Fix comments and move code to detect those type of errors

theano/tensor/tests/test_extra_ops.py

@@ -134,6 +134,19 @@ class TestBinCountOp(utt.InferShapeTester):
 
     def test_bincountFn(self):
         w = T.vector('w')
+        def ref(data, w=None, minlength=None):
+            size = data.max() + 1
+            if minlength:
+                size = max(size, minlength)
+            if w is not None:
+                out = np.zeros(size, dtype=w.dtype)
+                for i in range(data.shape[0]):
+                    out[data[i]] += w[i]
+            else:
+                out = np.zeros(size, dtype=a.dtype)
+                for i in range(data.shape[0]):
+                    out[data[i]] += 1
+            return out
         for dtype in ('int8', 'int16', 'int32', 'int64',
                       'uint8', 'uint16', 'uint32', 'uint64'):
             x = T.vector('x', dtype=dtype)
@@ -144,21 +157,8 @@ class TestBinCountOp(utt.InferShapeTester):
             f1 = theano.function([x], bincount(x))
             f2 = theano.function([x, w], bincount(x, weights=w))
 
-            def ref(data, w=None, minlength=None):
-                size = data.max() + 1
-                if minlength:
-                    size = max(size, minlength)
-                if w:
-                    out = np.zeros(size, dtype=weights.dtype)
-                    for i in range(data.shape[0]):
-                        out[data[i]] += weights[i]
-                else:
-                    out = np.zeros(size, dtype=a.dtype)
-                    for i in range(data.shape[0]):
-                        out[data[i]] += 1
-                return out
             assert (ref(a) == f1(a)).all()
-            assert np.allclose(ref(a, w), f2(a, weights))
+            assert np.allclose(ref(a, weights), f2(a, weights))
             f3 = theano.function([x], bincount(x, minlength=55))
             f4 = theano.function([x], bincount(x, minlength=5))
             assert (ref(a, minlength=55) == f3(a)).all()