white space fix.

theano/sandbox/cuda/var.py

@@ -19,7 +19,7 @@ class _operators(tensor.basic._tensor_py_operators):
     """Define a few properties and conversion methods for CudaNdarray Variables.
 
     The default implementation of arithemetic operators is to build graphs of TensorType
-    variables. 
+    variables.
 
     The optimization pass (specialization) will insert pure GPU implementations.
     This approach relieves the Cuda-Ops of having to deal with input argument checking and
@@ -60,7 +60,7 @@ class CudaNdarraySharedVariable(SharedVariable, _operators):
         """
         Return the value of this SharedVariable's internal array.
 
-        :param borrow: 
+        :param borrow:
                 permit the return of internal storage, when used in conjunction with
                 ``return_internal_type=True``
         :param return_internal_type:
@@ -110,7 +110,7 @@ class CudaNdarraySharedVariable(SharedVariable, _operators):
             * You change the value of the shared variable via set_value, not via the .value
               accessors. You should not use the .value accessors anyway, since they will soon be
               deprecated and removed.
-            
+
             It is also worth mentioning that, for efficient transfer to the GPU, Theano will make the new data
             ``c_contiguous``. This can require an extra copy of the data on the host.
         """
@@ -142,7 +142,7 @@ def cuda_shared_constructor(value, name=None, strict=False,
 
     # THIS CONSTRUCTOR TRIES TO CAST VALUE TO A FLOAT32, WHICH THEN GOES ONTO THE CARD
     # SO INT shared vars, float64 shared vars, etc. all end up on the card.
-    # THIS IS NOT THE DEFAULT BEHAVIOUR THAT WE WANT. 
+    # THIS IS NOT THE DEFAULT BEHAVIOUR THAT WE WANT.
     # SEE float32_shared_constructor
 
     #TODO: what should strict mean in this context, since we always have to make a copy?
@@ -172,7 +172,7 @@ def float32_shared_constructor(value, name=None, strict=False,
     """SharedVariable Constructor for CudaNdarrayType from numpy.ndarray or CudaNdarray"""
 
     # if value isn't a float32 ndarray, or a CudaNdarray then raise
-    
+
     if not isinstance(value, (numpy.ndarray, theano.sandbox.cuda.CudaNdarray)):
         raise TypeError('ndarray or CudaNdarray required')
     if isinstance(value, numpy.ndarray) and value.dtype.num != CudaNdarrayType.typenum: