Patch for bwd data comments (#174)

* change function name and way to set input zero

* change enable if

example/17_convnd_bwd_data_xdl/convnd_bwd_data_xdl.cpp

@@ -83,7 +83,7 @@ using ReferenceConvBwdDataInstance =
                                                      OutElementOp,
                                                      NumDimSpatial>;
 
-void PrintUseMsg()
+void print_use_msg()
 {
     std::cout << "arg1: verification (0=no, 1=yes)\n"
               << "arg2: initialization (0=no init, 1=random value, 2= init to 1 )\n"
@@ -99,7 +99,7 @@ void PrintUseMsg()
               << " <right padding>, (ie RightPy, RightPx for 2D)\n"
               << std::endl;
 }
-ck::conv_util::ConvParams ParseConvParams(int num_dim_spatial, char* argv[])
+ck::conv_util::ConvParams parse_conv_params(int num_dim_spatial, char* argv[])
 {
     // (N, K, C) + num_dim_spatial * 6 (filter, input, strides, dilations, pad left, pad right)
     ck::conv_util::ConvParams params;
@@ -144,8 +144,8 @@ ck::conv_util::ConvParams ParseConvParams(int num_dim_spatial, char* argv[])
     return params;
 }
 
-HostTensorDescriptor GetInputHostTensorDescriptor(const std::vector<std::size_t>& dims,
-                                                  int num_dim_spatial = 2)
+HostTensorDescriptor get_input_host_tensor_descriptor(const std::vector<std::size_t>& dims,
+                                                      int num_dim_spatial = 2)
 {
     namespace tl = ck::tensor_layout::convolution;
 
@@ -165,8 +165,8 @@ HostTensorDescriptor GetInputHostTensorDescriptor(const std::vector<std::size_t>
     }
     }
 }
-HostTensorDescriptor GetFiltersHostTensorDescriptor(const std::vector<std::size_t>& dims,
-                                                    int num_dim_spatial = 2)
+HostTensorDescriptor get_filters_host_tensor_descriptor(const std::vector<std::size_t>& dims,
+                                                        int num_dim_spatial = 2)
 {
     namespace tl = ck::tensor_layout::convolution;
 
@@ -187,8 +187,8 @@ HostTensorDescriptor GetFiltersHostTensorDescriptor(const std::vector<std::size_
     }
 }
 
-HostTensorDescriptor GetOutputHostTensorDescriptor(const std::vector<std::size_t>& dims,
-                                                   int num_dim_spatial = 2)
+HostTensorDescriptor get_output_host_tensor_descriptor(const std::vector<std::size_t>& dims,
+                                                       int num_dim_spatial = 2)
 {
     namespace tl = ck::tensor_layout::convolution;
 
@@ -210,7 +210,7 @@ HostTensorDescriptor GetOutputHostTensorDescriptor(const std::vector<std::size_t
     }
 }
 
-DeviceConvBwdDataBasePtr GetConvInstance(int num_dim_spatial)
+DeviceConvBwdDataBasePtr get_conv_instance(int num_dim_spatial)
 {
     switch(num_dim_spatial)
     {
@@ -256,15 +256,15 @@ int main(int argc, char* argv[])
         int cmdline_nargs = conv_args + 5;
         if(cmdline_nargs != argc)
         {
-            PrintUseMsg();
+            print_use_msg();
             exit(1);
         }
 
-        params = ParseConvParams(num_dim_spatial, argv);
+        params = parse_conv_params(num_dim_spatial, argv);
     }
     else if(argc != 1)
     {
-        PrintUseMsg();
+        print_use_msg();
         exit(1);
     }
 
@@ -288,11 +288,13 @@ int main(int argc, char* argv[])
                        std::end(output_spatial_lengths));
 
