Update numpy implementation of PoolRop

theano/tests/test_rop.py

@@ -21,6 +21,7 @@ import numpy
 from theano.gof import Op, Apply
 from theano.gradient import grad_undefined
 from theano.tests.unittest_tools import SkipTest
+from theano.tensor.signal.pool import Pool
 from theano.tensor.nnet import conv, conv2d
 
 '''
@@ -255,6 +256,28 @@ class test_RopLop(RopLop_checker):
             self.x[:4].dimshuffle('x', 0), 0).sum(axis=1),
             (1,))
 
+    def test_downsample(self):
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        test_ws = ((1, 1), (3, 2), (2, 3))
+        vx = (rng.rand(2, 3, 3, 4) * 2.0).astype(theano.config.floatX)
+        vv = (rng.rand(2, 3, 3, 4) * 2.0).astype(theano.config.floatX)
+        input = theano.shared(vx)
+        eval_p = theano.shared(vv)
+        for ws in test_ws:
+            for ignore_border in [False, True]:
+                out = Pool(ignore_border)(input, ws).flatten()
+                yv = tensor.Rop(out, input, eval_p)
+                rop_f = function([], yv, on_unused_input='ignore')
+                sy, _ = theano.scan(lambda i, y, x, v:
+                                    (tensor.grad(y[i], x) * v).sum(),
+                                    sequences=tensor.arange(out.shape[0]),
+                                    non_sequences=[out, input, eval_p])
+                scan_f = function([], sy, on_unused_input='ignore')
+                v1 = rop_f()
+                v2 = scan_f()
+                assert numpy.allclose(v1, v2), ("Rop mismatch: %s %s" %
+                                                (v1, v2))
+
     def test_conv(self):
         for conv_op in [conv.conv2d, conv2d]:
             for border_mode in ['valid', 'full']: