Use macro to eliminate redundant code

profiler/src/profile_batched_gemm.cpp

@@ -26,12 +26,15 @@ enum struct GemmDataType
     INT8_INT8_INT8, // 3
 };
 
+#define OP_NAME "batched_gemm"
+#define OP_DESC "Batched GEMM"
+
 int profile_batched_gemm(int argc, char* argv[])
 {
     if(argc != 18)
     {
         // clang-format off
-        printf("arg1: tensor operation (batched_gemm: Batched GEMM)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16, 2: bf16, 3: int8)\n");
         printf("arg3: matrix layout (0: A[g, m, k] * B[g, k, n] = C[g, m, n];\n");
         printf("                     1: A[g, m, k] * B[g, n, k] = C[g, m, n];\n");
@@ -197,4 +200,4 @@ int profile_batched_gemm(int argc, char* argv[])
     }
 }
 
-REGISTER_PROFILER_OPERATION("batched_gemm", "Batched GEMM", profile_batched_gemm);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_batched_gemm);

profiler/src/profile_batched_gemm_add_relu_gemm_add.cpp

@@ -15,6 +15,9 @@ using F32 = float;
 using Row = ck::tensor_layout::gemm::RowMajor;
 using Col = ck::tensor_layout::gemm::ColumnMajor;
 
+#define OP_NAME "batched_gemm_add_relu_gemm_add"
+#define OP_DESC "Batched GEMM+Add+Relu+GEMM+Add"
+
 int profile_batched_gemm_add_relu_gemm_add(int argc, char* argv[])
 {
     enum struct GemmMatrixLayout
@@ -110,8 +113,7 @@ int profile_batched_gemm_add_relu_gemm_add(int argc, char* argv[])
     }
     else
     {
-        printf("arg1: tensor operation (batched_gemm_add_relu_gemm_add: "
-               "Batched GEMM+Add+Relu+GEMM+Add)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (1: fp16)\n");
         printf("arg3: matrix layout (0: Relu(A0[m, k] * B0[n, k] + D0[m, n]) * B1[n, o] + D1[m, o] "
                "= E1[m, o]; 1: Relu(A0[m, k] * B0[n, k] + D0[m, n]) * B1[o, n] + D1[m, o] = "
@@ -209,6 +211,4 @@ int profile_batched_gemm_add_relu_gemm_add(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("batched_gemm_add_relu_gemm_add",
-                            "Batched GEMM+Add+Relu+GEMM+Add",
-                            profile_batched_gemm_add_relu_gemm_add);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_batched_gemm_add_relu_gemm_add);

profiler/src/profile_batched_gemm_gemm.cpp

@@ -15,6 +15,9 @@ using F32 = float;
 using Row = ck::tensor_layout::gemm::RowMajor;
 using Col = ck::tensor_layout::gemm::ColumnMajor;
 
+#define OP_NAME "batched_gemm_gemm"
+#define OP_DESC "Batched GEMM+GEMM"
+
 int profile_batched_gemm_gemm(int argc, char* argv[])
 {
     enum struct GemmMatrixLayout
@@ -102,7 +105,7 @@ int profile_batched_gemm_gemm(int argc, char* argv[])
     }
     else
     {
-        printf("arg1: tensor operation (batched_gemm_gemm: Batched GEMM+GEMM)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (1: fp16)\n");
         printf("arg3: matrix layout (0: Relu(A0[m, k] * B0[n, k] + D0[m, n]) * B1[n, o] + D1[m, o] "
                "= E1[m, o];  1: Relu(A0[m, k] * B0[n, k] + D0[m, n]) * B1[o, n] + D1[m, o] = E1[m, "
@@ -181,4 +184,4 @@ int profile_batched_gemm_gemm(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("batched_gemm_gemm", "Batched GEMM+GEMM", profile_batched_gemm_gemm);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_batched_gemm_gemm);

profiler/src/profile_batched_gemm_reduce.cpp

@@ -9,6 +9,9 @@
 #include "profiler/profile_batched_gemm_reduce_impl.hpp"
 #include "profiler_operation_registry.hpp"
 
+#define OP_NAME "batched_gemm_reduce"
+#define OP_DESC "Batched GEMM+Reduce"
+
 int profile_batched_gemm_reduce(int argc, char* argv[])
 {
     enum struct GemmMatrixLayout
@@ -27,7 +30,7 @@ int profile_batched_gemm_reduce(int argc, char* argv[])
 
     if(argc != 15)
     {
-        printf("arg1: tensor operation (batched_gemm_reduce: Batched GEMM+Reduce)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16)\n");
         printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
         printf("                     1: A[m, k] * B[n, k] = C[m, n];\n");
@@ -153,6 +156,4 @@ int profile_batched_gemm_reduce(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("batched_gemm_reduce",
-                            "Batched GEMM+Reduce",
-                            profile_batched_gemm_reduce);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_batched_gemm_reduce);

profiler/src/profile_conv_bwd_data.cpp

@@ -25,10 +25,13 @@ enum struct ConvDataType
     INT8_INT8_INT8, // 3
 };
 
+#define OP_NAME "conv_bwd_data"
+#define OP_DESC "Convolution Backward Data"
+
 static void print_helper_msg()
 {
     std::cout
-        << "arg1: tensor operation (conv_bwd_data: Convolution Backward Data)\n"
+        << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
         << "arg2: data type (0: Input fp32, Weight fp32, Output fp32\n"
         << "                 1: Input fp16, Weight fp16, Output fp16\n"
         << "                 2: Input bf16, Weight bf16, Output bf16\n"
@@ -184,4 +187,4 @@ int profile_conv_bwd_data(int argc, char* argv[])
     return 1;
 }
 
-REGISTER_PROFILER_OPERATION("conv_bwd_data", "Convolution Backward Data", profile_conv_bwd_data);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_conv_bwd_data);

profiler/src/profile_conv_fwd.cpp

@@ -25,11 +25,14 @@ enum struct ConvDataType
     INT8_INT8_INT8, // 3
 };
 
+#define OP_NAME "conv_fwd"
+#define OP_DESC "Convolution Forward"
+
 static void print_helper_msg()
 {
     std::cout
         // clang-format-off
-        << "arg1: tensor operation (conv_fwd: Convolution Forward)\n"
+        << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
         << "arg2: data type (0: Input fp32, Weight fp32, Output fp32\n"
         << "                 1: Input fp16, Weight fp16, Output fp16\n"
         << "                 2: Input bf16, Weight bf16, Output bf16\n"
@@ -186,4 +189,4 @@ int profile_conv_fwd(int argc, char* argv[])
     return 1;
 }
 
-REGISTER_PROFILER_OPERATION("conv_fwd", "Convolution Forward", profile_conv_fwd);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_conv_fwd);

profiler/src/profile_conv_fwd_bias_relu.cpp

@@ -33,11 +33,14 @@ enum struct ConvOutputLayout
     NHWK, // 1
 };
 
+#define OP_NAME "conv_fwd_bias_relu"
+#define OP_DESC "Convolution Forward+Bias+ReLU"
+
 int profile_conv_fwd_bias_relu(int argc, char* argv[])
 {
     if(argc != 25)
     {
-        printf("arg1: tensor operation (conv_fwd_bias_relu: Convolution Forward+Bias+ReLU)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16)\n");
         printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
         printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
@@ -116,6 +119,4 @@ int profile_conv_fwd_bias_relu(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("conv_fwd_bias_relu",
-                            "Convolution Forward+Bias+ReLU",
-                            profile_conv_fwd_bias_relu);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_conv_fwd_bias_relu);

profiler/src/profile_conv_fwd_bias_relu_add.cpp

@@ -33,12 +33,14 @@ enum struct ConvOutputLayout
     NHWK, // 1
 };
 
