Merge pull request #4205 from abergeron/fix_buildbot2

theano/sandbox/cuda/tests/test_opt.py

@@ -823,7 +823,8 @@ def test_blocksparse_gpu_gemv_opt():
 
     f = theano.function([W, h, iIdx, b, oIdx], o, mode=mode_with_gpu)
 
-    assert isinstance(f.maker.fgraph.toposort()[-2].op, GpuSparseBlockGemv)
+    assert sum(1 for n in f.maker.fgraph.apply_nodes
+               if isinstance(n.op, GpuSparseBlockGemv)) == 1
 
 
 def test_blocksparse_gpu_outer_opt():
@@ -839,7 +840,8 @@ def test_blocksparse_gpu_outer_opt():
                                                                wrt=W)],
                         mode=mode_with_gpu)
 
-    assert isinstance(f.maker.fgraph.toposort()[-2].op, GpuSparseBlockOuter)
+    assert sum(1 for n in f.maker.fgraph.apply_nodes
+               if isinstance(n.op, GpuSparseBlockOuter)) == 1
 
 
 class test_diag(theano.tensor.tests.test_nlinalg.test_diag):

theano/tensor/basic.py

@@ -1355,7 +1355,7 @@ class MaxAndArgmax(Op):
         if axes is None:
             axes = tuple(range(x.ndim))
         else:
-            axes = tuple(axes)
+            axes = tuple(int(ax) for ax in axes)
         max[0] = theano._asarray(numpy.max(x, axes),
                                  dtype=node.outputs[0].dtype)
         # Numpy does not support multiple axes for argmax

theano/tensor/nnet/tests/test_abstract_conv.py

@@ -64,6 +64,8 @@ class TestGetConvOutShape(unittest.TestCase):
 
 class BaseTestConv2d(unittest.TestCase):
     def setUp(self):
+        if theano.config.blas.ldflags == '':
+            raise SkipTest("BLAS required for reference")
         self.inputs_shapes = [(8, 1, 12, 12), (8, 1, 18, 18), (2, 1, 4, 4),
                               (6, 1, 10, 11), (2, 1, 6, 5), (1, 5, 9, 9)]
         self.filters_shapes = [(5, 1, 2, 2), (4, 1, 3, 3), (2, 1, 3, 3),