Better handling for tests that should fail.

theano/gpuarray/tests/check_dnn_conv.py

@@ -348,7 +348,7 @@ class CuDNNV51ConvCaseGenerator(object):
 
     def _fwd_fft(self, ndim):
         inputs_sizes = [(10,) * ndim,
-                        (248, 5) + (2,) * (ndim - 2)]
+                        (240, 5) + (2,) * (ndim - 2)]
         filters_sizes = [tuple(range(9, 9 - ndim, -1))]
         subsamples = [(1,) * ndim]
         return ConvCaseGenerator(ndim=ndim,
@@ -357,7 +357,7 @@ class CuDNNV51ConvCaseGenerator(object):
                                  subsamples=subsamples,
                                  dilations=self._dilations(ndim))
 
-    def _fwd_fft_tiling(self, ndim):
+    def _fwd_fft_tiling(self, ndim, dtype, precision):
         if ndim == 2:
             filters_sizes = [(32, 5)]
         if ndim == 3:
@@ -395,8 +395,8 @@ class CuDNNV51ConvCaseGenerator(object):
     def _gi_fft(self, ndim):
         return self._fwd_fft(ndim)
 
-    def _gi_fft_tiling(self, ndim):
-        return self._fwd_fft_tiling(ndim)
+    def _gi_fft_tiling(self, ndim, dtype, precision):
+        return self._fwd_fft_tiling(ndim, dtype, precision)
 
     def _gi_winograd(self, ndim):
         return self._fwd_winograd(ndim)
@@ -406,29 +406,29 @@ class CuDNNV51ConvCaseGenerator(object):
 
     # Public interface.
 
-    def fwd(self, algo, ndim):
+    def fwd(self, algo, ndim, dtype, precision):
         if algo == self.FFT:
             return self._fwd_fft(ndim)
         if algo == self.FFT_TILING:
-            return self._fwd_fft_tiling(ndim)
+            return self._fwd_fft_tiling(ndim, dtype, precision)
         if algo == self.WINOGRAD:
             return self._fwd_winograd(ndim)
         if algo == self.WINOGRAD_NON_FUSED:
             return self._fwd_winograd_non_fused(ndim)
         return ConvCaseGenerator(ndim=ndim, dilations=self._dilations(ndim))
 
-    def gw(self, algo, ndim):
+    def gw(self, algo, ndim, dtype, precision):
         if algo == self.FFT:
             return self._gw_fft(ndim)
         if algo == self.WINOGRAD_NON_FUSED:
             return self._gw_winograd_non_fused(ndim)
         return ConvCaseGenerator(ndim=ndim, dilations=self._dilations(ndim))
 
-    def gi(self, algo, ndim):
+    def gi(self, algo, ndim, dtype, precision):
         if algo == self.FFT:
             return self._gi_fft(ndim)
         if algo == self.FFT_TILING:
-            return self._gi_fft_tiling(ndim)
+            return self._gi_fft_tiling(ndim, dtype, precision)
         if algo == self.WINOGRAD:
             return self._gi_winograd(ndim)
         if algo == self.WINOGRAD_NON_FUSED:
@@ -441,22 +441,25 @@ class CuDNNV6ConvCaseGenerator(CuDNNV51ConvCaseGenerator):
         # All dilations allowed.
         return ConvCaseGenerator(ndim=ndim)
 
