flakes8

theano/sandbox/multinomial.py

@@ -176,10 +176,10 @@ class MultinomialFromUniform(Op):
             z[0].fill(0)
 
         nb_multi = pvals.shape[0]
-        nb_outcomes = pvals.shape[1]
         # Original version that is not vectorized. I keep it here as
         # it is more readable.
         # For each multinomial, loop over each possible outcome
+        # nb_outcomes = pvals.shape[1]
         # for c in range(n_samples):
         #    for n in range(nb_multi):
         #        waiting = True

theano/tests/test_ifelse.py

@@ -494,8 +494,8 @@ class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
         correct = (score * y > 0)
 
         loss = ifelse(correct, 0, 1)
-        updates = [(param, param - 0.5 * tensor.grad(cost=loss, wrt=param))
-                   for param in params]
+        [(param, param - 0.5 * tensor.grad(cost=loss, wrt=param))
+         for param in params]
 
 
 if __name__ == '__main__':