     Tensor<InDataType> in_n_c_hi_wi_host_result(
-        GetInputHostTensorDescriptor(input_dims, num_dim_spatial));
+        get_input_host_tensor_descriptor(input_dims, num_dim_spatial));
     Tensor<InDataType> in_n_c_hi_wi_device_result(
-        GetInputHostTensorDescriptor(input_dims, num_dim_spatial));
-    Tensor<WeiDataType> wei_k_c_y_x(GetFiltersHostTensorDescriptor(filter_dims, num_dim_spatial));
-    Tensor<OutDataType> out_n_k_ho_wo(GetOutputHostTensorDescriptor(output_dims, num_dim_spatial));
+        get_input_host_tensor_descriptor(input_dims, num_dim_spatial));
+    Tensor<WeiDataType> wei_k_c_y_x(
+        get_filters_host_tensor_descriptor(filter_dims, num_dim_spatial));
+    Tensor<OutDataType> out_n_k_ho_wo(
+        get_output_host_tensor_descriptor(output_dims, num_dim_spatial));
 
     std::cout << "in_n_c_hi_wi: " << in_n_c_hi_wi_host_result.mDesc << std::endl;
     std::cout << "wei_k_c_y_x: " << wei_k_c_y_x.mDesc << std::endl;
@@ -318,11 +320,10 @@ int main(int argc, char* argv[])
     out_device_buf.ToDevice(out_n_k_ho_wo.mData.data());
     wei_device_buf.ToDevice(wei_k_c_y_x.mData.data());
     // reset input to zero
-    in_n_c_hi_wi_device_result.GenerateTensorValue(GeneratorTensor_1<InDataType>{0});
-    in_device_buf.ToDevice(in_n_c_hi_wi_device_result.mData.data());
+    in_device_buf.SetZero();
 
     // do GEMM
-    auto conv    = GetConvInstance(num_dim_spatial);
+    auto conv    = get_conv_instance(num_dim_spatial);
     auto invoker = conv->MakeInvokerPointer();
     auto argument =
         conv->MakeArgumentPointer(static_cast<InDataType*>(in_device_buf.GetDeviceBuffer()),

include/ck/tensor_operation/gpu/device/device_convnd_bwd_data_xdl_ndhwc_kzyxc_ndhwk.hpp

@@ -917,21 +917,21 @@ struct DeviceConvndBwdDataXdl_Input_N_Di_Hi_Wi_C_Weight_K_Z_Y_X_C_Output_N_Do_Ho
 
     } // function end
 
-    template <ck::index_t NDim, typename std::enable_if<NDim == 1, bool>::type = false>
+    template <ck::index_t NDim, typename ck::enable_if<NDim == 1, bool>::type = false>
     static auto GetABCGridDesc()
     {
         return MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<1>(
             1, 1, 1, {1}, {1}, {1}, {1}, {1}, {1}, {1}, {0});
     }
 
-    template <ck::index_t NDim, typename std::enable_if<NDim == 2, bool>::type = false>
+    template <ck::index_t NDim, typename ck::enable_if<NDim == 2, bool>::type = false>
     static auto GetABCGridDesc()
     {
         return MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<2>(
             1, 1, 1, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {0, 0});
     }
 
-    template <ck::index_t NDim, typename std::enable_if<NDim == 3, bool>::type = false>
+    template <ck::index_t NDim, typename ck::enable_if<NDim == 3, bool>::type = false>
     static auto GetABCGridDesc()
     {
         return MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N<3>(1,

library/include/ck/library/reference_tensor_operation/cpu/reference_conv_bwd_data.hpp

@@ -18,8 +18,8 @@ template <typename InDataType,
           typename InElementwiseOperation,
           typename WeiElementwiseOperation,
           typename OutElementwiseOperation,
-          ck::index_t NumDimSpatial                                                     = 2,
-          typename std::enable_if<NumDimSpatial >= 1 && NumDimSpatial <= 3, bool>::type = false>
+          ck::index_t NumDimSpatial                                                    = 2,
+          typename ck::enable_if<NumDimSpatial >= 1 && NumDimSpatial <= 3, bool>::type = false>
 struct ReferenceConvBwdData : public device::BaseOperator
 {
     // Argument

profiler/include/profile_convnd_bwd_data_impl.hpp

@@ -336,8 +336,7 @@ bool profile_convnd_bwd_data_impl(int do_verification,
     wei_device_buf.ToDevice(weights.mData.data());
 
     // reset input to zero
-    input_device_result.GenerateTensorValue(GeneratorTensor_1<InDataType>{0});
-    in_device_buf.ToDevice(input_device_result.mData.data());
+    in_device_buf.SetZero();
 
     if(do_verification)
     {