# HG changeset patch
# User Frederic Bastien <bastienf@iro.umontreal.ca>
# Date 1212774959 14400
# Node ID 2ee53bae9ee0a1666505c2567f3d34863ec9eb3e
# Parent  23981827b7942ed470b744cc9d4b3f0028f25bcf
renamed _nnet_ops.py to _test_nnet_opt.py to be used with autotest

diff -r 23981827b794 -r 2ee53bae9ee0 _nnet_ops.py
--- a/_nnet_ops.py	Fri Jun 06 13:53:02 2008 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,41 +0,0 @@
-
-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]
-        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]
-        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)])
-
-
-
-if __name__ == '__main__':
-    unittest.main()
diff -r 23981827b794 -r 2ee53bae9ee0 _test_nnet_ops.py
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/_test_nnet_ops.py	Fri Jun 06 13:55:59 2008 -0400
@@ -0,0 +1,41 @@
+
+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]
+        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]
+        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)])
+
+
+
+if __name__ == '__main__':
+    unittest.main()