+#define OP_NAME "conv_fwd_bias_relu_add"
+#define OP_DESC "Convolution Forward+Bias+ReLU+Add"
+
 int profile_conv_fwd_bias_relu_add(int argc, char* argv[])
 {
     if(argc != 25)
     {
-        printf(
-            "arg1: tensor operation (conv_fwd_bias_relu_add: Convolution Forward+Bias+ReLU+Add)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16)\n");
         printf("arg3: input tensor layout (0: NCHW; 1: NHWC)\n");
         printf("arg4: weight tensor layout (0: KCYX; 1: KYXC)\n");
@@ -117,6 +119,4 @@ int profile_conv_fwd_bias_relu_add(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("conv_fwd_bias_relu_add",
-                            "Convolution Forward+Bias+ReLU+Add",
-                            profile_conv_fwd_bias_relu_add);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_conv_fwd_bias_relu_add);

profiler/src/profile_gemm.cpp

@@ -25,9 +25,12 @@ enum struct GemmDataType
     INT8_INT8_INT8, // 3
 };
 
+#define OP_NAME "gemm"
+#define OP_DESC "GEMM"
+
 static void print_helper_msg()
 {
-    std::cout << "arg1: tensor operation (gemm: GEMM)\n"
+    std::cout << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
               << "arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n"
               << "arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n"
               << "                     1: A[m, k] * B[n, k] = C[m, n];\n"
@@ -186,4 +189,4 @@ int profile_gemm(int argc, char* argv[])
     }
 }
 
-REGISTER_PROFILER_OPERATION("gemm", "GEMM", profile_gemm);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm);

profiler/src/profile_gemm_add_add_fastgelu.cpp

@@ -9,6 +9,9 @@
 #include "profiler/profile_gemm_add_add_fastgelu_impl.hpp"
 #include "profiler_operation_registry.hpp"
 
+#define OP_NAME "gemm_add_add_fastgelu"
+#define OP_DESC "GEMM+Add+Add+FastGeLU"
+
 int profile_gemm_add_add_fastgelu(int argc, char* argv[])
 {
     enum struct MatrixLayout
@@ -30,7 +33,7 @@ int profile_gemm_add_add_fastgelu(int argc, char* argv[])
     if(argc != 16)
     {
         // clang-format off
-        printf("arg1: tensor operation (gemm_add_add_fastgelu: GEMM+Add+Add+FastGeLU)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
         printf("arg3: matrix layout (0: E[m, n] = FastGeLU(A[m, k] * B[k, n] + D0[m, n] + D1[m, n]);\n");
         printf("                     1: E[m, n] = FastGeLU(A[m, k] * B[n, k] + D0[m, n] + D1[m, n]);\n");
@@ -152,6 +155,4 @@ int profile_gemm_add_add_fastgelu(int argc, char* argv[])
     }
 }
 
-REGISTER_PROFILER_OPERATION("gemm_add_add_fastgelu",
-                            "GEMM+Add+Add+FastGeLU",
-                            profile_gemm_add_add_fastgelu);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_add_add_fastgelu);

profiler/src/profile_gemm_bias_add_reduce.cpp

@@ -9,6 +9,9 @@
 #include "profiler/profile_gemm_bias_add_reduce_impl.hpp"
 #include "profiler_operation_registry.hpp"
 
+#define OP_NAME "gemm_bias_add_reduce"
+#define OP_DESC "GEMM+Bias+Add+Reduce"
+
 int profile_gemm_bias_add_reduce(int argc, char* argv[])
 {
     enum struct GemmMatrixLayout
@@ -27,7 +30,7 @@ int profile_gemm_bias_add_reduce(int argc, char* argv[])
 
     if(!(argc == 14 || argc == 15))
     {
-        printf("arg1: tensor operation (gemm_bias_add_reduce: GEMM+Bias+Add+Reduce)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16)\n");
         printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
         printf("                     1: A[m, k] * B[n, k] = C[m, n];\n");
@@ -161,6 +164,4 @@ int profile_gemm_bias_add_reduce(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("gemm_bias_add_reduce",
-                            "GEMM+Bias+Add+Reduce",
-                            profile_gemm_bias_add_reduce);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_bias_add_reduce);

profiler/src/profile_gemm_bilinear.cpp

@@ -9,6 +9,9 @@
 #include "profiler/profile_gemm_bilinear_impl.hpp"
 #include "profiler_operation_registry.hpp"
 
