Made DownsampleFactorMax.out_shape work correctly with tensor variable.

theano/tensor/signal/downsample.py

@@ -65,7 +65,8 @@ class DownsampleFactorMax(Op):
 
         :param imgshape: the shape of a tensor of images. The last two elements are interpreted
         as the number of rows, and the number of cols.
-        :type imgshape: tuple, list, or similar.
+        :type imgshape: tuple, list, or similar of integer or
+        scalar Theano variable.
 
         :param ds: downsample factor over rows and columns
         :type ds: list or tuple of two ints
@@ -83,10 +84,15 @@ class DownsampleFactorMax(Op):
             raise TypeError('imgshape must have at least two elements (rows, cols)')
         r, c = imgshape[-2:]
         rval = list(imgshape[:-2])+[ r/ds[0], c/ds[1]]
+
         if not ignore_border:
-            if r % ds[0]:
+            if isinstance(r, theano.Variable):
+                rval[-2] = tensor.switch(r % ds[0], rval[-2] + 1, rval[-2])
+            elif r % ds[0]:
                 rval[-2] += 1
-            if c % ds[1]:
+            if isinstance(c, theano.Variable):
+                rval[-1] = tensor.switch(c % ds[1], rval[-1] + 1, rval[-1])
+            elif c % ds[1]:
                 rval[-1] += 1
         return rval
 

theano/tensor/signal/tests/test_downsample.py

@@ -163,13 +163,12 @@ class TestDownsampleFactorMax(utt.InferShapeTester):
 
         images = tensor.dtensor4()
         rng = numpy.random.RandomState(utt.fetch_seed())
-        maxpoolshps = ((1, 1), (2, 2), (3, 3), (2, 3))
-        # maxpoolshps = ((1, 1), (2, 3), (3, 2))
+        maxpoolshps = ((1, 1), (2, 2), (3, 3), (2, 3), (3, 2))
         imval = rng.rand(4, 10, 64, 64)
         # imval = rng.rand(2, 3, 3, 4)
         for maxpoolshp in maxpoolshps:
-            for ignore_border in [True]:
-            # for ignore_border in [True, False]:
+            for ignore_border in [True, False]:
+                print maxpoolshp, ignore_border
                 self._compile_and_check([images],
                         [DownsampleFactorMax(maxpoolshp,
                         ignore_border=ignore_border)(images)],