Merge pull request #5427 from notoraptor/investigation-5143

theano/gpuarray/dnn.py

@@ -720,6 +720,11 @@ 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' 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".')
         ctx_name = infer_context_name(img, topgrad, output)
         img = as_gpuarray_variable(img, ctx_name)
         topgrad = as_gpuarray_variable(topgrad, ctx_name)

theano/gpuarray/tests/test_dnn.py

@@ -973,7 +973,6 @@ def get_conv3d_test_cases():
                    [(8, 4, 20, 12, 15), (5, 4, 6, 12, 4), (2, 2, 2)],
                    [(8, 1, 20, 12, 15), (5, 1, 6, 12, 4), (3, 3, 3)],
                    [(8, 1, 20, 12, 15), (5, 1, 6, 12, 4), (3, 2, 1)],
-                   [(8, 1, 20, 12, 15), (5, 1, 6, 12, 4), (3, 2, 1)],
                    # Test with 1x1x1 filters
                    [(8, 1, 10, 10, 10), (10, 1, 1, 1, 1), (1, 1, 1)],
                    # Test with dimensions larger than 1024 (thread block dim)

theano/sandbox/cuda/dnn.py

@@ -789,6 +789,11 @@ class GpuDnnConv3dGradW(GpuDnnConvGradW):
                 DisconnectedType()(), d_alpha, d_beta)
 
     def make_node(self, img, topgrad, output, desc, alpha=None, beta=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".')
         img = as_cuda_ndarray_variable(img)
         topgrad = as_cuda_ndarray_variable(topgrad)
         output = as_cuda_ndarray_variable(output)

theano/sandbox/cuda/tests/test_dnn.py

@@ -1554,7 +1554,6 @@ def get_conv3d_test_cases():
                    [(8, 4, 20, 12, 15), (5, 4, 6, 12, 4), (2, 2, 2)],
                    [(8, 1, 20, 12, 15), (5, 1, 6, 12, 4), (3, 3, 3)],
                    [(8, 1, 20, 12, 15), (5, 1, 6, 12, 4), (3, 2, 1)],
-                   [(8, 1, 20, 12, 15), (5, 1, 6, 12, 4), (3, 2, 1)],
                    # Test with 1x1x1 filters
                    [(8, 1, 10, 10, 10), (10, 1, 1, 1, 1), (1, 1, 1)],
                    # Test with dimensions larger than 1024 (thread block dim)