Change test, because it was building an incorrect graph.

It makes no sense to have a softmax_grad node with inputs that are not matrices of the same size. C implementation would have complained. T_SoftmaxGrad.test_infer_shape now passes in FAST_COMPILE.

Change test, because it was building an incorrect graph.
5cfa6e2b · Pascal Lamblin · 5df0aeca · 5cfa6e2b
--- a/theano/tensor/nnet/tests/test_nnet.py
+++ b/theano/tensor/nnet/tests/test_nnet.py
@@ -89,9 +89,9 @@ class T_SoftmaxWithBias(unittest.TestCase):
 class T_SoftmaxGrad(unittest.TestCase):
    def test_infer_shape(self):
        a=T.constant(numpy.random.rand(3,4))
-        b=T.constant(numpy.random.rand(4))
+        b=T.constant(numpy.random.rand(3,4))
        f=theano.function([],softmax_grad(a,b).shape)
-        assert f()==[4]
+        assert numpy.all(f()==[3,4])

 class T_CrossentropySoftmax1Hot(unittest.TestCase):
    def setUp(self):