Change default DnnConvGrad implementation

theano/sandbox/cuda/dnn.py

@@ -356,7 +356,7 @@ AddConfigVar('dnn.conv.workmem',
 AddConfigVar('dnn.conv.workmem_bwd',
              "Default value for the workmem attribute of cudnn gradient "
              "convolutions.",
-             EnumStr('deterministic', 'none', 'fft', 'guess'),
+             EnumStr('none', 'deterministic', 'fft', 'guess'),
              in_c_key=False)
 
 

theano/sandbox/cuda/dnn_conv_base.c

@@ -53,8 +53,8 @@ for (int i = 0; i < 5; i++)
 // implementations should be selected based on the size of the data.
 APPLY_SPECIFIC(previous_algo) = CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM;
 #if defined(CUDNN_VERSION) && CUDNN_VERSION >= 3000
-APPLY_SPECIFIC(previous_bwd_f_algo) = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1;
-APPLY_SPECIFIC(previous_bwd_d_algo) = CUDNN_CONVOLUTION_BWD_DATA_ALGO_1;
+APPLY_SPECIFIC(previous_bwd_f_algo) = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_0;
+APPLY_SPECIFIC(previous_bwd_d_algo) = CUDNN_CONVOLUTION_BWD_DATA_ALGO_0;
 #endif
 
 #section cleanup_code_struct

theano/sandbox/cuda/dnn_gi.c

@@ -147,7 +147,7 @@ APPLY_SPECIFIC(conv_gi)(CudaNdarray *kerns, CudaNdarray *output,
       if (stride_v != 1 || stride_h != 1 || input_h > 1024 ||
           input_w > 1024 || (filter_h == 1 && filter_w == 1))
       {
-        chosen_algo = CUDNN_CONVOLUTION_BWD_DATA_ALGO_1;
+        chosen_algo = CUDNN_CONVOLUTION_BWD_DATA_ALGO_0;
       }
     }
 

theano/sandbox/cuda/dnn_gw.c

@@ -147,7 +147,7 @@ APPLY_SPECIFIC(conv_gw)(CudaNdarray *input, CudaNdarray *output,
       if (stride_v != 1 || stride_h != 1 || input_h > 1024 ||
           input_w > 1024 || (filter_h == 1 && filter_w == 1))
       {
-        chosen_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1;
+        chosen_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_0;
       }
     }