fix by comments

composable_kernel/include/problem_transform/transform_backward_weight_convolution_into_gemm_v4r4r2_nchw_kcyx_nkhw.hpp

@@ -8,8 +8,8 @@
 namespace ck {
 
 // GemmM = K
-// GemmN = N * Ho * Wo
-// GemmK = C * Y * X
+// GemmK = N * Ho * Wo
+// GemmN = C * Y * X
 template <typename... Wei,
           typename... In,
           typename... Out,

host/driver_offline/include/device_convolution_backward_weight_implicit_gemm_v4r4r2_xdlops_nchw_kcyx_nkhw.hpp

@@ -48,7 +48,7 @@ void device_convolution_backward_weight_implicit_gemm_v4r4r2_xdlops_nchw_kcyx_nk
     const auto out_n_k_ho_wo_desc = make_naive_tensor_descriptor_packed(out_n_k_ho_wo_lengths);
 
 #if 1
-    // [M, N, K0, K1] = [256, 128, 4, 8] for fp16
+    // [M, N, K0, K1] = [128, 128, 4, 8] for fp16
     constexpr index_t BlockSize = 256;
 
     constexpr index_t GemmMPerBlock = 128;

host/driver_offline/src/conv_wrw_driver_offline.cpp

@@ -87,13 +87,13 @@ int main(int argc, char* argv[])
     const bool do_log                 = std::stoi(argv[5]);
     const int nrepeat                 = std::stoi(argv[6]);
 
-    constexpr index_t N  = 128;
-    constexpr index_t C  = 192;
-    constexpr index_t Hi = 71;
-    constexpr index_t Wi = 71;
-    constexpr index_t K  = 256;
-    constexpr index_t Y  = 3;
-    constexpr index_t X  = 3;
+    constexpr index_t N  = Number<128>;
+    constexpr index_t C  = Number<128>;
+    constexpr index_t Hi = Number<14>;
+    constexpr index_t Wi = Number<14>;
+    constexpr index_t K  = Number<256>;
+    constexpr index_t Y  = Number<3>;
+    constexpr index_t X  = Number<3>;
 
     const index_t conv_stride_h   = 2;
     const index_t conv_stride_w   = 2;
@@ -200,8 +200,8 @@ int main(int argc, char* argv[])
         out.GenerateTensorValue(GeneratorTensor_2{-5, 5}, num_thread);
         break;
     case 5:
-        in.GenerateTensorValue(GeneratorTensor_3<float>{0.0, 0.01}, num_thread);
-        out.GenerateTensorValue(GeneratorTensor_3<float>{0.0, 0.01}, num_thread);
+        in.GenerateTensorValue(GeneratorTensor_3<float>{-0.01, 0.01}, num_thread);
+        out.GenerateTensorValue(GeneratorTensor_3<float>{-0.01, 0.01}, num_thread);
         break;
     default:
         in.GenerateTensorValue(GeneratorTensor_2{1, 5}, num_thread);