Add seed_rng() calls in tests.

advanced.tex

@@ -196,8 +196,7 @@ \section{How to Make an Op (Python)}
 \end{frame}
 
 \begin{frame}{Tests}
-To test the \code{infer_shape} method we use \code{InferShapeTester}
-\lstinputlisting[linerange={5-5,19-32}]{test_doubleop.py}
+\lstinputlisting[linerange={5-5,20-34}]{test_doubleop.py}
 \end{frame}
 
 \begin{frame}{Gradient}
@@ -220,7 +219,7 @@ \section{How to Make an Op (Python)}
 
 \begin{frame}{Tests}
 To test the gradient we use \code{verify_grad}
-\lstinputlisting[linerange={5-5,33-41}]{test_doubleop.py}
+\lstinputlisting[linerange={5-5,36-44}]{test_doubleop.py}
 It will compute the gradient numerically and symbolically (using our \code{grad()} method) and compare the two.
 \end{frame}
 

test_doubleop.py

@@ -9,6 +9,7 @@
 
 
 def test_doubleop():
+    utt.seed_rng()
     x = matrix()
     f = function([x], DoubleOp()(x))
     inp = numpy.asarray(numpy.random.rand(5, 4),
@@ -19,6 +20,7 @@ def test_doubleop():
 
 class test_Double(utt.InferShapeTester):
     def test_infer_shape(self):
+        utt.seed_rng()
         x = matrix()
         self._compile_and_check(
             # function inputs (symbolic)
@@ -33,14 +35,10 @@ def test_infer_shape(self):
 
 
 def test_doubleop_grad():
+    utt.seed_rng()
     utt.verify_grad(
         # Op instance
         DoubleOp(),
         # Numeric inputs
         [numpy.random.rand(5, 7, 2)]
         )
-
-
-class test_DoubleRop(RopLop_checker):
-    def test_double_rop(self):
-        self.check_rop_lop(DoubleOp()(self.x), self.in_shape)