pep8

theano/misc/may_share_memory.py

@@ -11,6 +11,7 @@ from theano.tensor.basic import TensorType
 try:
     import scipy.sparse
     from theano.sparse.basic import SparseType
+
     def _is_sparse(a):
         return scipy.sparse.issparse(a)
 except ImportError:
@@ -26,6 +27,7 @@ else:
     def _is_cuda(a):
         return False
 
+
 def may_share_memory(a, b, raise_other_type=True):
     a_ndarray = isinstance(a, numpy.ndarray)
     b_ndarray = isinstance(b, numpy.ndarray)
@@ -34,16 +36,18 @@ def may_share_memory(a, b, raise_other_type=True):
     a_cuda = _is_cuda(a)
     b_cuda = _is_cuda(b)
 
-    if not(a_ndarray or a_sparse or a_cuda) or not(b_ndarray or b_sparse or b_cuda):
+    if (not(a_ndarray or a_sparse or a_cuda) or
+        not(b_ndarray or b_sparse or b_cuda)):
         if raise_other_type:
-            raise TypeError("may_share_memory support only ndarray and scipy.sparse and CudaNdarray type")
+            raise TypeError("may_share_memory support only ndarray"
+                            " and scipy.sparse and CudaNdarray type")
         return False
 
     if a_ndarray and b_ndarray:
-        return TensorType.may_share_memory(a,b)
+        return TensorType.may_share_memory(a, b)
     if a_cuda and b_cuda:
         from theano.sandbox.cuda.type import CudaNdarrayType
-        return CudaNdarrayType.may_share_memory(a,b)
+        return CudaNdarrayType.may_share_memory(a, b)
     if a_cuda or b_cuda:
         return False
-    return SparseType.may_share_memory(a,b)
+    return SparseType.may_share_memory(a, b)