[CRASH] skip cudnn tests on gpu that are too old.

theano/sandbox/cuda/dnn.py

@@ -7,7 +7,7 @@ from theano.gof.type import CDataType
 from theano.compat import PY3
 from theano.compat.six import StringIO
 from theano.sandbox.cuda.type import CudaNdarrayType
-from theano.sandbox.cuda import GpuOp
+from theano.sandbox.cuda import GpuOp, active_device_number, device_properties
 from theano.sandbox.cuda.basic_ops import (as_cuda_ndarray_variable,
                                            gpu_contiguous)
 from theano.sandbox.cuda.blas import GpuConv
@@ -16,6 +16,23 @@ from theano.sandbox.cuda.nnet import GpuSoftmax
 from theano.sandbox.cuda.nvcc_compiler import NVCC_compiler
 
 
+def dnn_available():
+    if dnn_available.avail is None:
+        dev = active_device_number()
+        if device_properties(dev)['major'] < 3:
+            dnn_available.msg = "Device not supported by cuDNN"
+            dnn_available.avail = False
+        else:
+            dnn_available.msg = "Can not find the cuDNN library"
+            dnn_available.avail = theano.gof.cmodule.GCC_compiler.try_flags(
+                ["-l", "cudnn"])
+    return dnn_available.avail
+
+
+dnn_available.avail = None
+dnn_available.msg = None
+
+
 class DnnBase(GpuOp):
     """
     Creates a handle for cudnn and pulls in the cudnn libraries and headers.

theano/sandbox/cuda/tests/test_conv_cuda_ndarray.py

@@ -578,8 +578,8 @@ def test_gemm_valid():
 
 
 def test_dnn_valid():
-    if cuda.device_properties(cuda.active_device_number())['major'] < 3:
-        raise SkipTest('Current GPU too old')
+    if not cuda.dnn.dnn_available():
+        raise SkipTest(cuda.dnn.dnn_available.msg)
     for t in _test_valid(GpuDnnConv, mode=theano_mode.including("cudnn")):
         yield t
 
@@ -659,8 +659,8 @@ def test_gemm_full():
 
 
 def test_dnn_full():
-    if cuda.device_properties(cuda.active_device_number())['major'] < 3:
-        raise SkipTest('Current GPU too old')
+    if not cuda.dnn.dnn_available():
+        raise SkipTest(cuda.dnn.dnn_available.msg)
     for t in _test_full(GpuDnnConv, mode=theano_mode.including("cudnn")):
         yield t
 
@@ -711,8 +711,8 @@ def test_gemm_subsample():
 
 
 def test_dnn_subsample():
-    if cuda.device_properties(cuda.active_device_number())['major'] < 3:
-        raise SkipTest('Current GPU too old')
+    if not cuda.dnn.dnn_available():
+        raise SkipTest(cuda.dnn.dnn_available.msg)
     for t in _test_subsample(GpuDnnConv, theano_mode.including('cudnn')):
         yield t
 
@@ -909,6 +909,10 @@ def conv_grad(mode, bs, ch, nf, rImg1, rImg2, rFlt1, rFlt2, subsample, op):
 
 
 def test_conv_grads():
+    if cuda.device_properties(cuda.active_device_number())['major'] < 3:
+        ops = [gemm_op]
+    else:
+        ops = [gemm_op, dnn_op]
     for mode in 'valid', 'full':
         for bs in [1, 5]:
             for ch in [4]:
@@ -918,7 +922,7 @@ def test_conv_grads():
                             for rFlt1 in [1, 2]:
                                 for rFlt2 in [1, 2]:
                                     for subsample in (1, 1), (1, 2), (2, 2):
-                                        for op in [gemm_op, dnn_op]:
+                                        for op in ops:
                                             yield (conv_grad, mode, bs, ch, nf,
                                                    rImg1, rImg2, rFlt1, rFlt2,
                                                    subsample, op)

theano/sandbox/cuda/tests/test_nnet.py

@@ -301,6 +301,9 @@ class test_SoftMax(unittest.TestCase):
         self._cmp(0, 10, f, f_gpu)
 
     def test_cudnn_softmax(self):
+        if not cuda.dnn.dnn_available():
+            raise SkipTest(cuda.dnn.dnn_available.msg)
+
         def cmp(n, m, f, f_gpu):
             data = numpy.arange(n * m, dtype='float32').reshape(n, m)
             gdata = numpy.asarray(data)[:, :, None, None]