pep8 errors

theano/compile/tests/test_function_module.py

@@ -40,7 +40,8 @@ class T_function(unittest.TestCase):
         fn = function([], None)  # ok
         rval = fn()
         if rval == []:
-            raise SkipTest("See #254: Using None as function output leads to [] return value")
+            raise SkipTest("See #254: Using None as function output leads"
+                           "to [] return value")
         else:
             assert rval is None
 

theano/sandbox/scan_module/tests/test_scan.py

@@ -471,8 +471,9 @@ class TestScan(unittest.TestCase):
         # place (even when told not to by DebugMode). As this op will change
         # soon, and it is in the sandbox and not for user consumption, the
         # error is marked as KnownFailure
-        
-        raise SkipTest("Work-in-progress sandbox ScanOp is not fully functional yet")
+
+        raise SkipTest("Work-in-progress sandbox ScanOp is"
+                       "not fully functional yet")
 
         def f_pow2(x_tm1):
             return 2 * x_tm1
@@ -508,7 +509,8 @@ class TestScan(unittest.TestCase):
         # place (even when told not to by DebugMode). As this op will change
         # soon, and it is in the sandbox and not for user consumption, the
         # error is marked as KnownFailure
-        raise SkipTest("Work-in-progress sandbox ScanOp is not fully functional yet")
+        raise SkipTest("Work-in-progress sandbox"
+                       "ScanOp is not fully functional yet")
 
         def f_rnn(u_t, x_tm1, W_in, W):
             return u_t * W_in + x_tm1 * W

theano/scan_module/tests/test_scan.py

@@ -3271,7 +3271,8 @@ class T_Scan(unittest.TestCase):
                     if isinstance(x.op, theano.tensor.Elemwise)]) == 0
 
     def test_alloc_inputs2(self):
-        raise SkipTest("This tests depends on an optimization for scan that has not been implemented yet.")
+        raise SkipTest("This tests depends on an optimization for"
+                       "scan that has not been implemented yet.")
         W1 = tensor.matrix()
         W2 = tensor.matrix()
         h0 = tensor.vector()
@@ -3498,7 +3499,9 @@ class T_Scan(unittest.TestCase):
         assert out == 24
 
     def test_infershape_seq_shorter_nsteps(self):
-        raise SkipTest("This is a generic problem with infershape that has to be discussed and figured out")
+        raise SkipTest("This is a generic problem with"
+                       "infershape that has to be discussed"
+                       "and figured out")
         x = tensor.vector('x')
         [o1, o2], _ = theano.scan(lambda x, y: (x + 1, y + x),
                          sequences=x,

theano/tensor/tests/test_basic.py

@@ -6120,7 +6120,8 @@ class test_arithmetic_cast(unittest.TestCase):
                                     # a float32 may result in a complex64. As
                                     # of 1.9.2. this is still the case so it is
                                     # probably by design
-                                    raise SkipTest("Known issue with numpy >= 1.6.x see #761")
+                                    raise SkipTest("Known issue with"
+                                                   "numpy >= 1.6.x see #761")
                                 # In any other situation: something wrong is
                                 # going on!
                                 assert False

theano/tensor/tests/test_opt.py

@@ -1558,7 +1558,8 @@ def test_log_add():
         f([10000], [10000])  # causes overflow if handled incorrectly
         assert numpy.allclose(f([10000], [10000]), 20000)
     except AssertionError:
-        raise SkipTest("log(add(exp)) is not stabilized when adding more than 2 elements, see #623")
+        raise SkipTest("log(add(exp)) is not stabilized when adding"
+                       "more than 2 elements, see #623")
 
     # TODO: test that the optimization works in the presence of broadcasting.
 
@@ -4025,7 +4026,8 @@ def test_constant_get_stabilized():
 
     except (AssertionError, theano.compile.debugmode.InvalidValueError):
         raise SkipTest('Theano optimizes constant before stabilization.'
-            'This breaks stabilization optimization in some cases. See #504.')
+                       'This breaks stabilization optimization in some'
+                       'cases. See #504.')
 
 
 class T_local_switch_sink(unittest.TestCase):
@@ -4282,8 +4284,11 @@ class T_local_erfc(unittest.TestCase):
             0].op.scalar_op.fgraph.apply_nodes) == 22, len(f.maker.fgraph.toposort()[0].fgraph.toposort()[0].op.scalar_op.fgraph.apply_nodes)
         # TODO: fix this problem
         if theano.config.floatX == "float32" and theano.config.mode in ["DebugMode", "DEBUG_MODE"]:
-            raise SkipTest('The python code upcast somewhere internally some value of float32 to python float for part of its computation.'
-                'That make that the c and python code dont generate the same value. You can ignore this error.')
+            raise SkipTest('The python code upcast somewhere internally'
+                           'some value of float32 to python float for'
+                           'part of its computation. That make that the'
+                           'c and python code dont generate the same value.'
+                           'You can ignore this error.')
         assert all(numpy.isfinite(f(val)))
 
     def test_local_grad_log_erfc_neg(self):
@@ -4352,7 +4357,11 @@ class T_local_erfc(unittest.TestCase):
         # TODO: fix this problem
         if theano.config.floatX == "float32" and theano.config.mode in ["DebugMode", "DEBUG_MODE"]:
             # Showing this test error is a duplicate of the one in test_local_log_erfc. We hide it.
-            #raise KnownFailureTest("the python code upcast somewhere internally some value of float32 to python float for part of its computation. That make that the c and python code don't generate the same value. You can ignore this error. This happen in an intermediate step that don't show in the final result.")
+            # raise KnownFailureTest("the python code upcast somewhere internally some value of
+            # float32 to python float for part of its computation.
+            # That make that the c and python code do not generate the same value.
+            # You can ignore this error.
+            # This happen in an intermediate step that don't show in the final result.")
             pass
         else:
             assert all(numpy.isfinite(f(val)))

theano/tests/test_rop.py

@@ -190,8 +190,9 @@ class RopLop_checker(unittest.TestCase):
         assert numpy.allclose(v1, v2), ('LOP mismatch: %s %s' % (v1, v2))
 
         if known_fail:
-            raise SkipTest('Rop doesn t handle non-differentiable inputs correctly.' 
-                'Bug exposed by fixing Add.grad method.')
+            raise SkipTest('Rop does not handle non-differentiable inputs'
+                           'correctly. Bug exposed by fixing Add.grad method.')
+
 
 class test_RopLop(RopLop_checker):
     def test_shape(self):