+----------+------+--------+--------+-------+\n| Windows  | 64   | 3.7    | Yes    | No    |\n+----------+------+--------+--------+-------+\n| OSX      | 32   | -      | No     | No    |\n+----------+------+--------+--------+-------+\n| OSX      | 64   | 2.7    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n| OSX      | 64   | 3.5    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n| OSX      | 64   | 3.6    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n| OSX      | 64   | 3.7    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n| Linux    | 32   | -      | No     | No    |\n+----------+------+--------+--------+-------+\n| Linux    | 64   | 2.7    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n| Linux    | 64   | 3.5    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n| Linux    | 64   | 3.6    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n| Linux    | 64   | 3.7    | Yes    | Yes   |\n+----------+------+--------+--------+-------+\n\nTo install via ``conda``::\n\n   conda install -c sdrobert pydrobert-kaldi\n\nTo install via ``pip``::\n\n   pip install pydrobert-kaldi\n\nYou can also try building from source, but you'll have to specify where your\nBLAS install is somehow::\n\n   # for OpenBLAS\n   OPENBLASROOT=/path/to/openblas/install pip install \\\n     git+https://github.com/sdrobert/pydrobert-kaldi.git\n   # for MKL\n   MKLROOT=/path/to/mkl/install pip install \\\n     git+https://github.com/sdrobert/pydrobert-kaldi.git\n   # see setup.py for more options\n\nLicense\n-------\n\nThis code is licensed under Apache 2.0.\n\nCode found under the ``src/`` directory has been primarily copied from Kaldi.\n``setup.py`` is also strongly influenced by Kaldi's build\nconfiguration. Kaldi is also covered by the Apache 2.0 license; its specific\nlicense file was copied into ``src/COPYING_Kaldi_Project`` to live among its\nfellows.\n\n.. _Kaldi: http://kaldi-asr.org/\n.. _`Kaldi I/O`: http://kaldi-asr.org/doc/io.html\n.. _Swig: http://www.swig.org/\n.. _Numpy: http://www.numpy.org/\n.. _Conda: http://conda.pydata.org/docs/\n.. _PyPI: https://pypi.org/\n.. _PyTorch: https://pytorch.org/\n.. |travis| image:: https://travis-ci.com/sdrobert/pydrobert-kaldi.svg?branch=master\n            :target: https://travis-ci.com/sdrobert/pydrobert-kaldi\n            :alt: Travis Build Status\n.. |appveyor| image:: https://ci.appveyor.com/api/projects/status/lvjhj9pgju90wn8j/branch/master?svg=true\n              :target: https://ci.appveyor.com/project/sdrobert/pydrobert-kaldi\n              :alt: AppVeyor Build Status\n.. |readthedocs| image:: https://readthedocs.org/projects/pydrobert-kaldi/badge/?version=stable\n                 :target: https://pydrobert-kaldi.readthedocs.io/en/stable/\n                 :alt: Documentation Status\n\n\n",
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