follow comments and refine python doc

paddle/operators/conv_op.cc

@@ -284,9 +284,7 @@ void ConvOpGrad::InferShape(framework::InferShapeContext* ctx) const {
 framework::OpKernelType ConvOpGrad::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
   bool use_cudnn = ctx.Attr<bool>("use_cudnn");
-  if (paddle::platform::is_cpu_place(ctx.GetPlace())) {
-    use_cudnn = false;
-  }
+  use_cudnn &= platform::is_gpu_place(ctx.GetPlace());
   framework::LibraryType library_;
   if (use_cudnn) {
     library_ = framework::LibraryType::kCUDNN;

paddle/operators/conv_transpose_op.cc

@@ -264,9 +264,7 @@ void ConvTransposeOpGrad::InferShape(framework::InferShapeContext* ctx) const {
 framework::OpKernelType ConvTransposeOpGrad::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
   bool use_cudnn = ctx.Attr<bool>("use_cudnn");
-  if (paddle::platform::is_cpu_place(ctx.GetPlace())) {
-    use_cudnn = false;
-  }
+  use_cudnn &= platform::is_gpu_place(ctx.GetPlace());
   framework::LibraryType library_;
   if (use_cudnn) {
     library_ = framework::LibraryType::kCUDNN;

paddle/operators/pool_op.cc

@@ -89,9 +89,7 @@ void PoolOpGrad::InferShape(framework::InferShapeContext *ctx) const {
 framework::OpKernelType PoolOpGrad::GetExpectedKernelType(
     const framework::ExecutionContext &ctx) const {
   bool use_cudnn = ctx.Attr<bool>("use_cudnn");
-  if (paddle::platform::is_cpu_place(ctx.GetPlace())) {
-    use_cudnn = false;
-  }
+  use_cudnn &= platform::is_gpu_place(ctx.GetPlace());
   framework::LibraryType library_;
   if (use_cudnn) {
     library_ = framework::LibraryType::kCUDNN;

python/paddle/v2/fluid/layers/nn.py

@@ -724,6 +724,8 @@ def conv2d(input,
             connected to the second half of the input channels. Default: groups=1
         param_attr(ParamAttr): The parameters to the Conv2d Layer. Default: None
         bias_attr(ParamAttr): Bias parameter for the Conv2d layer. Default: None
+        use_cudnn(bool): Use cudnn kernel or not, it is valid only when the cudnn
+            library is installed. Default: True
         act(str): Activation type. Default: None
 
     Returns:
@@ -1115,8 +1117,8 @@ def conv2d_transpose(input,
             contain two integers, (dilation_H, dilation_W). Otherwise, the
             dilation_H = dilation_W = dilation.
         param_attr: Parameter Attribute.
-        main_program(Program): the main program
-        startup_program(Program): the startup program
+        use_cudnn(bool): Use cudnn kernel or not, it is valid only when the cudnn
+            library is installed. Default: True
 
     Returns:
         Variable: Output image.