Added Power function and tests.

theano/sandbox/linalg/ops.py

@@ -1202,3 +1202,7 @@ class EigvalshGrad(Op):
 
 def eigvalsh(a, b, lower=True):
     return Eigvalsh(lower)(a, b)
+
+
+def power(x,y):
+    return x**y

theano/sandbox/linalg/tests/test_linalg.py

@@ -31,6 +31,7 @@ from theano.sandbox.linalg.ops import (cholesky,
                                        imported_scipy,
                                        Eig,
                                        inv_as_solve,
+                                       power
                                        )
 from theano.sandbox.linalg import eig, eigh, eigvalsh
 from nose.plugins.skip import SkipTest
@@ -600,3 +601,23 @@ def test_eigvalsh_grad():
     b = 10 * numpy.eye(5, 5) + rng.randn(5, 5)
     tensor.verify_grad(lambda a, b: eigvalsh(a, b).dot([1, 2, 3, 4, 5]),
                        [a, b], rng=numpy.random)
+
+
+class T_Power():
+    def test_numpy_compare(self):
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        A = tensor.matrix("A", dtype=theano.config.floatX)
+        Q = power(A, 3)
+        fn = function([A], [Q])
+        a = rng.rand(4, 4).astype(theano.config.floatX)
+
+        n_p = numpy.power(a, 3)
+        t_p = fn(a)
+        assert numpy.allclose(n_p, t_p)
+
+    def test_multiple_power(self):
+        x = tensor.matrix()
+        y = [1, 2, 3]
+        z = power(x,y)
+        f = function([x], z)
+        assert allclose(f([1, 2, 3]), [1, 4, 27])