+#define OP_NAME "gemm_bilinear"
+#define OP_DESC "GEMM+Bilinear"
+
 int profile_gemm_bilinear(int argc, char* argv[])
 {
     enum struct MatrixLayout
@@ -30,7 +33,7 @@ int profile_gemm_bilinear(int argc, char* argv[])
     if(argc != 17)
     {
         // clang-format off
-        printf("arg1: tensor operation (gemm_bilinear: GEMM+Bilinear)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
         printf("arg3: matrix layout (0: E[m, n] = alpha * A[m, k] * B[k, n] + beta * D[m, n];\n");
         printf("                     1: E[m, n] = alpha * A[m, k] * B[n, k] + beta * D[m, n];\n");
@@ -146,4 +149,4 @@ int profile_gemm_bilinear(int argc, char* argv[])
     }
 }
 
-REGISTER_PROFILER_OPERATION("gemm_bilinear", "GEMM+Bilinear", profile_gemm_bilinear);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_bilinear);

profiler/src/profile_gemm_reduce.cpp

@@ -9,6 +9,9 @@
 #include "profiler/profile_gemm_reduce_impl.hpp"
 #include "profiler_operation_registry.hpp"
 
+#define OP_NAME "gemm_reduce"
+#define OP_DESC "GEMM+Reduce"
+
 int profile_gemm_reduce(int argc, char* argv[])
 {
     enum struct GemmMatrixLayout
@@ -27,7 +30,7 @@ int profile_gemm_reduce(int argc, char* argv[])
 
     if(!(argc == 14 || argc == 15))
     {
-        printf("arg1: tensor operation (gemm_reduce: GEMM+Reduce)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16)\n");
         printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
         printf("                     1: A[m, k] * B[n, k] = C[m, n];\n");
@@ -148,4 +151,4 @@ int profile_gemm_reduce(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("gemm_reduce", "GEMM+Reduce", profile_gemm_reduce);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_reduce);

profiler/src/profile_gemm_splitk.cpp

@@ -25,11 +25,14 @@ enum struct GemmDataType
     INT8_INT8_INT8, // 3
 };
 
+#define OP_NAME "gemm_splitk"
+#define OP_DESC "Split-K GEMM"
+
 int profile_gemm_splitk(int argc, char* argv[])
 {
     if(argc != 15)
     {
-        printf("arg1: tensor operation (gemm_splitk: Split-K GEMM)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
         printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
         printf("                     1: A[m, k] * B[n, k] = C[m, n];\n");
@@ -148,4 +151,4 @@ int profile_gemm_splitk(int argc, char* argv[])
     }
 }
 
-REGISTER_PROFILER_OPERATION("gemm_splitk", "Split-K GEMM", profile_gemm_splitk);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_gemm_splitk);

profiler/src/profile_grouped_conv_bwd_weight.cpp

@@ -24,23 +24,25 @@ enum struct ConvDataType
     BF16_F32_BF16, // 2
 };
 
+#define OP_NAME "grouped_conv_bwd_weight"
+#define OP_DESC "Grouped Convolution Backward Weight"
+
 static void print_helper_msg()
 {
-    std::cout
-        << "arg1: tensor operation (grouped_conv_bwd_weight: Grouped Convolution Backward Weight\n"
-        << "arg2: data type (0: Input fp32, Weight fp32, Output fp32\n"
-        << "                 1: Input fp16, Weight fp16, Output fp16\n"
-        << "                 2: Input bf16, Weight fp32, Output bf16)\n"
-        << "arg3: tensor layout (0: Input[G, N, C, Hi, Wi], Weight[G, K, C, Y, X], Output[G, "
-           "N, K, Ho, Wo]\n"
-        << "                     1: Input[G, N, Hi, Wi, C], Weight[G, K, Y, X, C], Output[G, "
-           "N, Ho, Wo, K]\n"
-        << "arg4: verification (0: no, 1: yes)\n"
-        << "arg5: initialization (0: no init, 1: integer value, 2: decimal value)\n"
-        << "arg6: print tensor value (0: no; 1: yes)\n"
-        << "arg7: time kernel (0: no, 1: yes)\n"
-        << ck::utils::conv::get_conv_param_parser_helper_msg() << " SplitK\n"
-        << std::endl;
+    std::cout << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
+              << "arg2: data type (0: Input fp32, Weight fp32, Output fp32\n"
+              << "                 1: Input fp16, Weight fp16, Output fp16\n"
+              << "                 2: Input bf16, Weight fp32, Output bf16)\n"
+              << "arg3: tensor layout (0: Input[G, N, C, Hi, Wi], Weight[G, K, C, Y, X], Output[G, "
+                 "N, K, Ho, Wo]\n"
+              << "                     1: Input[G, N, Hi, Wi, C], Weight[G, K, Y, X, C], Output[G, "
+                 "N, Ho, Wo, K]\n"
+              << "arg4: verification (0: no, 1: yes)\n"
+              << "arg5: initialization (0: no init, 1: integer value, 2: decimal value)\n"
+              << "arg6: print tensor value (0: no; 1: yes)\n"
+              << "arg7: time kernel (0: no, 1: yes)\n"
+              << ck::utils::conv::get_conv_param_parser_helper_msg() << " SplitK\n"
+              << std::endl;
 }
 
