Mercurial > pylearn
view _test_onehotop.py @ 470:bd937e845bbb
new stuff: algorithms/logistic_regression, datasets/MNIST
author | James Bergstra <bergstrj@iro.umontreal.ca> |
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date | Wed, 22 Oct 2008 15:56:53 -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()