Mercurial > pylearn
view _nnet_ops.py @ 92:c4726e19b8ec
Finished first draft of TLearner
author | Yoshua Bengio <bengioy@iro.umontreal.ca> |
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date | Mon, 05 May 2008 18:14:32 -0400 |
parents | 76e5c0f37165 |
children | 3ef569b92fba |
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import unittest import theano._test_tensor as TT import numpy from nnet_ops import * class T_sigmoid(unittest.TestCase): def setUp(self): numpy.random.seed(9999) def test_elemwise(self): TT.verify_grad(self, Sigmoid, [numpy.random.rand(3,4)]) class T_softplus(unittest.TestCase): def setUp(self): numpy.random.seed(9999) def test_elemwise(self): TT.verify_grad(self, Softplus, [numpy.random.rand(3,4)]) class T_CrossentropySoftmax1Hot(unittest.TestCase): def setUp(self): numpy.random.seed(9999) def test0(self): y_idx = [0,1,3] def output1(a,b): return crossentropy_softmax_1hot_with_bias(a, b, y_idx)[0:1] TT.verify_grad(self, output1, [numpy.random.rand(3,4), numpy.random.rand(4)]) def test1(self): y_idx = [0,1,3] def output1(a): return crossentropy_softmax_1hot(a, y_idx)[0:1] TT.verify_grad(self, output1, [numpy.random.rand(3,4)]) if __name__ == '__main__': unittest.main()