Mercurial > pylearn
view _test_onehotop.py @ 496:f13847478c6d
A few more ideas, in comments
author | Joseph Turian <turian@gmail.com> |
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date | Tue, 28 Oct 2008 12:09:49 -0400 |
parents | 18702ceb2096 |
children | 844bad76459c |
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from onehotop import one_hot import unittest from theano import compile from theano import gradient from theano.tensor import as_tensor import random import numpy.random class T_OneHot(unittest.TestCase): def test0(self): x = as_tensor([3, 2, 1]) y = as_tensor(5) o = one_hot(x, y) y = compile.eval_outputs([o]) self.failUnless(numpy.all(y == numpy.asarray([[0, 0, 0, 1, 0], [0, 0, 1, 0, 0], [0, 1, 0, 0, 0]]))) if __name__ == '__main__': unittest.main()