-    def _fwd_fft_tiling(self, ndim):
+    def _fwd_fft_tiling(self, ndim, dtype, precision):
         if ndim == 2:
             subsamples = [(1, 1)]
             # wDesc's filter height must be greater than convDesc's zero-padding height
             # wDesc's filter width must be greater than convDesc's zero-padding width
+            generators = []
+            if (dtype, precision) != ('float64', 'float64'):
+                # Filter sizes with every dimension != 1 is not supported for DOUBLE_CONFIG.
                 filters_sizes = [(32, 5), (10, 10)]
                 borders = [(1, 1), (6, 4)]
-            generator1 = ConvCaseGenerator(ndim=ndim, dilations=self._dilations(ndim), subsamples=subsamples,
-                                           filters_sizes=filters_sizes, borders=borders)
+                generators += [ConvCaseGenerator(ndim=ndim, dilations=self._dilations(ndim), subsamples=subsamples,
+                                                 filters_sizes=filters_sizes, borders=borders)]
             filters_sizes = [(256, 1), (5, 1)]
             borders = [(1, 0), (2, 0)]
-            generator2 = ConvCaseGenerator(ndim=ndim, dilations=self._dilations(ndim), subsamples=subsamples,
-                                           filters_sizes=filters_sizes, borders=borders)
-            return ConvCaseGeneratorChain(generator1, generator2)
+            generators += [ConvCaseGenerator(ndim=ndim, dilations=self._dilations(ndim), subsamples=subsamples,
+                                             filters_sizes=filters_sizes, borders=borders)]
+            return ConvCaseGeneratorChain(*generators)
         if ndim == 3:
-            return super(CuDNNV6ConvCaseGenerator, self)._fwd_fft_tiling(ndim)
+            return super(CuDNNV6ConvCaseGenerator, self)._fwd_fft_tiling(ndim, dtype, precision)
 
     def _gw_none(self, ndim):
         return self._fwd_none(ndim)
@@ -476,22 +479,22 @@ class CuDNNV6ConvCaseGenerator(CuDNNV51ConvCaseGenerator):
     def _gi_none(self, ndim):
         return self._fwd_none(ndim)
 
-    def fwd(self, algo, ndim):
+    def fwd(self, algo, ndim, dtype, precision):
         if algo == self.NONE:
             return self._fwd_none(ndim)
-        return super(CuDNNV6ConvCaseGenerator, self).fwd(algo, ndim)
+        return super(CuDNNV6ConvCaseGenerator, self).fwd(algo, ndim, dtype, precision)
 
-    def gw(self, algo, ndim):
+    def gw(self, algo, ndim, dtype, precision):
         if algo == self.NONE:
             return self._gw_none(ndim)
         if algo == self.FFT_TILING:
             return self._gw_fft_tiling(ndim)
-        return super(CuDNNV6ConvCaseGenerator, self).gw(algo, ndim)
+        return super(CuDNNV6ConvCaseGenerator, self).gw(algo, ndim, dtype, precision)
 
-    def gi(self, algo, ndim):
+    def gi(self, algo, ndim, dtype, precision):
         if algo == self.NONE:
             return self._gi_none(ndim)
-        return super(CuDNNV6ConvCaseGenerator, self).gi(algo, ndim)
+        return super(CuDNNV6ConvCaseGenerator, self).gi(algo, ndim, dtype, precision)
 
 
 cudnn_conv_case_generator = CuDNNV51ConvCaseGenerator() if cudnn.version < 6 else CuDNNV6ConvCaseGenerator()
@@ -692,15 +695,24 @@ class BaseTestDnnConv(object):
         else:
             utt.assert_allclose(alpha * res_ref + beta * filters_val, res, rtol=rtol)
 
-    def should_fail(self, callable, *args):
+    def should_fail(self, function, *args):
         try:
             print('(should fail)', file=sys.stderr, end=' ')
-            callable(*args)
+            function(*args)
         except Exception:
             pass
         else:
             raise AssertionError('Should fail', callable.__name__, *args)
 
+    def should_fail_fwd(self, *args):
+        self.should_fail(self.run_conv_fwd, *args)
+
+    def should_fail_gradinput(self, *args):
+        self.should_fail(self.run_conv_gradinput, *args)
+
+    def should_fail_gradweight(self, *args):
+        self.should_fail(self.run_conv_gradweight, *args)
+
     def get_expected_tcount(self):
         """
         Utility function to get expected test count
@@ -717,7 +729,7 @@ class BaseTestDnnConv(object):
             algos = (algo for algo in self.fwd_algorithms
                      if cudnn.fwd_algo_supports_dtype_config(algo, dtype, precision, self.ndim))
             for algo in algos:
-                for parameters in cudnn_conv_case_generator.fwd(algo, self.ndim).get_cases():
+                for parameters in cudnn_conv_case_generator.fwd(algo, self.ndim, dtype, precision).get_cases():
                     yield (self.run_conv_fwd, algo, dtype, precision, parameters)
             for algo in SUPPORTED_DNN_CONV_ALGO_RUNTIME:
                 for parameters in self.get_cases():
@@ -725,7 +737,7 @@ class BaseTestDnnConv(object):
         for dnn_case in self.special_cases:
             if dnn_case.is_fwd():
                 if dnn_case.should_fail:
-                    yield (self.should_fail, self.run_conv_fwd,) + dnn_case.get_case()
+                    yield (self.should_fail_fwd,) + dnn_case.get_case()
                 else:
                     yield (self.run_conv_fwd,) + dnn_case.get_case()
 
