tests of the roperator/loperator

theano/tensor/tests/test_rop.py

+"""
+ WRITE ME
+
+ Tests for the R operator / L operator
+"""
+
+import unittest
+from theano.tests  import unittest_tools as utt
+from theano import function
+import theano
+import theano.tensor as TT
+import numpy
+
+class test_rop(unittest.TestCase):
+
+    def test_specifyshape(self):
+        rng  = numpy.random.RandomState(utt.fetch_seed())
+        vx = numpy.asarray(rng.uniform(size=(5,)), theano.config.floatX)
+        vv = numpy.asarray(rng.uniform(size=(5,)), theano.config.floatX)
+
+        x  = TT.vector('x')
+        v  = TT.vector('v')
+        y  = TT.specify_shape(x, (5,))
+        yv = TT.Rop(y,x,v)
+        rop_f = function([v,x], yv)
+        J, _ = theano.scan( lambda i,y,x: TT.grad(y[i],x),
+                           sequences = TT.arange(x.shape[0]),
+                           non_sequences = [y,x])
+        sy = TT.dot(J, v)
+
+        scan_f = function([x,v], sy)
+
+        v1 = rop_f(vx,vv)
+        v2 = scan_f(vx,vv)
+        assert numpy.allclose(v1,v1)
+
+
+class test_lop(unittest.TestCase):
+
+    def test_specifyshape(self):
+        rng  = numpy.random.RandomState(utt.fetch_seed())
+        vx = numpy.asarray(rng.uniform(size=(5,)), theano.config.floatX)
+        vv = numpy.asarray(rng.uniform(size=(5,)), theano.config.floatX)
+
+        x  = TT.vector('x')
+        v  = TT.vector('v')
+        y  = TT.specify_shape(x, (5,))
+        yv = TT.Lop(y,x,v)
+        rop_f = function([v,x], yv)
+        J, _ = theano.scan( lambda i,y,x: TT.grad(y[i],x),
+                           sequences = TT.arange(x.shape[0]),
+                           non_sequences = [y,x])
+        sy = TT.dot(v, J)
+
+        scan_f = function([x,v], sy)
+
+        v1 = rop_f(vx,vv)
+        v2 = scan_f(vx,vv)
+        assert numpy.allclose(v1,v1)
+
+