 } // namespace
@@ -177,6 +179,4 @@ int profile_grouped_conv_bwd_weight(int argc, char* argv[])
     return 1;
 }
 
-REGISTER_PROFILER_OPERATION("grouped_conv_bwd_weight",
-                            "Grouped Convolution Backward Weight",
-                            profile_grouped_conv_bwd_weight);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_conv_bwd_weight);

profiler/src/profile_grouped_conv_fwd.cpp

@@ -25,11 +25,14 @@ enum struct ConvDataType
     INT8_INT8_INT8, // 3
 };
 
+#define OP_NAME "grouped_conv_fwd"
+#define OP_DESC "Grouped Convolution Forward"
+
 static void print_helper_msg()
 {
     std::cout
         // clang-format off
-        << "arg1: tensor operation (grouped_conv_fwd: Grouped Convolution Forward)\n"
+        << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
         << "arg2: data type (0: Input fp32, Weight fp32, Output fp32\n"
         << "                 1: Input fp16, Weight fp16, Output fp16\n"
         << "                 2: Input bf16, Weight bf16, Output bf16\n"
@@ -254,6 +257,4 @@ int profile_grouped_conv_fwd(int argc, char* argv[])
     return 1;
 }
 
-REGISTER_PROFILER_OPERATION("grouped_conv_fwd",
-                            "Grouped Convolution Forward",
-                            profile_grouped_conv_fwd);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_conv_fwd);

profiler/src/profile_grouped_gemm.cpp

@@ -45,11 +45,14 @@ std::vector<int> argToIntArray(char* input)
     return out;
 }
 
+#define OP_NAME "grouped_gemm"
+#define OP_DESC "Grouped GEMM"
+
 int profile_grouped_gemm(int argc, char* argv[])
 {
     if(!(argc == 14))
     {
-        printf("arg1: tensor operation (grouped_gemm: Grouped GEMM)\n");
+        printf("arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n");
         printf("arg2: data type (0: fp32; 1: fp16; 2: bf16; 3: int8)\n");
         printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
         printf("                     1: A[m, k] * B[n, k] = C[m, n];\n");
@@ -163,4 +166,4 @@ int profile_grouped_gemm(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("grouped_gemm", "Grouped GEMM", profile_grouped_gemm);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_grouped_gemm);

profiler/src/profile_groupnorm.cpp

@@ -44,9 +44,12 @@ struct GroupnormArgParser
     }
 };
 
+#define OP_NAME "groupnorm"
+#define OP_DESC "Group Normalization"
+
 void print_help_groupnorm()
 {
-    std::cout << "arg1: tensor operation (groupnorm: Group Normalization)\n"
+    std::cout << "arg1: tensor operation (" OP_NAME ": " OP_DESC ")\n"
               << "arg2: data type (0: fp16; 1: fp32)\n"
               << "arg3: verification (0: no; 1: yes)\n"
               << "arg4: initialization (0: no init; 1: integer value; 2: decimal value)\n"
@@ -106,4 +109,4 @@ int profile_groupnorm(int argc, char* argv[])
     return 0;
 }
 
-REGISTER_PROFILER_OPERATION("groupnorm", "Group Normalization", profile_groupnorm);
+REGISTER_PROFILER_OPERATION(OP_NAME, OP_DESC, profile_groupnorm);