Verify more tests on floating point data

CMakePresets.json

@@ -66,7 +66,8 @@
             "cacheVariables": {
                 "GPU_TARGETS": "gfx90a",
                 "CMAKE_BUILD_TYPE": "Release",
-                "CMAKE_CXX_FLAGS": "-O3"
+                "CMAKE_CXX_FLAGS": "-O3",
+                "CK_USE_FP8_ON_UNSUPPORTED_ARCH":"ON"
             }
         },
         {
@@ -76,7 +77,8 @@
             "cacheVariables": {
                 "GPU_TARGETS": "gfx90a",
                 "CMAKE_BUILD_TYPE": "Debug",
-                "CMAKE_CXX_FLAGS": "-O0 -ggdb"
+                "CMAKE_CXX_FLAGS": "-O0 -ggdb",
+                "CK_USE_FP8_ON_UNSUPPORTED_ARCH":"ON"
             }
         },
         {

example/01_gemm/run_gemm_example_streamk_v2.inc

@@ -162,12 +162,12 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config)
         b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-2, 2});
         break;
     case 2:
-        a_m_k.GenerateTensorValue(GeneratorTensor_1<ADataType>{1});
-        b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-2, 2});
+        a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
+        b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-2, 2});
         break;
     case 3:
-        a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-2, 2});
-        b_k_n.GenerateTensorValue(GeneratorTensor_1<BDataType>{1});
+        a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{-2, 2});
+        b_k_n.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
         break;
     default:
         a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});

example/01_gemm/run_gemm_example_v2.inc

@@ -146,19 +146,11 @@ bool run_gemm(const ProblemType& problem_size, const ExecutionConfig& config)
         b_k_n.GenerateTensorValue(GeneratorTensor_1<BDataType>{1});
         break;
     case 1:
-        a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-2, 2});
-        b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-2, 2});
-        break;
-    case 2:
-        a_m_k.GenerateTensorValue(GeneratorTensor_1<ADataType>{1});
-        b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-2, 2});
-        break;
-    case 3:
-        a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-2, 2});
-        b_k_n.GenerateTensorValue(GeneratorTensor_1<BDataType>{1});
+        a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{-2, 2});
+        b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-3, 3});
         break;
     default:
-        a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
+        a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{-1.0, 1.0});
         b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
     }
 

example/15_grouped_gemm/grouped_gemm_xdl_fixed_nk_fp16_fp8.cpp

@@ -75,7 +75,7 @@ struct ProblemSize final
 struct ExecutionConfig final
 {
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 2;
     int k_batch          = 1;
     bool time_kernel     = false;
 };

example/62_convnd_activ/convinvscale/run_convnd_fwd_convinvscale_example.inc

@@ -8,7 +8,7 @@ bool run_convnd_fwd_example(int argc, char* argv[])
     print_helper_msg();
 
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 2;
     bool time_kernel     = false;
 
     ck::utils::conv::ConvParam conv_param{

example/62_convnd_activ/convscale/run_convnd_fwd_convscale_example.inc

@@ -8,7 +8,7 @@ bool run_convnd_fwd_example(int argc, char* argv[])
     print_helper_msg();
 
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 2;
     bool time_kernel     = false;
 
     ck::utils::conv::ConvParam conv_param{

example/62_convnd_activ/convscale_add/run_convnd_fwd_convscale_add_example.inc

@@ -8,7 +8,7 @@ bool run_convnd_fwd_example(int argc, char* argv[])
     print_helper_msg();
 
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 2;
     bool time_kernel     = false;
 
     ck::utils::conv::ConvParam conv_param{

example/62_convnd_activ/convscale_reduce/run_convnd_fwd_example.inc

@@ -8,7 +8,7 @@ bool run_convnd_fwd_example(int argc, char* argv[])
     print_helper_msg();
 
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 2;
     bool time_kernel     = false;
 
     ck::utils::conv::ConvParam conv_param{

example/62_convnd_activ/convscale_relu/run_convnd_fwd_convscale_relu_example.inc

@@ -8,7 +8,7 @@ bool run_convnd_fwd_example(int argc, char* argv[])
     print_helper_msg();
 
