Mercurial > pylearn
diff _nnet_ops.py @ 117:3ef569b92fba
ported nnet_ops to new theano
author | James Bergstra <bergstrj@iro.umontreal.ca> |
---|---|
date | Wed, 07 May 2008 15:28:17 -0400 |
parents | 76e5c0f37165 |
children |
line wrap: on
line diff
--- a/_nnet_ops.py Wed May 07 13:07:33 2008 -0400 +++ b/_nnet_ops.py Wed May 07 15:28:17 2008 -0400 @@ -9,29 +9,31 @@ def setUp(self): numpy.random.seed(9999) def test_elemwise(self): - TT.verify_grad(self, Sigmoid, [numpy.random.rand(3,4)]) + 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)]) + 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), + class Dummy(object): + def make_node(self, a,b): + return crossentropy_softmax_1hot_with_bias(a, b, y_idx)[0:1] + TT.verify_grad(self, Dummy(), [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)]) + class Dummy(object): + def make_node(self, a): + return crossentropy_softmax_1hot(a, y_idx)[0:1] + TT.verify_grad(self, Dummy(), [numpy.random.rand(3,4)])