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        "description": "[This document is a copy of the original.  `The latest version is\navailable on Tijmen Tieleman's\nhomepage. <http://www.cs.toronto.edu/~tijmen/gnumpy.html>`_]\n\nGnumpy is free software, but if you use it in scientific work that\ngets published, you should cite `this tech report\n<http://www.cs.toronto.edu/~tijmen/gnumpyTr.pdf>`_ in your\npublication.\n\nDocumentation: `here\n<http://www.cs.toronto.edu/~tijmen/gnumpyDoc.html>`_.\n\nDo you want to have both the compute power of GPU's and the\nprogramming convenience of Python numpy? Gnumpy + Cudamat will bring\nyou that.\n\nGnumpy is a simple Python module that interfaces in a way almost\nidentical to numpy, but does its computations on your computer's\nGPU. See `this example\n<http://www.cs.toronto.edu/~tijmen/gnumpy_example.py>`_, training an\nRBM using Gnumpy.\n\nGnumpy runs on top of, and therefore requires, the excellent `cudamat\n<http://code.google.com/p/cudamat/>`_ library, written by `Vlad Mnih\n<http://www.cs.toronto.edu/~vmnih/>`_.\n\nGnumpy can run in simulation mode: everything happens on the CPU, but\nthe interface is the same. This can be helpful if you like to write\nyour programs on your GPU-less laptop before running them on a\nGPU-equipped machine. It also allows you to easily test what\nperformance gain you get from using a GPU. The simulation mode\nrequires `npmat <http://www.cs.toronto.edu/~ilya/npmat.py>`_, written\nby `Ilya Sutskever <http://www.cs.toronto.edu/~ilya>`_.  [npmat is\nincluded in this distribution.]\n\nGnumpy is licensed with a BSD-style license (i.e. it's completely free\nto use for everyone, also as a component in commercial software), with\none added note: if you use it for scientific work that gets published,\nyou must include reference to the Gnumpy tech report in your\npublication. For details of the license, see the top of gnumpy.py.\n\nRecent changes:\n\n- 2012-07-25: Bugfix. gnumpy.dot(x, x), when x is a 1-dimensional array, didn't work but now works.\n- 2011-06-06: gnumpy.dot() now takes arrays of ndim>2.\n- 2011-04-19: Bugfix: several bugs involving zero size arrays were fixed.\n- 2011-04-15: Bugfix. \"x=gnumpy.zeros(10); x[array([])] = garray([])\" didn't work as it should. Now it does.\n- 2011-03-24: Added gnumpy.outer().\n- 2011-03-15: The ability to check for infs and nans automatically has been added to Gnumpy.\n- 2010-07-19: Cudamat now enables fast indexing with arrays of indices. Download the newest Cudamat to have fast indexing with arrays in Gnumpy.\n- 2010-07-08: Renamed the project to Gnumpy. It used to be called Gpunnumpy.",
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        "summary": "Gnumpy is a simple Python module that interfaces in a way almost identical to numpy, but does its computations on your computer's  GPU, using Cudamat.",
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