add logs

paddle/fluid/operators/conv_cudnn_helper.h

@@ -467,6 +467,7 @@ struct SearchAlgorithm<cudnnConvolutionBwdFilterAlgoPerf_t> {
     algo_t algo;
     if (!exhaustive && !deterministic) {
 #if CUDNN_VERSION >= 7001
+      VLOG(3) << "=====Not exhaustive=====";
       using perf_t = cudnnConvolutionBwdFilterAlgoPerf_t;
       int perf_count;
       int best_algo_idx = 0;
@@ -493,6 +494,7 @@ struct SearchAlgorithm<cudnnConvolutionBwdFilterAlgoPerf_t> {
     } else if (deterministic) {
       return CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1;
     } else {
+      VLOG(3) << "=======exhaustive=======: " << exhaustive;
       auto& dev_ctx =
           ctx.template device_context<platform::CUDADeviceContext>();
       auto workspace_handle = dev_ctx.cudnn_workspace_handle();

paddle/fluid/operators/conv_cudnn_op.cu

@@ -336,6 +336,11 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
     int groups = ctx.Attr<int>("groups");
     bool exhaustive_search =
         FLAGS_cudnn_exhaustive_search || ctx.Attr<bool>("exhaustive_search");
+    VLOG(3) << "=====exhaustive_search====: " << exhaustive_search;
+    VLOG(3) << "====FLAGS_cudnn_exhaustive_search====: "
+            << FLAGS_cudnn_exhaustive_search;
+    VLOG(3) << "====Attr: exhaustive_search====: "
+            << ctx.Attr<bool>("exhaustive_search");
     bool deterministic = FLAGS_cudnn_deterministic;
     if (exhaustive_search && deterministic) {
       PADDLE_THROW(

python/paddle/fluid/layers/nn.py

@@ -1582,7 +1582,7 @@ def conv2d(input,
             'use_mkldnn': False,
             'fuse_relu_before_depthwise_conv': False,
             "padding_algorithm": padding_algorithm,
-            "data_format": data_format
+            "data_format": data_format,
         })
 
     if data_format == 'NCHW':