clang-format

include/ck/tensor_operation/gpu/device/impl/device_grouped_gemm_xdl_splitk_cshuffle.hpp

@@ -265,10 +265,10 @@ struct DeviceGroupedGemmXdlSplitKCShuffle : public DeviceGroupedGemmSplitK<ALayo
                 const index_t stride_b = gemm_descs[i].stride_B_;
                 const index_t stride_c = gemm_descs[i].stride_C_;
 
-                const index_t m_padded = GridwiseGemm::CalculateMPadded(M);
-                const index_t n_padded = GridwiseGemm::CalculateNPadded(N);
-                const index_t k_padded = GridwiseGemm::CalculateKPadded(K, K_BATCH);
-                const index_t k0_padded       = GridwiseGemm::CalculateK0Padded(K, K_BATCH);
+                const index_t m_padded  = GridwiseGemm::CalculateMPadded(M);
+                const index_t n_padded  = GridwiseGemm::CalculateNPadded(N);
+                const index_t k_padded  = GridwiseGemm::CalculateKPadded(K, K_BATCH);
+                const index_t k0_padded = GridwiseGemm::CalculateK0Padded(K, K_BATCH);
 
                 const auto c_grid_desc_m_n = GridwiseGemm::MakeCGridDescriptor_M_N(M, N, stride_c);
 
@@ -320,8 +320,8 @@ struct DeviceGroupedGemmXdlSplitKCShuffle : public DeviceGroupedGemmSplitK<ALayo
 
                 auto& karg = gemm_kernel_args_[i].karg_;
 
-                const index_t k_padded = GridwiseGemm::CalculateKPadded(karg.K, K_BATCH);
-                const index_t k0_padded       = GridwiseGemm::CalculateK0Padded(karg.K, K_BATCH);
+                const index_t k_padded  = GridwiseGemm::CalculateKPadded(karg.K, K_BATCH);
+                const index_t k0_padded = GridwiseGemm::CalculateK0Padded(karg.K, K_BATCH);
 
                 const auto c_grid_desc_m_n =
                     GridwiseGemm::MakeCGridDescriptor_M_N(karg.M, karg.N, karg.StrideC);
@@ -340,7 +340,7 @@ struct DeviceGroupedGemmXdlSplitKCShuffle : public DeviceGroupedGemmSplitK<ALayo
                     GroupedGemmBlock2ETileMap(local_b2c_tile_map, block_start);
 
                 karg.KPadded                            = k_padded;
-                karg.K0Padded                                 = k0_padded;
+                karg.K0Padded                           = k0_padded;
                 karg.k_batch                            = K_BATCH;
                 gemm_kernel_args_[i].block_2_ctile_map_ = grouped_block_2_ctile_map;
                 gemm_kernel_args_[i].block_start_       = block_start;

library/include/ck/library/tensor_operation_instance/gpu/grouped_gemm.hpp

@@ -133,8 +133,6 @@ void add_device_grouped_gemm_xdl_splitk_f16_f8_f16_mk_kn_mn_irregular_instances(
                                                   PassThrough,
                                                   PassThrough>>>& instances);
 
-
-
 template <typename ALayout,
           typename BLayout,
           typename ELayout,
@@ -199,13 +197,13 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
                 add_device_grouped_gemm_xdl_f16_f16_f16_km_nk_mn_instances(op_ptrs);
             }
         }
-	else if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, f8_t> &&
-                     is_same_v<EDataType, half_t>)
+        else if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, f8_t> &&
+                          is_same_v<EDataType, half_t>)
         {
-		if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
+            if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
                          is_same_v<ELayout, Row>)
             {
-		    add_device_grouped_gemm_xdl_splitk_f16_f8_f16_mk_kn_mn_irregular_instances(op_ptrs);
+                add_device_grouped_gemm_xdl_splitk_f16_f8_f16_mk_kn_mn_irregular_instances(op_ptrs);
             }
         }
         return op_ptrs;

profiler/src/profile_grouped_gemm.cpp

@@ -27,7 +27,7 @@ enum struct GemmDataType
     F16_F16_F16,    // 1
     BF16_BF16_BF16, // 2
     INT8_INT8_INT8, // 3
-    F16_F8_F16,    // 4
+    F16_F8_F16,     // 4
 };
 
 #define OP_NAME "grouped_gemm"