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 2;
     bool time_kernel     = false;
 
     ck::utils::conv::ConvParam conv_param{

example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8.cpp

@@ -86,7 +86,7 @@ using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultiD_Xdl_CShu
 int main(int argc, char* argv[])
 {
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 2;
     bool time_kernel     = false;
 
     // GEMM shape

example/65_gemm_multiply_multiply/gemm_multiply_multiply_xdl_fp8_ab_scale.cpp

@@ -78,7 +78,7 @@ using DeviceOpInstance = ck::tensor_operation::device::DeviceGemmMultiD_ABScale_
 int main(int argc, char* argv[])
 {
     bool do_verification = true;
-    int init_method      = 1;
+    int init_method      = 5;
     bool time_kernel     = false;
 
     // GEMM shape
@@ -186,6 +186,20 @@ int main(int argc, char* argv[])
         b0_k_n.GenerateTensorValue(GeneratorTensor_1<B0DataType>{});
         a1_m_k.GenerateTensorValue(GeneratorTensor_3<A1DataType>{0, 1.0});
         b1_k_n.GenerateTensorValue(GeneratorTensor_3<B1DataType>{0, 1.0});
+        break;
+    case 6:
+        a0_m_k.GenerateTensorValue(GeneratorTensor_PI<ADataType>{});
+        b0_k_n.GenerateTensorValue(GeneratorTensor_1<BDataType>{0.5f});
+        a1_m_k.GenerateTensorValue(GeneratorTensor_1<A1DataType>{0.5});
+        b1_k_n.GenerateTensorValue(GeneratorTensor_1<B1DataType>{4});
+
+        break;
+    case 7:
+        a0_m_k.GenerateTensorValue(GeneratorTensor_PI_A<ADataType>{});
+        b0_k_n.GenerateTensorValue(GeneratorTensor_PI_B<BDataType>{});
+        a1_m_k.GenerateTensorValue(GeneratorTensor_1<A1DataType>{2});
+        b1_k_n.GenerateTensorValue(GeneratorTensor_1<B1DataType>{0.5});
+
         break;
     default:
         a0_m_k.GenerateTensorValue(GeneratorTensor_3<A0DataType>{-0.5, 0.5});
@@ -306,6 +320,32 @@ int main(int argc, char* argv[])
 
         e_device_buf.FromDevice(e_m_n_device_result.mData.data());
 
+        if(init_method == 6 || init_method == 7)
+        {
+            std::cout << std::fixed << std::setprecision(16);
+
+            float a = ck::type_convert<float>(a0_device_buf(0, 10));
+            float b = ck::type_convert<float>(b0_device_buf(0, 10));
+            std::cout << "a(0,10): " << a << std::endl;
+            std::cout << "b(0,10): " << b << std::endl;
+            std::cout << "a: " << ck::type_convert<float>(a0_device_buf(0, 0)) << std::endl;
+            std::cout << "a: " << ck::type_convert<float>(a0_device_buf(0, 1)) << std::endl;
+            std::cout << "a: " << ck::type_convert<float>(a0_device_buf(0, 2)) << std::endl;
+            std::cout << "b: " << ck::type_convert<float>(b0_device_buf(0, 0)) << std::endl;
+            std::cout << "b: " << ck::type_convert<float>(b0_device_buf(1, 0)) << std::endl;
+            std::cout << "b: " << ck::type_convert<float>(b0_device_buf(2, 0)) << std::endl;
+
+            float d = ck::type_convert<float>(e_m_n_device_result(0, 10));
+            float h = ck::type_convert<float>(e_m_n_host_result(10, 0));
+            std::cout << "device result: " << d << std::endl;
+            std::cout << "host result: " << h << std::endl;
+            std::cout << "expected result: " << M_PI << std::endl;
+            std::cout << "device - host: " << std::abs(d - h) << std::endl;
+            std::cout << "device - expected: " << std::abs(d - M_PI) << std::endl;
+            std::cout << "atol: " << 5e-2 << std::endl;
+            std::cout << std::endl << std::endl;
+        }
+
         return ck::utils::check_err(
                    e_m_n_device_result, e_m_n_host_result, "Error: Incorrect results!", 5e-2, 5e-2)
                    ? 0