update tests

theano/tensor/nnet/tests/test_bn.py

@@ -34,7 +34,7 @@ def test_bn():
     utt.verify_grad(batch_normalization, [X, G, B, M, V])
 
     bn_op = batch_normalization(x, g, b, x.mean(axis=0, keepdims=True), x.std(axis=0, keepdims=True))
-    bn_ref_op = bn_ref(x, g, b, x.mean(axis=0, keepdims=True), x.var(axis=0, keepdims=True))
+    bn_ref_op = bn_ref(x, g, b, x.mean(axis=0, keepdims=True), x.std(axis=0, keepdims=True))
     f = theano.function([x, b, g], [bn_op])
     f_ref = theano.function([x, b, g], [bn_ref_op])
     res = f(X, G, B)
@@ -66,7 +66,7 @@ def test_bn_feature_maps():
                                 g.dimshuffle('x', 0, 'x', 'x'),
                                 b.dimshuffle('x', 0, 'x', 'x'),
                                 m.dimshuffle('x', 0, 'x', 'x'),
-                                v.dimshuffle('x', 0, 'x', 'x'), axis=1)
+                                v.dimshuffle('x', 0, 'x', 'x'))
     bn_ref_op = bn_ref(x,
                        g.dimshuffle('x', 0, 'x', 'x'),
                        b.dimshuffle('x', 0, 'x', 'x'),
@@ -78,11 +78,10 @@ def test_bn_feature_maps():
     res_ref = f_ref(X, G, B, M, V)
     utt.assert_allclose(res_ref, res)
 
-    def conv_bn(inputs, gamma, beta, mean, variance):
+    def conv_bn(inputs, gamma, beta, mean, std):
         return batch_normalization(inputs,
                                    gamma.dimshuffle('x', 0, 'x', 'x'),
                                    beta.dimshuffle('x', 0, 'x', 'x'),
                                    mean.dimshuffle('x', 0, 'x', 'x'),
-                                   variance.dimshuffle('x', 0, 'x', 'x'),
-                                   axis=1)
+                                   std.dimshuffle('x', 0, 'x', 'x'))
     utt.verify_grad(conv_bn, [X, G, B, M, V])