file theano/gof/tests/test_graph_opt_caching.py

theano/gof/tests/test_graph_opt_caching.py

 from __future__ import absolute_import, print_function, division
 import os
-import numpy
+import numpy as np
 import theano
 import theano.tensor as T
 
@@ -19,20 +19,20 @@ def test_graph_opt_caching():
         theano.config.cache_optimizations = True
         a = T.fmatrix('a')
         b = T.fmatrix('b')
-        c = theano.shared(numpy.ones((10, 10), dtype=floatX))
-        d = theano.shared(numpy.ones((10, 10), dtype=floatX))
+        c = theano.shared(np.ones((10, 10), dtype=floatX))
+        d = theano.shared(np.ones((10, 10), dtype=floatX))
         e = T.sum(T.sum(T.sum(a ** 2 + b) + c) + d)
         f1 = theano.function([a, b], e, mode=mode)
 
         m = T.fmatrix('x1')
         n = T.fmatrix('x2')
-        p = theano.shared(numpy.ones((10, 10), dtype=floatX))
-        q = theano.shared(numpy.ones((10, 10), dtype=floatX))
+        p = theano.shared(np.ones((10, 10), dtype=floatX))
+        q = theano.shared(np.ones((10, 10), dtype=floatX))
         j = T.sum(T.sum(T.sum(m ** 2 + n) + p) + q)
         f2 = theano.function([m, n], j, mode=mode)
 
-        in1 = numpy.ones((10, 10), dtype=floatX)
-        in2 = numpy.ones((10, 10), dtype=floatX)
+        in1 = np.ones((10, 10), dtype=floatX)
+        in2 = np.ones((10, 10), dtype=floatX)
         assert f1(in1, in2) == f2(in1, in2)
     finally:
         theano.config.cache_optimizations = default