Shape_i.perform - optimization. skip _asarray() when output is provided.

theano/tensor/opt.py

@@ -267,7 +267,10 @@ class Shape_i(T.Op):
             raise TypeError('x has too few dimensions for Shape_i', (x, self.i))
         return T.Apply(self, [x], [T.lscalar()])
     def perform(self, node, (x, ), (out, )):
-        out[0] = theano._asarray(x.shape[self.i], dtype = 'int64')
+        if out[0] is None:
+            out[0] = theano._asarray(x.shape[self.i], dtype='int64')
+        else:
+            out[0][...] = x.shape[self.i]
     def grad(self, (x,), (gz,)):
         return [None]