speed up misc.may_share_memory()

theano/misc/may_share_memory.py

@@ -15,12 +15,14 @@ try:
     def _is_sparse(a):
         return scipy.sparse.issparse(a)
 except ImportError:
-    #scipy not imported, their can be only ndarray and cudandarray
+    # scipy not imported, their can be only ndarray and cudandarray
     def _is_sparse(a):
         return False
 
 from theano.sandbox import cuda
 if cuda.cuda_available:
+    from theano.sandbox.cuda.type import CudaNdarrayType
+
     def _is_cuda(a):
         return isinstance(a, cuda.CudaNdarray)
 else:
@@ -40,13 +42,19 @@ else:
 def may_share_memory(a, b, raise_other_type=True):
     a_ndarray = isinstance(a, numpy.ndarray)
     b_ndarray = isinstance(b, numpy.ndarray)
-    a_sparse = _is_sparse(a)
-    b_sparse = _is_sparse(b)
+    if a_ndarray and b_ndarray:
+        return TensorType.may_share_memory(a, b)
     a_cuda = _is_cuda(a)
     b_cuda = _is_cuda(b)
+    if a_cuda and b_cuda:
+        return CudaNdarrayType.may_share_memory(a, b)
     a_gpua = _is_gpua(a)
     b_gpua = _is_gpua(b)
+    if a_gpua and b_gpua:
+        return gpuarray.pygpu.gpuarray.may_share_memory(a, b)
 
+    a_sparse = _is_sparse(a)
+    b_sparse = _is_sparse(b)
     if (not(a_ndarray or a_sparse or a_cuda or a_gpua) or
         not(b_ndarray or b_sparse or b_cuda or b_gpua)):
         if raise_other_type:
@@ -54,13 +62,6 @@ def may_share_memory(a, b, raise_other_type=True):
                             " and scipy.sparse, CudaNdarray or GpuArray type")
         return False
 
-    if a_ndarray and b_ndarray:
-        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)
-    if a_gpua and b_gpua:
-        return gpuarray.pygpu.gpuarray.may_share_memory(a, b)
     if a_cuda or b_cuda or a_gpua or b_gpua:
         return False
     return SparseType.may_share_memory(a, b)