Mercurial > pylearn
view _test_xlogx.py @ 487:94a4c5b7293b
DAA code more generic:
Can now choose activation function and reconstruction cost.
author | Joseph Turian <turian@gmail.com> |
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date | Tue, 28 Oct 2008 02:21:50 -0400 |
parents | 117e5b09cf31 |
children | 242efecefd70 |
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from xlogx import xlogx import unittest from theano import compile from theano import gradient from theano.tensor import as_tensor import theano._test_tensor as TT import random import numpy.random class T_XlogX(unittest.TestCase): def test0(self): x = as_tensor([1, 0]) y = xlogx(x) y = compile.eval_outputs([y]) self.failUnless(numpy.all(y == numpy.asarray([0, 0.]))) def test1(self): class Dummy(object): def make_node(self, a): return [xlogx(a)[:,2]] TT.verify_grad(self, Dummy(), [numpy.random.rand(3,4)]) if __name__ == '__main__': unittest.main()