@@ -734,7 +746,7 @@ class BaseTestDnnConv(object):
             algos = (algo for algo in self.bwd_data_algorithms
                      if cudnn.bwd_data_algo_supports_dtype_config(algo, dtype, precision, self.ndim))
             for algo in algos:
-                for parameters in cudnn_conv_case_generator.gi(algo, self.ndim).get_cases():
+                for parameters in cudnn_conv_case_generator.gi(algo, self.ndim, dtype, precision).get_cases():
                     yield (self.run_conv_gradinput, algo, dtype, precision, parameters)
             for algo in SUPPORTED_DNN_CONV_ALGO_RUNTIME:
                 for parameters in self.get_cases():
@@ -742,7 +754,7 @@ class BaseTestDnnConv(object):
         for dnn_case in self.special_cases:
             if dnn_case.is_bwd_data():
                 if dnn_case.should_fail:
-                    yield (self.should_fail, self.run_conv_gradinput,) + dnn_case.get_case()
+                    yield (self.should_fail_gradinput,) + dnn_case.get_case()
                 else:
                     yield (self.run_conv_gradinput,) + dnn_case.get_case()
 
@@ -751,7 +763,7 @@ class BaseTestDnnConv(object):
             algos = (algo for algo in self.bwd_filter_algorithms
                      if cudnn.bwd_filter_algo_supports_dtype_config(algo, dtype, precision, self.ndim))
             for algo in algos:
-                for parameters in cudnn_conv_case_generator.gw(algo, self.ndim).get_cases():
+                for parameters in cudnn_conv_case_generator.gw(algo, self.ndim, dtype, precision).get_cases():
                     yield (self.run_conv_gradweight, algo, dtype, precision, parameters)
             for algo in SUPPORTED_DNN_CONV_ALGO_RUNTIME:
                 for parameters in self.get_cases():
@@ -759,7 +771,7 @@ class BaseTestDnnConv(object):
         for dnn_case in self.special_cases:
             if dnn_case.is_bwd_filter():
                 if dnn_case.should_fail:
-                    yield (self.should_fail, self.run_conv_gradweight,) + dnn_case.get_case()
+                    yield (self.should_fail_gradweight,) + dnn_case.get_case()
                 else:
                     yield (self.run_conv_gradweight,) + dnn_case.get_case()
 

theano/gpuarray/tests/run_dnn_conv.py

@@ -9,6 +9,7 @@ import sys
 
 import theano
 from theano.configdefaults import SUPPORTED_DNN_CONV_ALGO_RUNTIME
+from theano.tensor.nnet.abstract_conv import get_conv_output_shape
 from theano.gpuarray.cudnn_defs import (HALF, FLOAT, DOUBLE,
                                         TRUE_HALF_CONFIG, PSEUDO_HALF_CONFIG, FLOAT_CONFIG, DOUBLE_CONFIG)
 from theano.gpuarray.tests.check_dnn_conv import (cudnn, TestDnnConv2D, TestDnnConv3D, CheckDnn)
@@ -144,4 +145,6 @@ if test == BWD_FILTER:
     tests.run_conv_gradweight(algo, dtype, precision, parameters)
 if test == BWD_DATA:
     tests.run_conv_gradinput(algo, dtype, precision, parameters)
+print('Output shape:', get_conv_output_shape(args.input_shape, args.filter_shape, args.border_mode,
+                                             args.subsample, args.dilation))
 print('... OK')