flake8

theano/tests/test_flake8.py

@@ -30,7 +30,6 @@ whitelist_flake8 = [
     "tests/test_gradient.py",
     "tests/test_config.py",
     "tests/diverse_tests.py",
-    "tests/test_ifelse.py",
     "tests/test_rop.py",
     "tests/test_2nd_order_grads.py",
     "tests/run_tests_in_batch.py",

theano/tests/test_ifelse.py

@@ -3,11 +3,6 @@
 """
 
 from __future__ import print_function
-__docformat__ = 'restructedtext en'
-__authors__ = ("Razvan Pascanu ")
-__copyright__ = "(c) 2010, Universite de Montreal"
-__contact__ = "Razvan Pascanu <r.pascanu@gmail>"
-
 import unittest
 import numpy
 from nose.plugins.skip import SkipTest
@@ -17,7 +12,13 @@ import theano
 from theano import tensor
 import theano.ifelse
 from theano.ifelse import IfElse, ifelse
-from theano.tests  import unittest_tools as utt
+from theano.tests import unittest_tools as utt
+
+
+__docformat__ = 'restructedtext en'
+__authors__ = ("Razvan Pascanu ")
+__copyright__ = "(c) 2010, Universite de Montreal"
+__contact__ = "Razvan Pascanu <r.pascanu@gmail>"
 
 
 class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
@@ -63,7 +64,7 @@ class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
             # the opt.
             'fusion', 'local_add_canonizer',
             'inplace', 'constant_folding', 'constant_folding')
-        y2 = reduce(lambda x, y: x+y, [y] + range(200))
+        y2 = reduce(lambda x, y: x + y, [y] + range(200))
         f = theano.function([c, x, y], ifelse(c, x, y2), mode=mode)
         # For not inplace ifelse
         self.assertFunctionContains1(f, IfElse(1))
@@ -92,9 +93,9 @@ class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
         xlen = rng.randint(200)
         ylen = rng.randint(200)
 
-        vx1 = numpy.asarray(rng.uniform(size=(xlen,))*3, 'int32')
+        vx1 = numpy.asarray(rng.uniform(size=(xlen,)) * 3, 'int32')
         vx2 = numpy.asarray(rng.uniform(size=(xlen,)), self.dtype)
-        vy1 = numpy.asarray(rng.uniform(size=(ylen,))*3, 'int32')
+        vy1 = numpy.asarray(rng.uniform(size=(ylen,)) * 3, 'int32')
         vy2 = numpy.asarray(rng.uniform(size=(ylen,)), self.dtype)
 
         o1, o2 = f(1, vx1, vx2, vy1, vy2)
@@ -315,8 +316,8 @@ class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
         z2 = ifelse(c, x + 2, y + 2)
         z = z1 + z2
         f = theano.function([c, x, y], z)
-        assert len([x for x in f.maker.fgraph.toposort()
-                    if isinstance(x.op, IfElse)]) == 1
+        assert len([n for n in f.maker.fgraph.toposort()
+                    if isinstance(n.op, IfElse)]) == 1
 
     def test_remove_useless_inputs1(self):
         raise SkipTest("Optimization temporarily disabled")
@@ -326,8 +327,8 @@ class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
         z = ifelse(c, (x, x), (y, y))
         f = theano.function([c, x, y], z)
 
-        ifnode = [x for x in f.maker.fgraph.toposort()
-                  if isinstance(x.op, IfElse)][0]
+        ifnode = [n for n in f.maker.fgraph.toposort()
+                  if isinstance(n.op, IfElse)][0]
         assert len(ifnode.inputs) == 3
 
     def test_remove_useless_inputs2(self):
@@ -445,12 +446,12 @@ class test_ifelse(unittest.TestCase, utt.TestOptimizationMixin):
         c = tensor.iscalar('c')
 
         out = ifelse(c,
-            ifelse(c, x1, x2) + ifelse(c, y1, y2) + w1,
-            ifelse(c, x1, x2) + ifelse(c, y1, y2) + w2)
+                     ifelse(c, x1, x2) + ifelse(c, y1, y2) + w1,
+                     ifelse(c, x1, x2) + ifelse(c, y1, y2) + w2)
         f = theano.function([x1, x2, y1, y2, w1, w2, c], out,
                             allow_input_downcast=True)
         assert len([x for x in f.maker.fgraph.toposort()
-                if isinstance(x.op, IfElse)]) == 1
+                    if isinstance(x.op, IfElse)]) == 1
 
         rng = numpy.random.RandomState(utt.fetch_seed())
         vx1 = rng.uniform()