Add grouped conv bwd weight dl instances and new layout (#897)

* Add grouped conv bwd weight dl instances and new layout

* Add M and N padding

* Remove todo comment

* Enable grouped conv fwd dl k,c=1 generic instance

* Comment fixes

library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight/device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_bf16_instance.cpp

@@ -2,7 +2,6 @@
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
 #include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
-
 #include "ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_xdl_instance.hpp"
 
 namespace ck {

library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight/device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_instance.cpp

@@ -2,7 +2,6 @@
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
 #include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
-
 #include "ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_xdl_instance.hpp"
 
 namespace ck {

library/src/tensor_operation_instance/gpu/grouped_conv3d_bwd_weight/device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f32_instance.cpp

@@ -2,7 +2,6 @@
 // Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
 
 #include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
-
 #include "ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_xdl_instance.hpp"
 
 namespace ck {

test/grouped_convnd_bwd_weight/test_grouped_convnd_bwd_weight.cpp

@@ -14,6 +14,8 @@
 
 #include "profiler/profile_grouped_conv_bwd_weight_impl.hpp"
 
+using namespace ck::tensor_layout::convolution;
+
 template <typename Tuple>
 class TestGroupedConvndBwdWeight : public ::testing::Test
 {
@@ -27,28 +29,59 @@ class TestGroupedConvndBwdWeight : public ::testing::Test
     using NDimSpatial = std::tuple_element_t<6, Tuple>;
 
     std::vector<ck::utils::conv::ConvParam> conv_params;
-    ck::index_t split_k{2};
+    std::vector<ck::index_t> split_ks{1, 2};
+
+    bool skip_case(const ck::utils::conv::ConvParam& params, const ck::index_t split_k)
+    {
+        // K or C are odd is supported only by DL kernel (only applies to fp16)
+        // DL kernel is only supported for split_k=1
+        if constexpr(std::is_same_v<InDataType, ck::half_t>)
+        {
+            if(split_k != 1 && (params.K_ % 2 != 0 || params.C_ % 2 != 0))
+            {
+                return true;
+            }
+        }
+
+        // 1d NWGC is only supported by DL kernel
+        // DL kernel is only supported for split_k=1
+        if constexpr(std::is_same_v<InLayout, NWGC> && std::is_same_v<OutLayout, NWGK>)
+        {
+            if(split_k != 1)
+            {
+                return true;
+            }
+        }
+
+        return false;
+    }
 
     void Run()
     {
         EXPECT_FALSE(conv_params.empty());
         bool pass = true;
 
-        for(auto& param : conv_params)
+        for(auto split_k : split_ks)
         {
-            pass = pass && ck::profiler::profile_grouped_conv_bwd_weight_impl<NDimSpatial{},
-                                                                              InLayout,
-                                                                              WeiLayout,
-                                                                              OutLayout,
-                                                                              InDataType,
-                                                                              WeiDataType,
-                                                                              OutDataType>(
-                               true,  // do_verification
-                               1,     // init_method: integer value
-                               false, // do_log
-                               false, // time_kernel
-                               param,
-                               split_k);
+            for(auto& param : conv_params)
+            {
+                if(!skip_case(param, split_k))
+                {
+                    pass = pass && ck::profiler::profile_grouped_conv_bwd_weight_impl<NDimSpatial{},
+                                                                                      InLayout,
+                                                                                      WeiLayout,
+                                                                                      OutLayout,
+                                                                                      InDataType,
+                                                                                      WeiDataType,
+                                                                                      OutDataType>(
+                                       true,  // do_verification
+                                       1,     // init_method: integer value
+                                       false, // do_log
+                                       false, // time_kernel
+                                       param,
+                                       split_k);
+                }
+            }
         }
         EXPECT_TRUE(pass);
     }
@@ -69,12 +102,13 @@ class TestGroupedConvndBwdWeight3d : public TestGroupedConvndBwdWeight<Tuple>
 {
 };
 
-using namespace ck::tensor_layout::convolution;
-
 using KernelTypes1d = ::testing::Types<
     std::tuple<float, float, float, GNWC, GKXC, GNWK, ck::Number<1>>,
     std::tuple<ck::half_t, ck::half_t, ck::half_t, GNWC, GKXC, GNWK, ck::Number<1>>,
-    std::tuple<ck::bhalf_t, float, ck::bhalf_t, GNWC, GKXC, GNWK, ck::Number<1>>>;
+    std::tuple<ck::bhalf_t, float, ck::bhalf_t, GNWC, GKXC, GNWK, ck::Number<1>>,
+    std::tuple<float, float, float, NWGC, GKXC, NWGK, ck::Number<1>>,
+    std::tuple<ck::half_t, ck::half_t, ck::half_t, NWGC, GKXC, NWGK, ck::Number<1>>,
+    std::tuple<ck::bhalf_t, float, ck::bhalf_t, NWGC, GKXC, NWGK, ck::Number<1>>>;
 using KernelTypes2d = ::testing::Types<
     std::tuple<float, float, float, GNHWC, GKYXC, GNHWK, ck::Number<2>>,
     std::tuple<ck::half_t, ck::half_t, ck::half_t, GNHWC, GKYXC, GNHWK, ck::Number<2>>,