Print the warning for conv3d backward operation only if subsample is not (1, 1, 1).

theano/gpuarray/dnn.py

@@ -720,11 +720,12 @@ class GpuDnnConvGradW(DnnBase):
         return defs
 
     def make_node(self, img, topgrad, output, desc, alpha=None, beta=None):
-        if img.type.ndim == 5 and self.algo != 'none':
-            warnings.warn('cuDNN backward filter convolution computation for 3D convolutions '
-                          'may produce bad results with certain algorithms depending on the compute capability '
-                          'of your GPU. If you encounter problems, consider setting the theano flag '
-                          '"dnn.conv.algo_bwd_filter" to "none" (dnn.conv.algo_bwd_filter=none)')
+        if img.type.ndim == 5 and self.algo != 'none' and desc.owner.op.subsample != (1, 1, 1):
+            warnings.warn('cuDNN backward filter operation for 3D convolutions may produce bad results '
+                          'with certain cuDNN algorithms depending on the compute capability of your GPU '
+                          'if subsample is not (1, 1, 1). If you encounter problems, consider '
+                          'setting the theano flag "dnn.conv.algo_bwd_filter" to "none" '
+                          '(dnn.conv.algo_bwd_filter=none)')
         ctx_name = infer_context_name(img, topgrad, output)
         img = as_gpuarray_variable(img, ctx_name)
         topgrad = as_gpuarray_variable(topgrad, ctx_name)

theano/sandbox/cuda/dnn.py

@@ -789,11 +789,12 @@ class GpuDnnConv3dGradW(GpuDnnConvGradW):
                 DisconnectedType()(), d_alpha, d_beta)
 
     def make_node(self, img, topgrad, output, desc, alpha=None, beta=None):
-        if self.algo != 'none':
-            warnings.warn('cuDNN backward filter convolution computation for 3D convolutions '
-                          'may produce bad results with certain algorithms depending on the compute capability '
-                          'of your GPU. If you encounter problems, consider setting the theano flag '
-                          '"dnn.conv.algo_bwd_filter" to "none" (dnn.conv.algo_bwd_filter=none)')
+        if self.algo != 'none' and desc.owner.op.subsample != (1, 1, 1):
+            warnings.warn('cuDNN backward filter operation for 3D convolutions may produce bad results '
+                          'with certain cuDNN algorithms depending on the compute capability of your GPU '
+                          'if subsample is not (1, 1, 1). If you encounter problems, consider '
+                          'setting the theano flag "dnn.conv.algo_bwd_filter" to "none" '
+                          '(dnn.conv.algo_bwd_filter=none)')
         img = as_cuda_ndarray_variable(img)
         topgrad = as_cuda_ndarray_variable(topgrad)
         output = as_cuda_ndarray_variable(output)